Sample records for target detection range

  1. Detection of Fast Moving and Accelerating Targets Compensating Range and Doppler Migration

    DTIC Science & Technology

    2014-06-01

    Radon -Fourier transform has been introduced to realize long- term coherent integration of the moving targets with range migration [8, 9]. Radon ...2010) Long-time coherent integration for radar target detection base on Radon -Fourier transform, in Proceedings of the IEEE Radar Conference, pp...432–436. 9. Xu, J., Yu, J., Peng, Y. & Xia, X. (2011) Radon -Fourier transform for radar target detection, I: Generalized Doppler filter bank, IEEE

  2. Laser range profiling for small target recognition

    NASA Astrophysics Data System (ADS)

    Steinvall, Ove; Tulldahl, Michael

    2016-05-01

    The detection and classification of small surface and airborne targets at long ranges is a growing need for naval security. Long range ID or ID at closer range of small targets has its limitations in imaging due to the demand on very high transverse sensor resolution. It is therefore motivated to look for 1D laser techniques for target ID. These include vibrometry, and laser range profiling. Vibrometry can give good results but is also sensitive to certain vibrating parts on the target being in the field of view. Laser range profiling is attractive because the maximum range can be substantial, especially for a small laser beam width. A range profiler can also be used in a scanning mode to detect targets within a certain sector. The same laser can also be used for active imaging when the target comes closer and is angular resolved. The present paper will show both experimental and simulated results for laser range profiling of small boats out to 6-7 km range and a UAV mockup at close range (1.3 km). We obtained good results with the profiling system both for target detection and recognition. Comparison of experimental and simulated range waveforms based on CAD models of the target support the idea of having a profiling system as a first recognition sensor and thus narrowing the search space for the automatic target recognition based on imaging at close ranges. The naval experiments took place in the Baltic Sea with many other active and passive EO sensors beside the profiling system. Discussion of data fusion between laser profiling and imaging systems will be given. The UAV experiments were made from the rooftop laboratory at FOI.

  3. Effects of Resolution, Range, and Image Contrast on Target Acquisition Performance.

    PubMed

    Hollands, Justin G; Terhaar, Phil; Pavlovic, Nada J

    2018-05-01

    We sought to determine the joint influence of resolution, target range, and image contrast on the detection and identification of targets in simulated naturalistic scenes. Resolution requirements for target acquisition have been developed based on threshold values obtained using imaging systems, when target range was fixed, and image characteristics were determined by the system. Subsequent work has examined the influence of factors like target range and image contrast on target acquisition. We varied the resolution and contrast of static images in two experiments. Participants (soldiers) decided whether a human target was located in the scene (detection task) or whether a target was friendly or hostile (identification task). Target range was also varied (50-400 m). In Experiment 1, 30 participants saw color images with a single target exemplar. In Experiment 2, another 30 participants saw monochrome images containing different target exemplars. The effects of target range and image contrast were qualitatively different above and below 6 pixels per meter of target for both tasks in both experiments. Target detection and identification performance were a joint function of image resolution, range, and contrast for both color and monochrome images. The beneficial effects of increasing resolution for target acquisition performance are greater for closer (larger) targets.

  4. Moving target detection in flash mode against stroboscopic mode by active range-gated laser imaging

    NASA Astrophysics Data System (ADS)

    Zhang, Xuanyu; Wang, Xinwei; Sun, Liang; Fan, Songtao; Lei, Pingshun; Zhou, Yan; Liu, Yuliang

    2018-01-01

    Moving target detection is important for the application of target tracking and remote surveillance in active range-gated laser imaging. This technique has two operation modes based on the difference of the number of pulses per frame: stroboscopic mode with the accumulation of multiple laser pulses per frame and flash mode with a single shot of laser pulse per frame. In this paper, we have established a range-gated laser imaging system. In the system, two types of lasers with different frequency were chosen for the two modes. Electric fan and horizontal sliding track were selected as the moving targets to compare the moving blurring between two modes. Consequently, the system working in flash mode shows more excellent performance in motion blurring against stroboscopic mode. Furthermore, based on experiments and theoretical analysis, we presented the higher signal-to-noise ratio of image acquired by stroboscopic mode than flash mode in indoor and underwater environment.

  5. Target discrimination strategies in optics detection

    NASA Astrophysics Data System (ADS)

    Sjöqvist, Lars; Allard, Lars; Henriksson, Markus; Jonsson, Per; Pettersson, Magnus

    2013-10-01

    Detection and localisation of optical assemblies used for weapon guidance or sniper rifle scopes has attracted interest for security and military applications. Typically a laser system is used to interrogate a scene of interest and the retro-reflected radiation is detected. Different system approaches for area coverage can be realised ranging from flood illumination to step-and-stare or continuous scanning schemes. Independently of the chosen approach target discrimination is a crucial issue, particularly if a complex scene such as in an urban environment and autonomous operation is considered. In this work target discrimination strategies in optics detection are discussed. Typical parameters affecting the reflected laser radiation from the target are the wavelength, polarisation properties, temporal effects and the range resolution. Knowledge about the target characteristics is important to predict the target discrimination capability. Two different systems were used to investigate polarisation properties and range resolution information from targets including e.g. road signs, optical reflexes, rifle sights and optical references. The experimental results and implications on target discrimination will be discussed. If autonomous operation is required target discrimination becomes critical in order to reduce the number of false alarms.

  6. Lidar detection algorithm for time and range anomalies.

    PubMed

    Ben-David, Avishai; Davidson, Charles E; Vanderbeek, Richard G

    2007-10-10

    A new detection algorithm for lidar applications has been developed. The detection is based on hyperspectral anomaly detection that is implemented for time anomaly where the question "is a target (aerosol cloud) present at range R within time t(1) to t(2)" is addressed, and for range anomaly where the question "is a target present at time t within ranges R(1) and R(2)" is addressed. A detection score significantly different in magnitude from the detection scores for background measurements suggests that an anomaly (interpreted as the presence of a target signal in space/time) exists. The algorithm employs an option for a preprocessing stage where undesired oscillations and artifacts are filtered out with a low-rank orthogonal projection technique. The filtering technique adaptively removes the one over range-squared dependence of the background contribution of the lidar signal and also aids visualization of features in the data when the signal-to-noise ratio is low. A Gaussian-mixture probability model for two hypotheses (anomaly present or absent) is computed with an expectation-maximization algorithm to produce a detection threshold and probabilities of detection and false alarm. Results of the algorithm for CO(2) lidar measurements of bioaerosol clouds Bacillus atrophaeus (formerly known as Bacillus subtilis niger, BG) and Pantoea agglomerans, Pa (formerly known as Erwinia herbicola, Eh) are shown and discussed.

  7. Laser range profiling for small target recognition

    NASA Astrophysics Data System (ADS)

    Steinvall, Ove; Tulldahl, Michael

    2017-03-01

    Long range identification (ID) or ID at closer range of small targets has its limitations in imaging due to the demand for very high-transverse sensor resolution. This is, therefore, a motivation to look for one-dimensional laser techniques for target ID. These include laser vibrometry and laser range profiling. Laser vibrometry can give good results, but is not always robust as it is sensitive to certain vibrating parts on the target being in the field of view. Laser range profiling is attractive because the maximum range can be substantial, especially for a small laser beam width. A range profiler can also be used in a scanning mode to detect targets within a certain sector. The same laser can also be used for active imaging when the target comes closer and is angularly resolved. Our laser range profiler is based on a laser with a pulse width of 6 ns (full width half maximum). This paper will show both experimental and simulated results for laser range profiling of small boats out to a 6 to 7-km range and a unmanned arrial vehicle (UAV) mockup at close range (1.3 km). The naval experiments took place in the Baltic Sea using many other active and passive electro-optical sensors in addition to the profiling system. The UAV experiments showed the need for a high-range resolution, thus we used a photon counting system in addition to the more conventional profiler used in the naval experiments. This paper shows the influence of target pose and range resolution on the capability of classification. The typical resolution (in our case 0.7 m) obtainable with a conventional range finder type of sensor can be used for large target classification with a depth structure over 5 to 10 m or more, but for smaller targets such as a UAV a high resolution (in our case 7.5 mm) is needed to reveal depth structures and surface shapes. This paper also shows the need for 3-D target information to build libraries for comparison of measured and simulated range profiles. At closer ranges

  8. Influence of target reflection on three-dimensional range gated reconstruction.

    PubMed

    Chua, Sing Yee; Wang, Xin; Guo, Ningqun; Tan, Ching Seong

    2016-08-20

    The range gated technique is a promising laser ranging method that is widely used in different fields such as surveillance, industry, and military. In a range gated system, a reflected laser pulse returned from the target scene contains key information for range reconstruction, which directly affects the system performance. Therefore, it is necessary to study the characteristics and effects of the target reflection factor. In this paper, theoretical and experimental analyses are performed to investigate the influence of target reflection on three-dimensional (3D) range gated reconstruction. Based on laser detection and ranging (LADAR) and bidirectional reflection distribution function (BRDF) theory, a 3D range gated reconstruction model is derived and the effect on range accuracy is analyzed from the perspectives of target surface reflectivity and angle of laser incidence. Our theoretical and experimental study shows that the range accuracy is proportional to the target surface reflectivity, but it decreases when the angle of incidence increases to adhere to the BRDF model. The presented findings establish a comprehensive understanding of target reflection in 3D range gated reconstruction, which is of interest to various applications such as target recognition and object modeling. This paper provides a reference for future improvement to perform accurate range compensation or correction.

  9. Performing target specific band reduction using artificial neural networks and assessment of its efficacy using various target detection algorithms

    NASA Astrophysics Data System (ADS)

    Yadav, Deepti; Arora, M. K.; Tiwari, K. C.; Ghosh, J. K.

    2016-04-01

    Hyperspectral imaging is a powerful tool in the field of remote sensing and has been used for many applications like mineral detection, detection of landmines, target detection etc. Major issues in target detection using HSI are spectral variability, noise, small size of the target, huge data dimensions, high computation cost, complex backgrounds etc. Many of the popular detection algorithms do not work for difficult targets like small, camouflaged etc. and may result in high false alarms. Thus, target/background discrimination is a key issue and therefore analyzing target's behaviour in realistic environments is crucial for the accurate interpretation of hyperspectral imagery. Use of standard libraries for studying target's spectral behaviour has limitation that targets are measured in different environmental conditions than application. This study uses the spectral data of the same target which is used during collection of the HSI image. This paper analyze spectrums of targets in a way that each target can be spectrally distinguished from a mixture of spectral data. Artificial neural network (ANN) has been used to identify the spectral range for reducing data and further its efficacy for improving target detection is verified. The results of ANN proposes discriminating band range for targets; these ranges were further used to perform target detection using four popular spectral matching target detection algorithm. Further, the results of algorithms were analyzed using ROC curves to evaluate the effectiveness of the ranges suggested by ANN over full spectrum for detection of desired targets. In addition, comparative assessment of algorithms is also performed using ROC.

  10. Real-time multisensor data fusion for target detection, classification, tracking, counting, and range estimates

    NASA Astrophysics Data System (ADS)

    Tsui, Eddy K.; Thomas, Russell L.

    2004-09-01

    As part of the Commanding General of Army Material Command's Research, Development & Engineering Command (RDECOM), the U.S. Army Research Development and Engineering Center (ARDEC), Picatinny funded a joint development effort with McQ Associates, Inc. to develop an Advanced Minefield Sensor (AMS) as a technology evaluation prototype for the Anti-Personnel Landmine Alternatives (APLA) Track III program. This effort laid the fundamental groundwork of smart sensors for detection and classification of targets, identification of combatant or noncombatant, target location and tracking at and between sensors, fusion of information across targets and sensors, and automatic situation awareness to the 1st responder. The efforts have culminated in developing a performance oriented architecture meeting the requirements of size, weight, and power (SWAP). The integrated digital signal processor (DSP) paradigm is capable of computing signals from sensor modalities to extract needed information within either a 360° or fixed field of view with acceptable false alarm rate. This paper discusses the challenges in the developments of such a sensor, focusing on achieving reasonable operating ranges, achieving low power, small size and low cost, and applications for extensions of this technology.

  11. Approach range and velocity determination using laser sensors and retroreflector targets

    NASA Technical Reports Server (NTRS)

    Donovan, William J.

    1991-01-01

    A laser docking sensor study is currently in the third year of development. The design concept is considered to be validated. The concept is based on using standard radar techniques to provide range, velocity, and bearing information. Multiple targets are utilized to provide relative attitude data. The design requirements were to utilize existing space-qualifiable technology and require low system power, weight, and size yet, operate from 0.3 to 150 meters with a range accuracy greater than 3 millimeters and a range rate accuracy greater than 3 mm per second. The field of regard for the system is +/- 20 deg. The transmitter and receiver design features a diode laser, microlens beam steering, and power control as a function of range. The target design consists of five target sets, each having seven 3-inch retroreflectors, arranged around the docking port. The target map is stored in the sensor memory. Phase detection is used for ranging, with the frequency range-optimized. Coarse bearing measurement is provided by the scanning system (one set of binary optics) angle. Fine bearing measurement is provided by a quad detector. A MIL-STD-1750 A/B computer is used for processing. Initial test results indicate a probability of detection greater than 99 percent and a probability of false alarm less than 0.0001. The functional system is currently at the MIT/Lincoln Lab for demonstration.

  12. Underwater single beam circumferentially scanning detection system using range-gated receiver and adaptive filter

    NASA Astrophysics Data System (ADS)

    Tan, Yayun; Zhang, He; Zha, Bingting

    2017-09-01

    Underwater target detection and ranging in seawater are of interest in unmanned underwater vehicles. This study presents an underwater detection system that synchronously scans a collimated laser beam and a narrow field of view to circumferentially detect an underwater target. Hybrid methods of range-gated and variable step-size least mean squares (VSS-LMS) adaptive filter are proposed to suppress water backscattering. The range-gated receiver eliminates the backscattering of near-field water. The VSS-LMS filter extracts the target echo in the remaining backscattering and the constant fraction discriminator timing method is used to improve ranging accuracy. The optimal constant fraction is selected by analysing the jitter noise and slope of the target echo. The prototype of the underwater detection system is constructed and tested in coastal seawater, then the effectiveness of backscattering suppression and high-ranging accuracy is verified through experimental results and analysis discussed in this paper.

  13. Cumulative detection probabilities and range accuracy of a pulsed Geiger-mode avalanche photodiode laser ranging system

    NASA Astrophysics Data System (ADS)

    Luo, Hanjun; Ouyang, Zhengbiao; Liu, Qiang; Chen, Zhiliang; Lu, Hualan

    2017-10-01

    Cumulative pulses detection with appropriate cumulative pulses number and threshold has the ability to improve the detection performance of the pulsed laser ranging system with GM-APD. In this paper, based on Poisson statistics and multi-pulses cumulative process, the cumulative detection probabilities and their influence factors are investigated. With the normalized probability distribution of each time bin, the theoretical model of the range accuracy and precision is established, and the factors limiting the range accuracy and precision are discussed. The results show that the cumulative pulses detection can produce higher target detection probability and lower false alarm probability. However, for a heavy noise level and extremely weak echo intensity, the false alarm suppression performance of the cumulative pulses detection deteriorates quickly. The range accuracy and precision is another important parameter evaluating the detection performance, the echo intensity and pulse width are main influence factors on the range accuracy and precision, and higher range accuracy and precision is acquired with stronger echo intensity and narrower echo pulse width, for 5-ns echo pulse width, when the echo intensity is larger than 10, the range accuracy and precision lower than 7.5 cm can be achieved.

  14. Synthetic aperture radar target detection, feature extraction, and image formation techniques

    NASA Technical Reports Server (NTRS)

    Li, Jian

    1994-01-01

    This report presents new algorithms for target detection, feature extraction, and image formation with the synthetic aperture radar (SAR) technology. For target detection, we consider target detection with SAR and coherent subtraction. We also study how the image false alarm rates are related to the target template false alarm rates when target templates are used for target detection. For feature extraction from SAR images, we present a computationally efficient eigenstructure-based 2D-MODE algorithm for two-dimensional frequency estimation. For SAR image formation, we present a robust parametric data model for estimating high resolution range signatures of radar targets and for forming high resolution SAR images.

  15. Quantum Illumination-Based Target Detection and Discrimination

    DTIC Science & Technology

    2014-06-30

    amplifier (EDFA) was combined with the signal to simulate a high-noise environment, with a noise photon number per mode NB in the range 40–300. The...Research Triangle Park, NC 27709-2211 quantum communication, target detection, entanglement , parametric downconversion, optical parametric amplifiers...laser system of the same average transmitted photon number, when the target return has random-amplitude behavior. Receiver operating characteristic

  16. Improved target detection by IR dual-band image fusion

    NASA Astrophysics Data System (ADS)

    Adomeit, U.; Ebert, R.

    2009-09-01

    Dual-band thermal imagers acquire information simultaneously in both the 8-12 μm (long-wave infrared, LWIR) and the 3-5 μm (mid-wave infrared, MWIR) spectral range. Compared to single-band thermal imagers they are expected to have several advantages in military applications. These advantages include the opportunity to use the best band for given atmospheric conditions (e. g. cold climate: LWIR, hot and humid climate: MWIR), the potential to better detect camouflaged targets and an improved discrimination between targets and decoys. Most of these advantages have not yet been verified and/or quantified. It is expected that image fusion allows better exploitation of the information content available with dual-band imagers especially with respect to detection of targets. We have developed a method for dual-band image fusion based on the apparent temperature differences in the two bands. This method showed promising results in laboratory tests. In order to evaluate its performance under operational conditions we conducted a field trial in an area with high thermal clutter. In such areas, targets are hardly to detect in single-band images because they vanish in the clutter structure. The image data collected in this field trial was used for a perception experiment. This perception experiment showed an enhanced target detection range and reduced false alarm rate for the fused images compared to the single-band images.

  17. Adaptive waveform optimization design for target detection in cognitive radar

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaowen; Wang, Kaizhi; Liu, Xingzhao

    2017-01-01

    The problem of adaptive waveform design for target detection in cognitive radar (CR) is investigated. This problem is analyzed in signal-dependent interference, as well as additive channel noise for extended target with unknown target impulse response (TIR). In order to estimate the TIR accurately, the Kalman filter is used in target tracking. In each Kalman filtering iteration, a flexible online waveform spectrum optimization design taking both detection and range resolution into account is modeled in Fourier domain. Unlike existing CR waveform, the proposed waveform can be simultaneously updated according to the environment information fed back by receiver and radar performance demands. Moreover, the influence of waveform spectral phase to radar performance is analyzed. Simulation results demonstrate that CR with the proposed waveform performs better than a traditional radar system with a fixed waveform and offers more flexibility and suitability. In addition, waveform spectral phase will not influence tracking, detection, and range resolution performance but will greatly influence waveform forming speed and peak-to-average power ratio.

  18. 32 CFR 644.526 - Reporting target ranges.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 32 National Defense 4 2010-07-01 2010-07-01 true Reporting target ranges. 644.526 Section 644.526... and Improvements § 644.526 Reporting target ranges. All Reports of Excess to GSA covering lands which have been used as target ranges of any kind will contain an affirmative or negative statement in regard...

  19. 32 CFR 644.526 - Reporting target ranges.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 32 National Defense 4 2011-07-01 2011-07-01 false Reporting target ranges. 644.526 Section 644.526... and Improvements § 644.526 Reporting target ranges. All Reports of Excess to GSA covering lands which have been used as target ranges of any kind will contain an affirmative or negative statement in regard...

  20. Comparison of human and algorithmic target detection in passive infrared imagery

    NASA Astrophysics Data System (ADS)

    Weber, Bruce A.; Hutchinson, Meredith

    2003-09-01

    We have designed an experiment that compares the performance of human observers and a scale-insensitive target detection algorithm that uses pixel level information for the detection of ground targets in passive infrared imagery. The test database contains targets near clutter whose detectability ranged from easy to very difficult. Results indicate that human observers detect more "easy-to-detect" targets, and with far fewer false alarms, than the algorithm. For "difficult-to-detect" targets, human and algorithm detection rates are considerably degraded, and algorithm false alarms excessive. Analysis of detections as a function of observer confidence shows that algorithm confidence attribution does not correspond to human attribution, and does not adequately correlate with correct detections. The best target detection score for any human observer was 84%, as compared to 55% for the algorithm for the same false alarm rate. At 81%, the maximum detection score for the algorithm, the same human observer had 6 false alarms per frame as compared to 29 for the algorithm. Detector ROC curves and observer-confidence analysis benchmarks the algorithm and provides insights into algorithm deficiencies and possible paths to improvement.

  1. The simulation study on optical target laser active detection performance

    NASA Astrophysics Data System (ADS)

    Li, Ying-chun; Hou, Zhao-fei; Fan, Youchen

    2014-12-01

    According to the working principle of laser active detection system, the paper establishes the optical target laser active detection simulation system, carry out the simulation study on the detection process and detection performance of the system. For instance, the performance model such as the laser emitting, the laser propagation in the atmosphere, the reflection of optical target, the receiver detection system, the signal processing and recognition. We focus on the analysis and modeling the relationship between the laser emitting angle and defocus amount and "cat eye" effect echo laser in the reflection of optical target. Further, in the paper some performance index such as operating range, SNR and the probability of the system have been simulated. The parameters including laser emitting parameters, the reflection of the optical target and the laser propagation in the atmosphere which make a great influence on the performance of the optical target laser active detection system. Finally, using the object-oriented software design methods, the laser active detection system with the opening type, complete function and operating platform, realizes the process simulation that the detection system detect and recognize the optical target, complete the performance simulation of each subsystem, and generate the data report and the graph. It can make the laser active detection system performance models more intuitive because of the visible simulation process. The simulation data obtained from the system provide a reference to adjust the structure of the system parameters. And it provides theoretical and technical support for the top level design of the optical target laser active detection system and performance index optimization.

  2. Top-attack modeling and automatic target detection using synthetic FLIR scenery

    NASA Astrophysics Data System (ADS)

    Weber, Bruce A.; Penn, Joseph A.

    2004-09-01

    A series of experiments have been performed to verify the utility of algorithmic tools for the modeling and analysis of cold-target signatures in synthetic, top-attack, FLIR video sequences. The tools include: MuSES/CREATION for the creation of synthetic imagery with targets, an ARL target detection algorithm to detect imbedded synthetic targets in scenes, and an ARL scoring algorithm, using Receiver-Operating-Characteristic (ROC) curve analysis, to evaluate detector performance. Cold-target detection variability was examined as a function of target emissivity, surrounding clutter type, and target placement in non-obscuring clutter locations. Detector metrics were also individually scored so as to characterize the effect of signature/clutter variations. Results show that using these tools, a detailed, physically meaningful, target detection analysis is possible and that scenario specific target detectors may be developed by selective choice and/or weighting of detector metrics. However, developing these tools into a reliable predictive capability will require the extension of these results to the modeling and analysis of a large number of data sets configured for a wide range of target and clutter conditions. Finally, these tools should also be useful for the comparison of competitive detection algorithms by providing well defined, and controllable target detection scenarios, as well as for the training and testing of expert human observers.

  3. ADRPM-VII applied to the long-range acoustic detection problem

    NASA Technical Reports Server (NTRS)

    Shalis, Edward; Koenig, Gerald

    1990-01-01

    An acoustic detection range prediction model (ADRPM-VII) has been written for IBM PC/AT machines running on the MS-DOS operating system. The software allows the user to predict detection distances of ground combat vehicles and their associated targets when they are involved in quasi-military settings. The program can also calculate individual attenuation losses due to spherical spreading, atmospheric absorption, ground reflection and atmospheric refraction due to temperature and wind gradients while varying parameters effecting the source-receiver problem. The purpose here is to examine the strengths and limitations of ADRPM-VII by modeling the losses due to atmospheric refraction and ground absorption, commonly known as excess attenuation, when applied to the long range detection problem for distances greater than 3 kilometers.

  4. Effects of age and eccentricity on visual target detection.

    PubMed

    Gruber, Nicole; Müri, René M; Mosimann, Urs P; Bieri, Rahel; Aeschimann, Andrea; Zito, Giuseppe A; Urwyler, Prabitha; Nyffeler, Thomas; Nef, Tobias

    2013-01-01

    The aim of this study was to examine the effects of aging and target eccentricity on a visual search task comprising 30 images of everyday life projected into a hemisphere, realizing a ±90° visual field. The task performed binocularly allowed participants to freely move their eyes to scan images for an appearing target or distractor stimulus (presented at 10°; 30°, and 50° eccentricity). The distractor stimulus required no response, while the target stimulus required acknowledgment by pressing the response button. One hundred and seventeen healthy subjects (mean age = 49.63 years, SD = 17.40 years, age range 20-78 years) were studied. The results show that target detection performance decreases with age as well as with increasing eccentricity, especially for older subjects. Reaction time also increases with age and eccentricity, but in contrast to target detection, there is no interaction between age and eccentricity. Eye movement analysis showed that younger subjects exhibited a passive search strategy while older subjects exhibited an active search strategy probably as a compensation for their reduced peripheral detection performance.

  5. A new method for detecting small and dim targets in starry background

    NASA Astrophysics Data System (ADS)

    Yao, Rui; Zhang, Yanning; Jiang, Lei

    2011-08-01

    Small visible optical space targets detection is one of the key issues in the research of long-range early warning and space debris surveillance. The SNR(Signal to Noise Ratio) of the target is very low because of the self influence of image device. Random noise and background movement also increase the difficulty of target detection. In order to detect small visible optical space targets effectively and rapidly, we bring up a novel detecting method based on statistic theory. Firstly, we get a reasonable statistical model of visible optical space image. Secondly, we extract SIFT(Scale-Invariant Feature Transform) feature of the image frames, and calculate the transform relationship, then use the transform relationship to compensate whole visual field's movement. Thirdly, the influence of star was wiped off by using interframe difference method. We find segmentation threshold to differentiate candidate targets and noise by using OTSU method. Finally, we calculate statistical quantity to judge whether there is the target for every pixel position in the image. Theory analysis shows the relationship of false alarm probability and detection probability at different SNR. The experiment result shows that this method could detect target efficiently, even the target passing through stars.

  6. Analysis of the infrared detection system operating range based on polarization degree

    NASA Astrophysics Data System (ADS)

    Jiang, Kai; Liu, Wen; Liu, Kai; Duan, Jing; Yan, Pei-pei; Shan, Qiu-sha

    2018-02-01

    Infrared polarization detection technology has unique advantages in the field of target detection and identification because of using the polarization information of radiation. The mechanism of infrared polarization is introduced. Comparing with traditional infrared detection distance model, infrared detection operating range and Signal to Noise Ratio (SNR) model is built according to the polarization degree and noise. The influence of polarization degree on the SNR of infrared system is analyzed. At last, the basic condition of polarization detection SNR better than traditional infrared detection SNR is obtained.

  7. Detection of Marine Radar Targets

    NASA Astrophysics Data System (ADS)

    Briggs, John N.

    A radar must detect targets before it can display them. Yet manufacturers' data sheets rarely tell us what the products will detect at what range. Many of the bigger radars are Type Approved so we consult the relevant IMO performance standard A 477 (XII). Paraphrasing Section 3.1 of the draft forthcoming revision (NAV 41/6): under normal propagation conditions with the scanner at height of 15 m, in the absence of clutter, the radar is required to give clear indication of an object such as a navigational buoy having a radar cross section area (RCS) of 10 m2 at 2 n.m. and, as examples, coastlines whose ground rises to 60/6 m at ranges of 20/7 n.m., a ship of 5000 tons at any aspect at 7 n.m. and a small vessel 10 m long at 3 n.m.This helps, but suppose we must pick up a 5 m2 buoy at g km? What happens in clutter? Should we prefer S- or X-band? To answer such questions we use equations which define the performance of surveillance radars, but the textbooks and specialist papers containing them often generalize with aeronautical and defence topics, making life difficult for the nonspecialist.This paper attempts a concise and self-contained engineering account of all main factors affecting detection of passive and active targets on civil marine and vessel traffic service (VTS) radars. We develop a set of equations for X- and S-band (3 and 10 cm, centred on 9400 and 3000 MHz respectively), suited for spreadsheet calculation.Sufficient theory is sketched in to indicate where results should be valid. Some simplifications of conventional treatments have been identified.

  8. Multisensor fusion for the detection of mines and minelike targets

    NASA Astrophysics Data System (ADS)

    Hanshaw, Terilee

    1995-06-01

    The US Army's Communications and Electronics Command through the auspices of its Night Vision and Electronics Sensors Directorate (CECOM-NVESD) is actively applying multisensor techniques to the detection of mine targets. This multisensor research results from the 'detection activity' with its broad range of operational conditions and targets. Multisensor operation justifies significant attention by yielding high target detection and low false alarm statistics. Furthermore, recent advances in sensor and computing technologies make its practical application realistic and affordable. The mine detection field-of-endeavor has since its WWI baptismal investigated the known spectra for applicable mine observation phenomena. Countless sensors, algorithms, processors, networks, and other techniques have been investigated to determine candidacy for mine detection. CECOM-NVESD efforts have addressed a wide range of sensors spanning the spectrum from gravity field perturbations, magentic field disturbances, seismic sounding, electromagnetic fields, earth penetrating radar imagery, and infrared/visible/ultraviolet surface imaging technologies. Supplementary analysis has considered sensor candidate applicability by testing under field conditions (versus laboratory), in determination of fieldability. As these field conditions directly effect the probability of detection and false alarms, sensor employment and design must be considered. Consequently, as a given sensor's performance is influenced directly by the operational conditions, tradeoffs are necessary. At present, mass produced and fielded mine detection techniques are limited to those incorporating a single sensor/processor methodology such as, pulse induction and megnetometry, as found in hand held detectors. The most sensitive fielded systems can detect minute metal components in small mine targets but result in very high false alarm rates reducing velocity in operation environments. Furthermore, the actual speed of

  9. Personal glucose meters for detection and quantification of a broad range of analytes

    DOEpatents

    Lu, Yi; Xiang, Yu

    2015-02-03

    A general methodology for the development of highly sensitive and selective sensors that can achieve portable, low-cost and quantitative detection of a broad range of targets using only a personal glucose meter (PGM) is disclosed. The method uses recognition molecules that are specific for a target agent, enzymes that can convert an enzyme substrate into glucose, and PGM. Also provided are sensors, which can include a solid support to which is attached a recognition molecule that permits detection of a target agent, wherein the recognition molecule specifically binds to the target agent in the presence of the target agent but not significantly to other agents as well as an enzyme that can catalyze the conversion of a substance into glucose, wherein the enzyme is attached directly or indirectly to the recognition molecule, and wherein in the presence of the target agent the enzyme can convert the substance into glucose. The disclosed sensors can be part of a lateral flow device. Methods of using such sensors for detecting target agents are also provided.

  10. Detection and classification of underwater targets by echolocating dolphins

    NASA Astrophysics Data System (ADS)

    Au, Whitlow

    2003-10-01

    Many experiments have been performed with echolocating dolphins to determine their target detection and discrimination capabilities. Target detection experiments have been performed in a naturally noisy environment, with masking noise and with both phantom echoes and masking noise, and in reverberation. The echo energy to rms noise spectral density for the Atlantic bottlenose dolphin (Tursiops truncatus) at the 75% correct response threshold is approximately 7.5 dB whereas for the beluga whale (Delphinapterus leucas) the threshold is approximately 1 dB. The dolphin's detection threshold in reverberation is approximately 2.5 dB vs 2 dB for the beluga. The difference in performance between species can probably be ascribed to differences in how both species perceived the task. The bottlenose dolphin may be performing a combination detection/discrimination task whereas the beluga may be performing a simple detection task. Echolocating dolphins also have the capability to make fine discriminate of target properties such as wall thickness difference of water-filled cylinders and material differences in metallic plates. The high resolution property of the animal's echolocation signals and the high dynamic range of its auditory system are important factors in their outstanding discrimination capabilities.

  11. Beyond the margins: real-time detection of cancer using targeted fluorophores

    PubMed Central

    Zhang, Ray R.; Schroeder, Alexandra B.; Grudzinski, Joseph J.; Rosenthal, Eben L.; Warram, Jason M.; Pinchuk, Anatoly N.; Eliceiri, Kevin W.; Kuo, John S.; Weichert, Jamey P.

    2017-01-01

    Over the past two decades, synergistic innovations in imaging technology have resulted in a revolution in which a range of biomedical applications are now benefiting from fluorescence imaging. Specifically, advances in fluorophore chemistry and imaging hardware, and the identification of targetable biomarkers have now positioned intraoperative fluorescence as a highly specific real-time detection modality for surgeons in oncology. In particular, the deeper tissue penetration and limited autofluorescence of near-infrared (NIR) fluorescence imaging improves the translational potential of this modality over visible-light fluorescence imaging. Rapid developments in fluorophores with improved characteristics, detection instrumentation, and targeting strategies led to the clinical testing in the early 2010s of the first targeted NIR fluorophores for intraoperative cancer detection. The foundations for the advances that underline this technology continue to be nurtured by the multidisciplinary collaboration of chemists, biologists, engineers, and clinicians. In this Review, we highlight the latest developments in NIR fluorophores, cancer-targeting strategies, and detection instrumentation for intraoperative cancer detection, and consider the unique challenges associated with their effective application in clinical settings. PMID:28094261

  12. Location detection and tracking of moving targets by a 2D IR-UWB radar system.

    PubMed

    Nguyen, Van-Han; Pyun, Jae-Young

    2015-03-19

    In indoor environments, the Global Positioning System (GPS) and long-range tracking radar systems are not optimal, because of signal propagation limitations in the indoor environment. In recent years, the use of ultra-wide band (UWB) technology has become a possible solution for object detection, localization and tracking in indoor environments, because of its high range resolution, compact size and low cost. This paper presents improved target detection and tracking techniques for moving objects with impulse-radio UWB (IR-UWB) radar in a short-range indoor area. This is achieved through signal-processing steps, such as clutter reduction, target detection, target localization and tracking. In this paper, we introduce a new combination consisting of our proposed signal-processing procedures. In the clutter-reduction step, a filtering method that uses a Kalman filter (KF) is proposed. Then, in the target detection step, a modification of the conventional CLEAN algorithm which is used to estimate the impulse response from observation region is applied for the advanced elimination of false alarms. Then, the output is fed into the target localization and tracking step, in which the target location and trajectory are determined and tracked by using unscented KF in two-dimensional coordinates. In each step, the proposed methods are compared to conventional methods to demonstrate the differences in performance. The experiments are carried out using actual IR-UWB radar under different scenarios. The results verify that the proposed methods can improve the probability and efficiency of target detection and tracking.

  13. Effect of radar frequency on the detection of shaped (low RCS) targets

    NASA Astrophysics Data System (ADS)

    Moraitis, D.; Alland, S.

    The use of shaping to reduce the radar cross-section (RCS) of aircraft and missiles can result in the RCS varying significantly with radar operating frequency. This RCS sensitivity to frequency should be considered when selecting radar frequency and should be accounted for when evaluating radar performance. A detection range increase for shaped (low RCS) targets of a factor of two or greater can be realized for lower frequency radar (e.g., UHF-Band or L-Band) when compared to higher frequency radar (C-Band or X-Band). For low flying (sea skimming) targets, the RCS variation with frequency for shaped (low RCS) targets neutralizes the advantage that higher radar frequencies realize in multipath propagation resulting in approximately the same detection range across the radar bands from UHF to X-Band.

  14. The application and research of the multi-receiving telescopes technology in laser ranging to space targets

    NASA Astrophysics Data System (ADS)

    Wu, Zhibo; Zhang, Haifeng; Zhang, Zhongping; Deng, Huarong; Li, Pu; Meng, Wendong; Cheng, Zhien; Shen, Lurun; Tang, Zhenhong

    2014-11-01

    Laser ranging technology can directly measure the distance between space targets and ground stations with the highest measurement precision and will play an irreplaceable role in orbit check and calibrating microwave measurement system. The precise orbit determination and accurate catalogue of space targets can also be realized by laser ranging with multi-stations. Among space targets, most of ones are inactive targets and space debris, which should be paid the great attentions for the safety of active spacecrafts. Because of laser diffuse reflection from the surface of targets, laser ranging to space debris has the characteristics of wide coverage and weak strength of laser echoes, even though the powerful laser system is applied. In order to increase the receiving ability of laser echoes, the large aperture telescope should be adopted. As well known, some disadvantages for one set of large aperture telescope, technical development difficulty and system running and maintenance complexity, will limit its flexible applications. The multi-receiving telescopes technology in laser ranging to space targets is put forward to realize the equivalent receiving ability produced by one larger aperture telescope by way of using multi-receiving telescopes, with the advantages of flexibility and maintenance. The theoretical analysis of the feasibility and key technologies of multi-receiving telescopes technology in laser ranging to space targets are presented in this paper. The experimental measurement system based on the 60cm SLR system and 1.56m astronomical telescopes with a distance of about 50m is established to provide the platform for researching on the multi-receiving telescopes technology. The laser ranging experiments to satellites equipped with retro-reflectors are successfully performed by using the above experimental system and verify the technical feasibility to increase the ability of echo detection. And the multi-receiving telescopes technology will become a

  15. A Technique for Real-Time Ionospheric Ranging Error Correction Based On Radar Dual-Frequency Detection

    NASA Astrophysics Data System (ADS)

    Lyu, Jiang-Tao; Zhou, Chen

    2017-12-01

    Ionospheric refraction is one of the principal error sources for limiting the accuracy of radar systems for space target detection. High-accuracy measurement of the ionospheric electron density along the propagation path of radar wave is the most important procedure for the ionospheric refraction correction. Traditionally, the ionospheric model and the ionospheric detection instruments, like ionosonde or GPS receivers, are employed for obtaining the electron density. However, both methods are not capable of satisfying the requirements of correction accuracy for the advanced space target radar system. In this study, we propose a novel technique for ionospheric refraction correction based on radar dual-frequency detection. Radar target range measurements at two adjacent frequencies are utilized for calculating the electron density integral exactly along the propagation path of the radar wave, which can generate accurate ionospheric range correction. The implementation of radar dual-frequency detection is validated by a P band radar located in midlatitude China. The experimental results present that the accuracy of this novel technique is more accurate than the traditional ionospheric model correction. The technique proposed in this study is very promising for the high-accuracy radar detection and tracking of objects in geospace.

  16. Tracking Honey Bees Using LIDAR (Light Detection and Ranging) Technology

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    BENDER, SUSAN FAE ANN; RODACY, PHILIP J.; SCHMITT, RANDAL L.

    The Defense Advanced Research Projects Agency (DARPA) has recognized that biological and chemical toxins are a real and growing threat to troops, civilians, and the ecosystem. The Explosives Components Facility at Sandia National Laboratories (SNL) has been working with the University of Montana, the Southwest Research Institute, and other agencies to evaluate the feasibility of directing honeybees to specific targets, and for environmental sampling of biological and chemical ''agents of harm''. Recent work has focused on finding and locating buried landmines and unexploded ordnance (UXO). Tests have demonstrated that honeybees can be trained to efficiently and accurately locate explosive signaturesmore » in the environment. However, it is difficult to visually track the bees and determine precisely where the targets are located. Video equipment is not practical due to its limited resolution and range. In addition, it is often unsafe to install such equipment in a field. A technology is needed to provide investigators with the standoff capability to track bees and accurately map the location of the suspected targets. This report documents Light Detection and Ranging (LIDAR) tests that were performed by SNL. These tests have shown that a LIDAR system can be used to track honeybees. The LIDAR system can provide both the range and coordinates of the target so that the location of buried munitions can be accurately mapped for subsequent removal.« less

  17. Detecting targets hidden in random forests

    NASA Astrophysics Data System (ADS)

    Kouritzin, Michael A.; Luo, Dandan; Newton, Fraser; Wu, Biao

    2009-05-01

    Military tanks, cargo or troop carriers, missile carriers or rocket launchers often hide themselves from detection in the forests. This plagues the detection problem of locating these hidden targets. An electro-optic camera mounted on a surveillance aircraft or unmanned aerial vehicle is used to capture the images of the forests with possible hidden targets, e.g., rocket launchers. We consider random forests of longitudinal and latitudinal correlations. Specifically, foliage coverage is encoded with a binary representation (i.e., foliage or no foliage), and is correlated in adjacent regions. We address the detection problem of camouflaged targets hidden in random forests by building memory into the observations. In particular, we propose an efficient algorithm to generate random forests, ground, and camouflage of hidden targets with two dimensional correlations. The observations are a sequence of snapshots consisting of foliage-obscured ground or target. Theoretically, detection is possible because there are subtle differences in the correlations of the ground and camouflage of the rocket launcher. However, these differences are well beyond human perception. To detect the presence of hidden targets automatically, we develop a Markov representation for these sequences and modify the classical filtering equations to allow the Markov chain observation. Particle filters are used to estimate the position of the targets in combination with a novel random weighting technique. Furthermore, we give positive proof-of-concept simulations.

  18. Visual performance on detection tasks with double-targets of the same and different difficulty.

    PubMed

    Chan, Alan H S; Courtney, Alan J; Ma, C W

    2002-10-20

    This paper reports a study of measurement of horizontal visual sensitivity limits for 16 subjects in single-target and double-targets detection tasks. Two phases of tests were conducted in the double-targets task; targets of the same difficulty were tested in phase one while targets of different difficulty were tested in phase two. The range of sensitivity for the double-targets test was found to be smaller than that for single-target in both the same and different target difficulty cases. The presence of another target was found to affect performance to a marked degree. Interference effect of the difficult target on detection of the easy one was greater than that of the easy one on the detection of the difficult one. Performance decrement was noted when correct percentage detection was plotted against eccentricity of target in both the single-target and double-targets tests. Nevertheless, the non-significant correlation found between the performance for the two tasks demonstrated that it was impossible to predict quantitatively ability for detection of double targets from the data for single targets. This indicated probable problems in generalizing data for single target visual lobes to those for multiple targets. Also lobe area values obtained from measurements using a single-target task cannot be applied in a mathematical model for situations with multiple occurrences of targets.

  19. Space moving target detection using time domain feature

    NASA Astrophysics Data System (ADS)

    Wang, Min; Chen, Jin-yong; Gao, Feng; Zhao, Jin-yu

    2018-01-01

    The traditional space target detection methods mainly use the spatial characteristics of the star map to detect the targets, which can not make full use of the time domain information. This paper presents a new space moving target detection method based on time domain features. We firstly construct the time spectral data of star map, then analyze the time domain features of the main objects (target, stars and the background) in star maps, finally detect the moving targets using single pulse feature of the time domain signal. The real star map target detection experimental results show that the proposed method can effectively detect the trajectory of moving targets in the star map sequence, and the detection probability achieves 99% when the false alarm rate is about 8×10-5, which outperforms those of compared algorithms.

  20. A new EMI system for detection and classification of challenging targets

    NASA Astrophysics Data System (ADS)

    Shubitidze, F.; Fernández, J. P.; Barrowes, B. E.; O'Neill, K.

    2013-06-01

    Advanced electromagnetic induction (EMI) sensors currently feature multi-axis illumination of targets and tri-axial vector sensing (e.g., MetalMapper), or exploit multi-static array data acquisition (e.g., TEMTADS). They produce data of high density, quality, and diversity, and have been combined with advanced EMI models to provide superb classification performance relative to the previous generation of single-axis, monostatic sensors. However, these advances yet have to improve significantly our ability to classify small, deep, and otherwise challenging targets. Particularly, recent live-site discrimination studies at Camp Butner, NC and Camp Beale, CA have revealed that it is more challenging to detect and discriminate small munitions (with calibers ranging from 20 mm to 60 mm) than larger ones. In addition, a live-site test at the Massachusetts Military Reservation, MA highlighted the difficulties for current sensors to classify large, deep, and overlapping targets with high confidence. There are two main approaches to overcome these problems: 1) adapt advanced EMI models to the existing systems and 2) improve the detection limits of current sensors by modifying their hardware. In this paper we demonstrate a combined software/hardware approach that will provide extended detection range and spatial resolution to next-generation EMI systems; we analyze and invert EMI data to extract classification features for small and deep targets; and we propose a new system that features a large transmitter coil.

  1. System considerations for detection and tracking of small targets using passive sensors

    NASA Astrophysics Data System (ADS)

    DeBell, David A.

    1991-08-01

    Passive sensors provide only a few discriminants to assist in threat assessment of small targets. Tracking of the small targets provides additional discriminants. This paper discusses the system considerations for tracking small targets using passive sensors, in particular EO sensors. Tracking helps establish good versus bad detections. Discussed are the requirements to be placed on the sensor system's accuracy, with respect to knowledge of the sightline direction. The detection of weak targets sets a requirement for two levels of tracking in order to reduce processor throughput. A system characteristic is the need to track all detections. For low thresholds, this can mean a heavy track burden. Therefore, thresholds must be adaptive in order not to saturate the processors. Second-level tracks must develop a range estimate in order to assess threat. Sensor platform maneuvers are required if the targets are moving. The need for accurate pointing, good stability, and a good update rate will be shown quantitatively, relating to track accuracy and track association.

  2. Covariance descriptor fusion for target detection

    NASA Astrophysics Data System (ADS)

    Cukur, Huseyin; Binol, Hamidullah; Bal, Abdullah; Yavuz, Fatih

    2016-05-01

    Target detection is one of the most important topics for military or civilian applications. In order to address such detection tasks, hyperspectral imaging sensors provide useful images data containing both spatial and spectral information. Target detection has various challenging scenarios for hyperspectral images. To overcome these challenges, covariance descriptor presents many advantages. Detection capability of the conventional covariance descriptor technique can be improved by fusion methods. In this paper, hyperspectral bands are clustered according to inter-bands correlation. Target detection is then realized by fusion of covariance descriptor results based on the band clusters. The proposed combination technique is denoted Covariance Descriptor Fusion (CDF). The efficiency of the CDF is evaluated by applying to hyperspectral imagery to detect man-made objects. The obtained results show that the CDF presents better performance than the conventional covariance descriptor.

  3. Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

    PubMed Central

    Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

    2016-01-01

    Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated

  4. Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection.

    PubMed

    Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

    2016-07-19

    Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated

  5. UGS video target detection and discrimination

    NASA Astrophysics Data System (ADS)

    Roberts, G. Marlon; Fitzgerald, James; McCormack, Michael; Steadman, Robert; Vitale, Joseph D.

    2007-04-01

    This project focuses on developing electro-optic algorithms which rank images by their likelihood of containing vehicles and people. These algorithms have been applied to images obtained from Textron's Terrain Commander 2 (TC2) Unattended Ground Sensor system. The TC2 is a multi-sensor surveillance system used in military applications. It combines infrared, acoustic, seismic, magnetic, and electro-optic sensors to detect nearby targets. When targets are detected by the seismic and acoustic sensors, the system is triggered and images are taken in the visible and infrared spectrum. The original Terrain Commander system occasionally captured and transmitted an excessive number of images, sometimes triggered by undesirable targets such as swaying trees. This wasted communications bandwidth, increased power consumption, and resulted in a large amount of end-user time being spent evaluating unimportant images. The algorithms discussed here help alleviate these problems. These algorithms are currently optimized for infra-red images, which give the best visibility in a wide range of environments, but could be adapted to visible imagery as well. It is important that the algorithms be robust, with minimal dependency on user input. They should be effective when tracking varying numbers of targets of different sizes and orientations, despite the low resolutions of the images used. Most importantly, the algorithms must be appropriate for implementation on a low-power processor in real time. This would enable us to maintain frame rates of 2 Hz for effective surveillance operations. Throughout our project we have implemented several algorithms, and used an appropriate methodology to quantitatively compare their performance. They are discussed in this paper.

  6. A method for detecting small targets based on cumulative weighted value of target properties

    NASA Astrophysics Data System (ADS)

    Jin, Xing; Sun, Gang; Wang, Wei-hua; Liu, Fang; Chen, Zeng-ping

    2015-03-01

    Laser detection based on the "cat's eye effect" has become the hot research project for its initiative compared to the passivity of sound detection and infrared detection. And the target detection is one of the core technologies in this system. The paper puts forward a method for detecting small targets based on cumulative weighted value of target properties using given data. Firstly, we make a frame difference to the images, then make image processing based on Morphology Principles. Secondly, we segment images, and screen the targets; then find some interesting locations. Finally, comparing to a quantity of frames, we locate the target. We did an exam to 394 true frames, the experimental result shows that the mathod can detect small targets efficiently.

  7. Improving detection of low SNR targets using moment-based detection

    NASA Astrophysics Data System (ADS)

    Young, Shannon R.; Steward, Bryan J.; Hawks, Michael; Gross, Kevin C.

    2016-05-01

    Increases in the number of cameras deployed, frame rate, and detector array sizes have led to a dramatic increase in the volume of motion imagery data that is collected. Without a corresponding increase in analytical manpower, much of the data is not analyzed to full potential. This creates a need for fast, automated, and robust methods for detecting signals of interest. Current approaches fall into two categories: detect-before-track (DBT), which are fast but often poor at detecting dim targets, and track-before-detect (TBD) methods which can offer better performance but are typically much slower. This research seeks to contribute to the near real time detection of low SNR, unresolved moving targets through an extension of earlier work on higher order moments anomaly detection, a method that exploits both spatial and temporal information but is still computationally efficient and massively parallelizable. It was found that intelligent selection of parameters can improve probability of detection by as much as 25% compared to earlier work with higherorder moments. The present method can reduce detection thresholds by 40% compared to the Reed-Xiaoli anomaly detector for low SNR targets (for a given probability of detection and false alarm).

  8. Detection technique of targets for missile defense system

    NASA Astrophysics Data System (ADS)

    Guo, Hua-ling; Deng, Jia-hao; Cai, Ke-rong

    2009-11-01

    Ballistic missile defense system (BMDS) is a weapon system for intercepting enemy ballistic missiles. It includes ballistic-missile warning system, target discrimination system, anti-ballistic-missile guidance systems, and command-control communication system. Infrared imaging detection and laser imaging detection are widely used in BMDS for surveillance, target detection, target tracking, and target discrimination. Based on a comprehensive review of the application of target-detection techniques in the missile defense system, including infrared focal plane arrays (IRFPA), ground-based radar detection technology, 3-dimensional imaging laser radar with a photon counting avalanche photodiode (APD) arrays and microchip laser, this paper focuses on the infrared and laser imaging detection techniques in missile defense system, as well as the trends for their future development.

  9. Long-range depth profiling of camouflaged targets using single-photon detection

    NASA Astrophysics Data System (ADS)

    Tobin, Rachael; Halimi, Abderrahim; McCarthy, Aongus; Ren, Ximing; McEwan, Kenneth J.; McLaughlin, Stephen; Buller, Gerald S.

    2018-03-01

    We investigate the reconstruction of depth and intensity profiles from data acquired using a custom-designed time-of-flight scanning transceiver based on the time-correlated single-photon counting technique. The system had an operational wavelength of 1550 nm and used a Peltier-cooled InGaAs/InP single-photon avalanche diode detector. Measurements were made of human figures, in plain view and obscured by camouflage netting, from a stand-off distance of 230 m in daylight using only submilliwatt average optical powers. These measurements were analyzed using a pixelwise cross correlation approach and compared to analysis using a bespoke algorithm designed for the restoration of multilayered three-dimensional light detection and ranging images. This algorithm is based on the optimization of a convex cost function composed of a data fidelity term and regularization terms, and the results obtained show that it achieves significant improvements in image quality for multidepth scenarios and for reduced acquisition times.

  10. Golay Complementary Waveforms in Reed–Müller Sequences for Radar Detection of Nonzero Doppler Targets

    PubMed Central

    Wang, Xuezhi; Huang, Xiaotao; Suvorova, Sofia; Moran, Bill

    2018-01-01

    Golay complementary waveforms can, in theory, yield radar returns of high range resolution with essentially zero sidelobes. In practice, when deployed conventionally, while high signal-to-noise ratios can be achieved for static target detection, significant range sidelobes are generated by target returns of nonzero Doppler causing unreliable detection. We consider signal processing techniques using Golay complementary waveforms to improve radar detection performance in scenarios involving multiple nonzero Doppler targets. A signal processing procedure based on an existing, so called, Binomial Design algorithm that alters the transmission order of Golay complementary waveforms and weights the returns is proposed in an attempt to achieve an enhanced illumination performance. The procedure applies one of three proposed waveform transmission ordering algorithms, followed by a pointwise nonlinear processor combining the outputs of the Binomial Design algorithm and one of the ordering algorithms. The computational complexity of the Binomial Design algorithm and the three ordering algorithms are compared, and a statistical analysis of the performance of the pointwise nonlinear processing is given. Estimation of the areas in the Delay–Doppler map occupied by significant range sidelobes for given targets are also discussed. Numerical simulations for the comparison of the performances of the Binomial Design algorithm and the three ordering algorithms are presented for both fixed and randomized target locations. The simulation results demonstrate that the proposed signal processing procedure has a better detection performance in terms of lower sidelobes and higher Doppler resolution in the presence of multiple nonzero Doppler targets compared to existing methods. PMID:29324708

  11. Highly sensitive detection of target molecules using a new fluorescence-based bead assay

    NASA Astrophysics Data System (ADS)

    Scheffler, Silvia; Strauß, Denis; Sauer, Markus

    2007-07-01

    Development of immunoassays with improved sensitivity, specificity and reliability are of major interest in modern bioanalytical research. We describe the development of a new immunomagnetic fluorescence detection (IM-FD) assay based on specific antigen/antibody interactions and on accumulation of the fluorescence signal on superparamagnetic PE beads in combination with the use of extrinsic fluorescent labels. IM-FD can be easily modified by varying the order of coatings and assay conditions. Depending on the target molecule, antibodies (ABs), entire proteins, or small protein epitopes can be used as capture molecules. The presence of target molecules is detected by fluorescence microscopy using fluorescently labeled secondary or detection antibodies. Here, we demonstrate the potential of the new assay detecting the two tumor markers IGF-I and p53 antibodies in the clinically relevant concentration range. Our data show that the fluorescence-based bead assay exhibits a large dynamic range and a high sensitivity down to the subpicomolar level.

  12. Specification for a surface-search radar-detection-range model

    NASA Astrophysics Data System (ADS)

    Hattan, Claude P.

    1990-09-01

    A model that predicts surface-search radar detection range versus a variety of combatants has been developed at the Naval Ocean Systems Center. This model uses a simplified ship radar cross section (RCS) model and the U.S. Navy Oceanographic and Atmospheric Mission Library Standard Electromagnetic Propagation Model. It provides the user with a method of assessing the effects of the environment of the performance of a surface-search radar system. The software implementation of the model is written in ANSI FORTRAN 77, with MIL-STD-1753 extensions. The program provides the user with a table of expected detection ranges when the model is supplied with the proper environmental radar system inputs. The target model includes the variation in RCS as a function of aspect angle and the distribution of reflected radar energy as a function of height above the waterline. The modeled propagation effects include refraction caused by a multisegmented refractivity profile, sea-surface roughness caused by local winds, evaporation ducting, and surface-based ducts caused by atmospheric layering.

  13. Infrared dim target detection based on visual attention

    NASA Astrophysics Data System (ADS)

    Wang, Xin; Lv, Guofang; Xu, Lizhong

    2012-11-01

    Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. Based on human visual attention mechanisms, an automatic detection algorithm for infrared dim target is presented. After analyzing the characteristics of infrared dim target images, the method firstly designs Difference of Gaussians (DoG) filters to compute the saliency map. Then the salient regions where the potential targets exist in are extracted by searching through the saliency map with a control mechanism of winner-take-all (WTA) competition and inhibition-of-return (IOR). At last, these regions are identified by the characteristics of the dim IR targets, so the true targets are detected, and the spurious objects are rejected. The experiments are performed for some real-life IR images, and the results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection.

  14. Lifting wavelet method of target detection

    NASA Astrophysics Data System (ADS)

    Han, Jun; Zhang, Chi; Jiang, Xu; Wang, Fang; Zhang, Jin

    2009-11-01

    Image target recognition plays a very important role in the areas of scientific exploration, aeronautics and space-to-ground observation, photography and topographic mapping. Complex environment of the image noise, fuzzy, all kinds of interference has always been to affect the stability of recognition algorithm. In this paper, the existence of target detection in real-time, accuracy problems, as well as anti-interference ability, using lifting wavelet image target detection methods. First of all, the use of histogram equalization, the goal difference method to obtain the region, on the basis of adaptive threshold and mathematical morphology operations to deal with the elimination of the background error. Secondly, the use of multi-channel wavelet filter wavelet transform of the original image de-noising and enhancement, to overcome the general algorithm of the noise caused by the sensitive issue of reducing the rate of miscarriage of justice will be the multi-resolution characteristics of wavelet and promotion of the framework can be designed directly in the benefits of space-time region used in target detection, feature extraction of targets. The experimental results show that the design of lifting wavelet has solved the movement of the target due to the complexity of the context of the difficulties caused by testing, which can effectively suppress noise, and improve the efficiency and speed of detection.

  15. Multiple targets detection method in detection of UWB through-wall radar

    NASA Astrophysics Data System (ADS)

    Yang, Xiuwei; Yang, Chuanfa; Zhao, Xingwen; Tian, Xianzhong

    2017-11-01

    In this paper, the problems and difficulties encountered in the detection of multiple moving targets by UWB radar are analyzed. The experimental environment and the penetrating radar system are established. An adaptive threshold method based on local area is proposed to effectively filter out clutter interference The objective of the moving target is analyzed, and the false target is further filtered out by extracting the target feature. Based on the correlation between the targets, the target matching algorithm is proposed to improve the detection accuracy. Finally, the effectiveness of the above method is verified by practical experiment.

  16. Range estimation of passive infrared targets through the atmosphere

    NASA Astrophysics Data System (ADS)

    Cho, Hoonkyung; Chun, Joohwan; Seo, Doochun; Choi, Seokweon

    2013-04-01

    Target range estimation is traditionally based on radar and active sonar systems in modern combat systems. However, jamming signals tremendously degrade the performance of such active sensor devices. We introduce a simple target range estimation method and the fundamental limits of the proposed method based on the atmosphere propagation model. Since passive infrared (IR) sensors measure IR signals radiating from objects in different wavelengths, this method has robustness against electromagnetic jamming. The measured target radiance of each wavelength at the IR sensor depends on the emissive properties of target material and various attenuation factors (i.e., the distance between sensor and target and atmosphere environment parameters). MODTRAN is a tool that models atmospheric propagation of electromagnetic radiation. Based on the results from MODTRAN and atmosphere propagation-based modeling, the target range can be estimated. To analyze the proposed method's performance statistically, we use maximum likelihood estimation (MLE) and evaluate the Cramer-Rao lower bound (CRLB) via the probability density function of measured radiance. We also compare CRLB and the variance of MLE using Monte-Carlo simulation.

  17. 3D range-gated super-resolution imaging based on stereo matching for moving platforms and targets

    NASA Astrophysics Data System (ADS)

    Sun, Liang; Wang, Xinwei; Zhou, Yan

    2017-11-01

    3D range-gated superresolution imaging is a novel 3D reconstruction technique for target detection and recognition with good real-time performance. However, for moving targets or platforms such as airborne, shipborne, remote operated vehicle and autonomous vehicle, 3D reconstruction has a large error or failure. In order to overcome this drawback, we propose a method of stereo matching for 3D range-gated superresolution reconstruction algorithm. In experiment, the target is a doll of Mario with a height of 38cm at the location of 34m, and we obtain two successive frame images of the Mario. To confirm our method is effective, we transform the original images with translation, rotation, scale and perspective, respectively. The experimental result shows that our method has a good result of 3D reconstruction for moving targets or platforms.

  18. Range detection using entangled optical photons

    NASA Astrophysics Data System (ADS)

    Brandsema, Matthew J.; Narayanan, Ram M.; Lanzagorta, Marco

    2015-05-01

    Quantum radar is an emerging field that shows a lot of promise in providing significantly improved resolution compared to its classical radar counterpart. The key to this kind of resolution lies in the correlations created from the entanglement of the photons being used. Currently, the technology available only supports quantum radar implementation and validation in the optical regime, as opposed to the microwave regime, because microwave photons have very low energy compared to optical photons. Furthermore, there currently do not exist practical single photon detectors and generators in the microwave spectrum. Viable applications in the optical regime include deep sea target detection and high resolution detection in space. In this paper, we propose a conceptual architecture of a quantum radar which uses entangled optical photons based on Spontaneous Parametric Down Conversion (SPDC) methods. After the entangled photons are created and emerge from the crystal, the idler photon is detected very shortly thereafter. At the same time, the signal photon is sent out towards the target and upon its reflection will impinge on the detector of the radar. From these two measurements, correlation data processing is done to obtain the distance of the target away from the radar. Various simulations are then shown to display the resolution that is possible.

  19. Fast range estimation based on active range-gated imaging for coastal surveillance

    NASA Astrophysics Data System (ADS)

    Kong, Qingshan; Cao, Yinan; Wang, Xinwei; Tong, Youwan; Zhou, Yan; Liu, Yuliang

    2012-11-01

    Coastal surveillance is very important because it is useful for search and rescue, illegal immigration, or harbor security and so on. Furthermore, range estimation is critical for precisely detecting the target. Range-gated laser imaging sensor is suitable for high accuracy range especially in night and no moonlight. Generally, before detecting the target, it is necessary to change delay time till the target is captured. There are two operating mode for range-gated imaging sensor, one is passive imaging mode, and the other is gate viewing mode. Firstly, the sensor is passive mode, only capturing scenes by ICCD, once the object appears in the range of monitoring area, we can obtain the course range of the target according to the imaging geometry/projecting transform. Then, the sensor is gate viewing mode, applying micro second laser pulses and sensor gate width, we can get the range of targets by at least two continuous images with trapezoid-shaped range intensity profile. This technique enables super-resolution depth mapping with a reduction of imaging data processing. Based on the first step, we can calculate the rough value and quickly fix delay time which the target is detected. This technique has overcome the depth resolution limitation for 3D active imaging and enables super-resolution depth mapping with a reduction of imaging data processing. By the two steps, we can quickly obtain the distance between the object and sensor.

  20. NAIMA: target amplification strategy allowing quantitative on-chip detection of GMOs.

    PubMed

    Morisset, Dany; Dobnik, David; Hamels, Sandrine; Zel, Jana; Gruden, Kristina

    2008-10-01

    We have developed a novel multiplex quantitative DNA-based target amplification method suitable for sensitive, specific and quantitative detection on microarray. This new method named NASBA Implemented Microarray Analysis (NAIMA) was applied to GMO detection in food and feed, but its application can be extended to all fields of biology requiring simultaneous detection of low copy number DNA targets. In a first step, the use of tailed primers allows the multiplex synthesis of template DNAs in a primer extension reaction. A second step of the procedure consists of transcription-based amplification using universal primers. The cRNA product is further on directly ligated to fluorescent dyes labelled 3DNA dendrimers allowing signal amplification and hybridized without further purification on an oligonucleotide probe-based microarray for multiplex detection. Two triplex systems have been applied to test maize samples containing several transgenic lines, and NAIMA has shown to be sensitive down to two target copies and to provide quantitative data on the transgenic contents in a range of 0.1-25%. Performances of NAIMA are comparable to singleplex quantitative real-time PCR. In addition, NAIMA amplification is faster since 20 min are sufficient to achieve full amplification.

  1. NAIMA: target amplification strategy allowing quantitative on-chip detection of GMOs

    PubMed Central

    Morisset, Dany; Dobnik, David; Hamels, Sandrine; Žel, Jana; Gruden, Kristina

    2008-01-01

    We have developed a novel multiplex quantitative DNA-based target amplification method suitable for sensitive, specific and quantitative detection on microarray. This new method named NASBA Implemented Microarray Analysis (NAIMA) was applied to GMO detection in food and feed, but its application can be extended to all fields of biology requiring simultaneous detection of low copy number DNA targets. In a first step, the use of tailed primers allows the multiplex synthesis of template DNAs in a primer extension reaction. A second step of the procedure consists of transcription-based amplification using universal primers. The cRNA product is further on directly ligated to fluorescent dyes labelled 3DNA dendrimers allowing signal amplification and hybridized without further purification on an oligonucleotide probe-based microarray for multiplex detection. Two triplex systems have been applied to test maize samples containing several transgenic lines, and NAIMA has shown to be sensitive down to two target copies and to provide quantitative data on the transgenic contents in a range of 0.1–25%. Performances of NAIMA are comparable to singleplex quantitative real-time PCR. In addition, NAIMA amplification is faster since 20 min are sufficient to achieve full amplification. PMID:18710880

  2. A comparison of directed search target detection versus in-scene target detection in Worldview-2 datasets

    NASA Astrophysics Data System (ADS)

    Grossman, S.

    2015-05-01

    Since the events of September 11, 2001, the intelligence focus has moved from large order-of-battle targets to small targets of opportunity. Additionally, the business community has discovered the use of remotely sensed data to anticipate demand and derive data on their competition. This requires the finer spectral and spatial fidelity now available to recognize those targets. This work hypothesizes that directed searches using calibrated data perform at least as well as inscene manually intensive target detection searches. It uses calibrated Worldview-2 multispectral images with NEF generated signatures and standard detection algorithms to compare bespoke directed search capabilities against ENVI™ in-scene search capabilities. Multiple execution runs are performed at increasing thresholds to generate detection rates. These rates are plotted and statistically analyzed. While individual head-to-head comparison results vary, 88% of the directed searches performed at least as well as in-scene searches with 50% clearly outperforming in-scene methods. The results strongly support the premise that directed searches perform at least as well as comparable in-scene searches.

  3. Antenna Allocation in MIMO Radar with Widely Separated Antennas for Multi-Target Detection

    PubMed Central

    Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong

    2014-01-01

    In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes. PMID:25350505

  4. Antenna allocation in MIMO radar with widely separated antennas for multi-target detection.

    PubMed

    Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong

    2014-10-27

    In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes.

  5. Biased normalized cuts for target detection in hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Zhang, Xuewen; Dorado-Munoz, Leidy P.; Messinger, David W.; Cahill, Nathan D.

    2016-05-01

    The Biased Normalized Cuts (BNC) algorithm is a useful technique for detecting targets or objects in RGB imagery. In this paper, we propose modifying BNC for the purpose of target detection in hyperspectral imagery. As opposed to other target detection algorithms that typically encode target information prior to dimensionality reduction, our proposed algorithm encodes target information after dimensionality reduction, enabling a user to detect different targets in interactive mode. To assess the proposed BNC algorithm, we utilize hyperspectral imagery (HSI) from the SHARE 2012 data campaign, and we explore the relationship between the number and the position of expert-provided target labels and the precision/recall of the remaining targets in the scene.

  6. Target detection, shape discrimination, and signal characteristics of an echolocating false killer whale (Pseudorca crassidens).

    PubMed

    Brill, R L; Pawloski, J L; Helweg, D A; Au, W W; Moore, P W

    1992-09-01

    This study demonstrated the ability of a false killer whale (Pseudorca crassidens) to discriminate between two targets and investigated the parameters of the whale's emitted signals for changes related to test conditions. Target detection performance comparable to the bottlenose dolphin's (Tursiops truncatus) has previously been reported for echolocating false killer whales. No other echolocation capabilities have been reported. A false killer whale, naive to conditioned echolocation tasks, was initially trained to detect a cylinder in a "go/no-go" procedure over ranges of 3 to 8 m. The transition from a detection task to a discrimination task was readily achieved by introducing a spherical comparison target. Finally, the cylinder was successfully compared to spheres of two different sizes and target strengths. Multivariate analyses were used to evaluate the parameters of emitted signals. Duncan's multiple range tests showed significant decreases (df = 185, p less than 0.05) in both source level and bandwidth in the transition from detection to discrimination. Analysis of variance revealed a significant decrease in the number of clicks over test conditions [F(5.26) = 5.23, p less than 0.0001]. These data suggest that the whale relied on cues relevant to target shape as well as target strength, that changes in source level and bandwidth were task-related, that the decrease in clicks was associated with learning experience, and that Pseudorca's ability to discriminate shapes using echolocation may be comparable to that of Tursiops truncatus.

  7. Spectral Target Detection using Schroedinger Eigenmaps

    NASA Astrophysics Data System (ADS)

    Dorado-Munoz, Leidy P.

    Applications of optical remote sensing processes include environmental monitoring, military monitoring, meteorology, mapping, surveillance, etc. Many of these tasks include the detection of specific objects or materials, usually few or small, which are surrounded by other materials that clutter the scene and hide the relevant information. This target detection process has been boosted lately by the use of hyperspectral imagery (HSI) since its high spectral dimension provides more detailed spectral information that is desirable in data exploitation. Typical spectral target detectors rely on statistical or geometric models to characterize the spectral variability of the data. However, in many cases these parametric models do not fit well HSI data that impacts the detection performance. On the other hand, non-linear transformation methods, mainly based on manifold learning algorithms, have shown a potential use in HSI transformation, dimensionality reduction and classification. In target detection, non-linear transformation algorithms are used as preprocessing techniques that transform the data to a more suitable lower dimensional space, where the statistical or geometric detectors are applied. One of these non-linear manifold methods is the Schroedinger Eigenmaps (SE) algorithm that has been introduced as a technique for semi-supervised classification. The core tool of the SE algorithm is the Schroedinger operator that includes a potential term that encodes prior information about the materials present in a scene, and enables the embedding to be steered in some convenient directions in order to cluster similar pixels together. A completely novel target detection methodology based on SE algorithm is proposed for the first time in this thesis. The proposed methodology does not just include the transformation of the data to a lower dimensional space but also includes the definition of a detector that capitalizes on the theory behind SE. The fact that target pixels and

  8. A Pedestrian Detection Scheme Using a Coherent Phase Difference Method Based on 2D Range-Doppler FMCW Radar

    PubMed Central

    Hyun, Eugin; Jin, Young-Seok; Lee, Jong-Hun

    2016-01-01

    For an automotive pedestrian detection radar system, fast-ramp based 2D range-Doppler Frequency Modulated Continuous Wave (FMCW) radar is effective for distinguishing between moving targets and unwanted clutter. However, when a weak moving target such as a pedestrian exists together with strong clutter, the pedestrian may be masked by the side-lobe of the clutter even though they are notably separated in the Doppler dimension. To prevent this problem, one popular solution is the use of a windowing scheme with a weighting function. However, this method leads to a spread spectrum, so the pedestrian with weak signal power and slow Doppler may also be masked by the main-lobe of clutter. With a fast-ramp based FMCW radar, if the target is moving, the complex spectrum of the range- Fast Fourier Transform (FFT) is changed with a constant phase difference over ramps. In contrast, the clutter exhibits constant phase irrespective of the ramps. Based on this fact, in this paper we propose a pedestrian detection for highly cluttered environments using a coherent phase difference method. By detecting the coherent phase difference from the complex spectrum of the range-FFT, we first extract the range profile of the moving pedestrians. Then, through the Doppler FFT, we obtain the 2D range-Doppler map for only the pedestrian. To test the proposed detection scheme, we have developed a real-time data logging system with a 24 GHz FMCW transceiver. In laboratory tests, we verified that the signal processing results from the proposed method were much better than those expected from the conventional 2D FFT-based detection method. PMID:26805835

  9. A Pedestrian Detection Scheme Using a Coherent Phase Difference Method Based on 2D Range-Doppler FMCW Radar.

    PubMed

    Hyun, Eugin; Jin, Young-Seok; Lee, Jong-Hun

    2016-01-20

    For an automotive pedestrian detection radar system, fast-ramp based 2D range-Doppler Frequency Modulated Continuous Wave (FMCW) radar is effective for distinguishing between moving targets and unwanted clutter. However, when a weak moving target such as a pedestrian exists together with strong clutter, the pedestrian may be masked by the side-lobe of the clutter even though they are notably separated in the Doppler dimension. To prevent this problem, one popular solution is the use of a windowing scheme with a weighting function. However, this method leads to a spread spectrum, so the pedestrian with weak signal power and slow Doppler may also be masked by the main-lobe of clutter. With a fast-ramp based FMCW radar, if the target is moving, the complex spectrum of the range- Fast Fourier Transform (FFT) is changed with a constant phase difference over ramps. In contrast, the clutter exhibits constant phase irrespective of the ramps. Based on this fact, in this paper we propose a pedestrian detection for highly cluttered environments using a coherent phase difference method. By detecting the coherent phase difference from the complex spectrum of the range-FFT, we first extract the range profile of the moving pedestrians. Then, through the Doppler FFT, we obtain the 2D range-Doppler map for only the pedestrian. To test the proposed detection scheme, we have developed a real-time data logging system with a 24 GHz FMCW transceiver. In laboratory tests, we verified that the signal processing results from the proposed method were much better than those expected from the conventional 2D FFT-based detection method.

  10. Texture metric that predicts target detection performance

    NASA Astrophysics Data System (ADS)

    Culpepper, Joanne B.

    2015-12-01

    Two texture metrics based on gray level co-occurrence error (GLCE) are used to predict probability of detection and mean search time. The two texture metrics are local clutter metrics and are based on the statistics of GLCE probability distributions. The degree of correlation between various clutter metrics and the target detection performance of the nine military vehicles in complex natural scenes found in the Search_2 dataset are presented. Comparison is also made between four other common clutter metrics found in the literature: root sum of squares, Doyle, statistical variance, and target structure similarity. The experimental results show that the GLCE energy metric is a better predictor of target detection performance when searching for targets in natural scenes than the other clutter metrics studied.

  11. Marine Targets Detection in Pol-SAR Data

    NASA Astrophysics Data System (ADS)

    Chen, Peng; Yang, Jingsong

    2016-08-01

    In this poster, we present a new method of marine target detection in Pol-SAR data. One band SAR image, like HH, VV or VH, can be used to find marine target using a Contant False Alarm Ratio (CFAR) algorithm. But some false detection may happen, as the sidelobe of antenna, Azimuth ambiguity, strong speckle noise and so on in the single band SAR image. Pol-SAR image can get more information of targets. After decomposition and false color composite, the sidelobe of antenna and Azimuth ambiguity could be deleted. So, the method presented include three steps, decomposion, false color composite and supervised classification. The result of Radarsat-2 SAR image test indicates a good accuracy. The detection results are compared with Automatic Indentify Sistem (AIS) data, the accuracy of right detection is above 95% and false detection ratio is below 5%.

  12. Hyperspectral target detection using heavy-tailed distributions

    NASA Astrophysics Data System (ADS)

    Willis, Chris J.

    2009-09-01

    One promising approach to target detection in hyperspectral imagery exploits a statistical mixture model to represent scene content at a pixel level. The process then goes on to look for pixels which are rare, when judged against the model, and marks them as anomalies. It is assumed that military targets will themselves be rare and therefore likely to be detected amongst these anomalies. For the typical assumption of multivariate Gaussianity for the mixture components, the presence of the anomalous pixels within the training data will have a deleterious effect on the quality of the model. In particular, the derivation process itself is adversely affected by the attempt to accommodate the anomalies within the mixture components. This will bias the statistics of at least some of the components away from their true values and towards the anomalies. In many cases this will result in a reduction in the detection performance and an increased false alarm rate. This paper considers the use of heavy-tailed statistical distributions within the mixture model. Such distributions are better able to account for anomalies in the training data within the tails of their distributions, and the balance of the pixels within their central masses. This means that an improved model of the majority of the pixels in the scene may be produced, ultimately leading to a better anomaly detection result. The anomaly detection techniques are examined using both synthetic data and hyperspectral imagery with injected anomalous pixels. A range of results is presented for the baseline Gaussian mixture model and for models accommodating heavy-tailed distributions, for different parameterizations of the algorithms. These include scene understanding results, anomalous pixel maps at given significance levels and Receiver Operating Characteristic curves.

  13. Comparison of human observer and algorithmic target detection in nonurban forward-looking infrared imagery

    NASA Astrophysics Data System (ADS)

    Weber, Bruce A.

    2005-07-01

    We have performed an experiment that compares the performance of human observers with that of a robust algorithm for the detection of targets in difficult, nonurban forward-looking infrared imagery. Our purpose was to benchmark the comparison and document performance differences for future algorithm improvement. The scale-insensitive detection algorithm, used as a benchmark by the Night Vision Electronic Sensors Directorate for algorithm evaluation, employed a combination of contrastlike features to locate targets. Detection receiver operating characteristic curves and observer-confidence analyses were used to compare human and algorithmic responses and to gain insight into differences. The test database contained ground targets, in natural clutter, whose detectability, as judged by human observers, ranged from easy to very difficult. In general, as compared with human observers, the algorithm detected most of the same targets, but correlated confidence with correct detections poorly and produced many more false alarms at any useful level of performance. Though characterizing human performance was not the intent of this study, results suggest that previous observational experience was not a strong predictor of human performance, and that combining individual human observations by majority vote significantly reduced false-alarm rates.

  14. A fast automatic target detection method for detecting ships in infrared scenes

    NASA Astrophysics Data System (ADS)

    Özertem, Kemal Arda

    2016-05-01

    Automatic target detection in infrared scenes is a vital task for many application areas like defense, security and border surveillance. For anti-ship missiles, having a fast and robust ship detection algorithm is crucial for overall system performance. In this paper, a straight-forward yet effective ship detection method for infrared scenes is introduced. First, morphological grayscale reconstruction is applied to the input image, followed by an automatic thresholding onto the suppressed image. For the segmentation step, connected component analysis is employed to obtain target candidate regions. At this point, it can be realized that the detection is defenseless to outliers like small objects with relatively high intensity values or the clouds. To deal with this drawback, a post-processing stage is introduced. For the post-processing stage, two different methods are used. First, noisy detection results are rejected with respect to target size. Second, the waterline is detected by using Hough transform and the detection results that are located above the waterline with a small margin are rejected. After post-processing stage, there are still undesired holes remaining, which cause to detect one object as multi objects or not to detect an object as a whole. To improve the detection performance, another automatic thresholding is implemented only to target candidate regions. Finally, two detection results are fused and post-processing stage is repeated to obtain final detection result. The performance of overall methodology is tested with real world infrared test data.

  15. Small target pre-detection with an attention mechanism

    NASA Astrophysics Data System (ADS)

    Wang, Yuehuan; Zhang, Tianxu; Wang, Guoyou

    2002-04-01

    We introduce the concept of predetection based on an attention mechanism to improve the efficiency of small-target detection by limiting the image region of detection. According to the characteristics of small-target detection, local contrast is taken as the only feature in predetection and a nonlinear sampling model is adopted to make the predetection adaptive to detect small targets with different area sizes. To simplify the predetection itself and decrease the false alarm probability, neighboring nodes in the sampling grid are used to generate a saliency map, and a short-term memory is adopted to accelerate the `pop-out' of targets. We discuss the fact that the proposed approach is simple enough in computational complexity. In addition, even in a cluttered background, attention can be led to targets in a satisfying few iterations, which ensures that the detection efficiency will not be decreased due to false alarms. Experimental results are presented to demonstrate the applicability of the approach.

  16. Detection and identification of human targets in radar data

    NASA Astrophysics Data System (ADS)

    Gürbüz, Sevgi Z.; Melvin, William L.; Williams, Douglas B.

    2007-04-01

    Radar offers unique advantages over other sensors, such as visual or seismic sensors, for human target detection. Many situations, especially military applications, prevent the placement of video cameras or implantment seismic sensors in the area being observed, because of security or other threats. However, radar can operate far away from potential targets, and functions during daytime as well as nighttime, in virtually all weather conditions. In this paper, we examine the problem of human target detection and identification using single-channel, airborne, synthetic aperture radar (SAR). Human targets are differentiated from other detected slow-moving targets by analyzing the spectrogram of each potential target. Human spectrograms are unique, and can be used not just to identify targets as human, but also to determine features about the human target being observed, such as size, gender, action, and speed. A 12-point human model, together with kinematic equations of motion for each body part, is used to calculate the expected target return and spectrogram. A MATLAB simulation environment is developed including ground clutter, human and non-human targets for the testing of spectrogram-based detection and identification algorithms. Simulations show that spectrograms have some ability to detect and identify human targets in low noise. An example gender discrimination system correctly detected 83.97% of males and 91.11% of females. The problems and limitations of spectrogram-based methods in high clutter environments are discussed. The SNR loss inherent to spectrogram-based methods is quantified. An alternate detection and identification method that will be used as a basis for future work is proposed.

  17. Insect Detection of Small Targets Moving in Visual Clutter

    PubMed Central

    Barnett, Paul D; O'Carroll, David C

    2006-01-01

    Detection of targets that move within visual clutter is a common task for animals searching for prey or conspecifics, a task made even more difficult when a moving pursuer needs to analyze targets against the motion of background texture (clutter). Despite the limited optical acuity of the compound eye of insects, this challenging task seems to have been solved by their tiny visual system. Here we describe neurons found in the male hoverfly,Eristalis tenax, that respond selectively to small moving targets. Although many of these target neurons are inhibited by the motion of a background pattern, others respond to target motion within the receptive field under a surprisingly large range of background motion stimuli. Some neurons respond whether or not there is a speed differential between target and background. Analysis of responses to very small targets (smaller than the size of the visual field of single photoreceptors) or those targets with reduced contrast shows that these neurons have extraordinarily high contrast sensitivity. Our data suggest that rejection of background motion may result from extreme selectivity for small targets contrasting against local patches of the background, combined with this high sensitivity, such that background patterns rarely contain features that satisfactorily drive the neuron. PMID:16448249

  18. Entanglement-enhanced Neyman-Pearson target detection using quantum illumination

    NASA Astrophysics Data System (ADS)

    Zhuang, Quntao; Zhang, Zheshen; Shapiro, Jeffrey H.

    2017-08-01

    Quantum illumination (QI) provides entanglement-based target detection---in an entanglement-breaking environment---whose performance is significantly better than that of optimum classical-illumination target detection. QI's performance advantage was established in a Bayesian setting with the target presumed equally likely to be absent or present and error probability employed as the performance metric. Radar theory, however, eschews that Bayesian approach, preferring the Neyman-Pearson performance criterion to avoid the difficulties of accurately assigning prior probabilities to target absence and presence and appropriate costs to false-alarm and miss errors. We have recently reported an architecture---based on sum-frequency generation (SFG) and feedforward (FF) processing---for minimum error-probability QI target detection with arbitrary prior probabilities for target absence and presence. In this paper, we use our results for FF-SFG reception to determine the receiver operating characteristic---detection probability versus false-alarm probability---for optimum QI target detection under the Neyman-Pearson criterion.

  19. Multispectral infrared target detection: phenomenology and modeling

    NASA Astrophysics Data System (ADS)

    Cederquist, Jack N.; Rogne, Timothy J.; Schwartz, Craig R.

    1993-10-01

    Many targets of interest provide only very small signature differences from the clutter background. The ability to detect these small difference targets should be improved by using data which is diverse in space, time, wavelength or some other observable. Target materials often differ from background materials in the variation of their reflectance or emittance with wavelength. A multispectral sensor is therefore considered as a means to improve detection of small signal targets. If this sensor operates in the thermal infrared, it will not need solar illumination and will be useful at night as well as during the day. An understanding of the phenomenology of the spectral properties of materials and an ability to model and simulate target and clutter signatures is needed to understand potential target detection performance from multispectral infrared sensor data. Spectral variations in material emittance are due to vibrational energy transitions in molecular bonds. The spectral emittances of many materials of interest have been measured. Examples are vegetation, soil, construction and road materials, and paints. A multispectral infrared signature model has been developed which includes target and background temperature and emissivity, sky, sun, cloud and background irradiance, multiple reflection effects, path radiance, and atmospheric attenuation. This model can be used to predict multispectral infrared signatures for small signal targets.

  20. A novel spatial-temporal detection method of dim infrared moving small target

    NASA Astrophysics Data System (ADS)

    Chen, Zhong; Deng, Tao; Gao, Lei; Zhou, Heng; Luo, Song

    2014-09-01

    Moving small target detection under complex background in infrared image sequence is one of the major challenges of modern military in Early Warning Systems (EWS) and the use of Long-Range Strike (LRS). However, because of the low SNR and undulating background, the infrared moving small target detection is a difficult problem in a long time. To solve this problem, a novel spatial-temporal detection method based on bi-dimensional empirical mode decomposition (EMD) and time-domain difference is proposed in this paper. This method is downright self-data decomposition and do not rely on any transition kernel function, so it has a strong adaptive capacity. Firstly, we generalized the 1D EMD algorithm to the 2D case. In this process, the project has solved serial issues in 2D EMD, such as large amount of data operations, define and identify extrema in 2D case, and two-dimensional signal boundary corrosion. The EMD algorithm studied in this project can be well adapted to the automatic detection of small targets under low SNR and complex background. Secondly, considering the characteristics of moving target, we proposed an improved filtering method based on three-frame difference on basis of the original difference filtering in time-domain, which greatly improves the ability of anti-jamming algorithm. Finally, we proposed a new time-space fusion method based on a combined processing of 2D EMD and improved time-domain differential filtering. And, experimental results show that this method works well in infrared small moving target detection under low SNR and complex background.

  1. Fluorescence turn-on detection of target sequence DNA based on silicon nanodot-mediated quenching.

    PubMed

    Zhang, Yanan; Ning, Xinping; Mao, Guobin; Ji, Xinghu; He, Zhike

    2018-05-01

    We have developed a new enzyme-free method for target sequence DNA detection based on the dynamic quenching of fluorescent silicon nanodots (SiNDs) toward Cy5-tagged DNA probe. Fascinatingly, the water-soluble SiNDs can quench the fluorescence of cyanine (Cy5) in Cy5-tagged DNA probe in homogeneous solution, and the fluorescence of Cy5-tagged DNA probe can be restored in the presence of target sequence DNA (the synthetic target miRNA-27a). Based on this phenomenon, a SiND-featured fluorescent sensor has been constructed for "turn-on" detection of the synthetic target miRNA-27a for the first time. This newly developed approach possesses the merits of low cost, simple design, and convenient operation since no enzymatic reaction, toxic reagents, or separation procedures are involved. The established method achieves a detection limit of 0.16 nM, and the relative standard deviation of this method is 9% (1 nM, n = 5). The linear range is 0.5-20 nM, and the recoveries in spiked human fluids are in the range of 90-122%. This protocol provides a new tactic in the development of the nonenzymic miRNA biosensors and opens a promising avenue for early diagnosis of miRNA-associated disease. Graphical abstract The SiND-based fluorescent sensor for detection of S-miR-27a.

  2. Experimental determination of particle range and dose distribution in thick targets through fragmentation reactions of stable heavy ions.

    PubMed

    Inaniwa, Taku; Kohno, Toshiyuki; Tomitani, Takehiro; Urakabe, Eriko; Sato, Shinji; Kanazawa, Mitsutaka; Kanai, Tatsuaki

    2006-09-07

    In radiation therapy with highly energetic heavy ions, the conformal irradiation of a tumour can be achieved by using their advantageous features such as the good dose localization and the high relative biological effectiveness around their mean range. For effective utilization of such properties, it is necessary to evaluate the range of incident ions and the deposited dose distribution in a patient's body. Several methods have been proposed to derive such physical quantities; one of them uses positron emitters generated through projectile fragmentation reactions of incident ions with target nuclei. We have proposed the application of the maximum likelihood estimation (MLE) method to a detected annihilation gamma-ray distribution for determination of the range of incident ions in a target and we have demonstrated the effectiveness of the method with computer simulations. In this paper, a water, a polyethylene and a polymethyl methacrylate target were each irradiated with stable (12)C, (14)N, (16)O and (20)Ne beams. Except for a few combinations of incident beams and targets, the MLE method could determine the range of incident ions R(MLE) with a difference between R(MLE) and the experimental range of less than 2.0 mm under the circumstance that the measurement of annihilation gamma rays was started just after the irradiation of 61.4 s and lasted for 500 s. In the process of evaluating the range of incident ions with the MLE method, we must calculate many physical quantities such as the fluence and the energy of both primary ions and fragments as a function of depth in a target. Consequently, by using them we can obtain the dose distribution. Thus, when the mean range of incident ions is determined with the MLE method, the annihilation gamma-ray distribution and the deposited dose distribution can be derived simultaneously. The derived dose distributions in water for the mono-energetic heavy-ion beams of four species were compared with those measured with an

  3. Manifold structure preservative for hyperspectral target detection

    NASA Astrophysics Data System (ADS)

    Imani, Maryam

    2018-05-01

    A nonparametric method termed as manifold structure preservative (MSP) is proposed in this paper for hyperspectral target detection. MSP transforms the feature space of data to maximize the separation between target and background signals. Moreover, it minimizes the reconstruction error of targets and preserves the topological structure of data in the projected feature space. MSP does not need to consider any distribution for target and background data. So, it can achieve accurate results in real scenarios due to avoiding unreliable assumptions. The proposed MSP detector is compared to several popular detectors and the experiments on a synthetic data and two real hyperspectral images indicate the superior ability of it in target detection.

  4. Determination of target detection limits in hyperspectral data using band selection and dimensionality reduction

    NASA Astrophysics Data System (ADS)

    Gross, W.; Boehler, J.; Twizer, K.; Kedem, B.; Lenz, A.; Kneubuehler, M.; Wellig, P.; Oechslin, R.; Schilling, H.; Rotman, S.; Middelmann, W.

    2016-10-01

    Hyperspectral remote sensing data can be used for civil and military applications to robustly detect and classify target objects. High spectral resolution of hyperspectral data can compensate for the comparatively low spatial resolution, which allows for detection and classification of small targets, even below image resolution. Hyperspectral data sets are prone to considerable spectral redundancy, affecting and limiting data processing and algorithm performance. As a consequence, data reduction strategies become increasingly important, especially in view of near-real-time data analysis. The goal of this paper is to analyze different strategies for hyperspectral band selection algorithms and their effect on subpixel classification for different target and background materials. Airborne hyperspectral data is used in combination with linear target simulation procedures to create a representative amount of target-to-background ratios for evaluation of detection limits. Data from two different airborne hyperspectral sensors, AISA Eagle and Hawk, are used to evaluate transferability of band selection when using different sensors. The same target objects were recorded to compare the calculated detection limits. To determine subpixel classification results, pure pixels from the target materials are extracted and used to simulate mixed pixels with selected background materials. Target signatures are linearly combined with different background materials in varying ratios. The commonly used classification algorithms Adaptive Coherence Estimator (ACE) is used to compare the detection limit for the original data with several band selection and data reduction strategies. The evaluation of the classification results is done by assuming a fixed false alarm ratio and calculating the mean target-to-background ratio of correctly detected pixels. The results allow drawing conclusions about specific band combinations for certain target and background combinations. Additionally

  5. Does working memory load facilitate target detection?

    PubMed

    Fruchtman-Steinbok, Tom; Kessler, Yoav

    2016-02-01

    Previous studies demonstrated that increasing working memory (WM) load delays performance of a concurrent task, by distracting attention and thus interfering with encoding and maintenance processes. The present study used a version of the change detection task with a target detection requirement during the retention interval. In contrast to the above prediction, target detection was faster following a larger set-size, specifically when presented shortly after the memory array (up to 400 ms). The effect of set-size on target detection was also evident when no memory retention was required. The set-size effect was also found using different modalities. Moreover, it was only observed when the memory array was presented simultaneously, but not sequentially. These results were explained by increased phasic alertness exerted by the larger visual display. The present study offers new evidence of ongoing attentional processes in the commonly-used change detection paradigm. Copyright © 2015 Elsevier B.V. All rights reserved.

  6. Detection of Moving Targets Using Soliton Resonance Effect

    NASA Technical Reports Server (NTRS)

    Kulikov, Igor K.; Zak, Michail

    2013-01-01

    The objective of this research was to develop a fundamentally new method for detecting hidden moving targets within noisy and cluttered data-streams using a novel "soliton resonance" effect in nonlinear dynamical systems. The technique uses an inhomogeneous Korteweg de Vries (KdV) equation containing moving-target information. Solution of the KdV equation will describe a soliton propagating with the same kinematic characteristics as the target. The approach uses the time-dependent data stream obtained with a sensor in form of the "forcing function," which is incorporated in an inhomogeneous KdV equation. When a hidden moving target (which in many ways resembles a soliton) encounters the natural "probe" soliton solution of the KdV equation, a strong resonance phenomenon results that makes the location and motion of the target apparent. Soliton resonance method will amplify the moving target signal, suppressing the noise. The method will be a very effective tool for locating and identifying diverse, highly dynamic targets with ill-defined characteristics in a noisy environment. The soliton resonance method for the detection of moving targets was developed in one and two dimensions. Computer simulations proved that the method could be used for detection of singe point-like targets moving with constant velocities and accelerations in 1D and along straight lines or curved trajectories in 2D. The method also allows estimation of the kinematic characteristics of moving targets, and reconstruction of target trajectories in 2D. The method could be very effective for target detection in the presence of clutter and for the case of target obscurations.

  7. Dim target detection method based on salient graph fusion

    NASA Astrophysics Data System (ADS)

    Hu, Ruo-lan; Shen, Yi-yan; Jiang, Jun

    2018-02-01

    Dim target detection is one key problem in digital image processing field. With development of multi-spectrum imaging sensor, it becomes a trend to improve the performance of dim target detection by fusing the information from different spectral images. In this paper, one dim target detection method based on salient graph fusion was proposed. In the method, Gabor filter with multi-direction and contrast filter with multi-scale were combined to construct salient graph from digital image. And then, the maximum salience fusion strategy was designed to fuse the salient graph from different spectral images. Top-hat filter was used to detect dim target from the fusion salient graph. Experimental results show that proposal method improved the probability of target detection and reduced the probability of false alarm on clutter background images.

  8. Object Tracking and Target Reacquisition Based on 3-D Range Data for Moving Vehicles

    PubMed Central

    Lee, Jehoon; Lankton, Shawn; Tannenbaum, Allen

    2013-01-01

    In this paper, we propose an approach for tracking an object of interest based on 3-D range data. We employ particle filtering and active contours to simultaneously estimate the global motion of the object and its local deformations. The proposed algorithm takes advantage of range information to deal with the challenging (but common) situation in which the tracked object disappears from the image domain entirely and reappears later. To cope with this problem, a method based on principle component analysis (PCA) of shape information is proposed. In the proposed method, if the target disappears out of frame, shape similarity energy is used to detect target candidates that match a template shape learned online from previously observed frames. Thus, we require no a priori knowledge of the target’s shape. Experimental results show the practical applicability and robustness of the proposed algorithm in realistic tracking scenarios. PMID:21486717

  9. Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method

    PubMed Central

    Zhang, Yang; Chen, Fuming; Xue, Huijun; Li, Zhao; An, Qiang; Wang, Jianqi; Zhang, Yang

    2016-01-01

    Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets. PMID:27801795

  10. Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method.

    PubMed

    Zhang, Yang; Chen, Fuming; Xue, Huijun; Li, Zhao; An, Qiang; Wang, Jianqi; Zhang, Yang

    2016-10-27

    Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets.

  11. Spatial Probability Dynamically Modulates Visual Target Detection in Chickens

    PubMed Central

    Sridharan, Devarajan; Ramamurthy, Deepa L.; Knudsen, Eric I.

    2013-01-01

    The natural world contains a rich and ever-changing landscape of sensory information. To survive, an organism must be able to flexibly and rapidly locate the most relevant sources of information at any time. Humans and non-human primates exploit regularities in the spatial distribution of relevant stimuli (targets) to improve detection at locations of high target probability. Is the ability to flexibly modify behavior based on visual experience unique to primates? Chickens (Gallus domesticus) were trained on a multiple alternative Go/NoGo task to detect a small, briefly-flashed dot (target) in each of the quadrants of the visual field. When targets were presented with equal probability (25%) in each quadrant, chickens exhibited a distinct advantage for detecting targets at lower, relative to upper, hemifield locations. Increasing the probability of presentation in the upper hemifield locations (to 80%) dramatically improved detection performance at these locations to be on par with lower hemifield performance. Finally, detection performance in the upper hemifield changed on a rapid timescale, improving with successive target detections, and declining with successive detections at the diagonally opposite location in the lower hemifield. These data indicate the action of a process that in chickens, as in primates, flexibly and dynamically modulates detection performance based on the spatial probabilities of sensory stimuli as well as on recent performance history. PMID:23734188

  12. Heterogeneous CPU-GPU moving targets detection for UAV video

    NASA Astrophysics Data System (ADS)

    Li, Maowen; Tang, Linbo; Han, Yuqi; Yu, Chunlei; Zhang, Chao; Fu, Huiquan

    2017-07-01

    Moving targets detection is gaining popularity in civilian and military applications. On some monitoring platform of motion detection, some low-resolution stationary cameras are replaced by moving HD camera based on UAVs. The pixels of moving targets in the HD Video taken by UAV are always in a minority, and the background of the frame is usually moving because of the motion of UAVs. The high computational cost of the algorithm prevents running it at higher resolutions the pixels of frame. Hence, to solve the problem of moving targets detection based UAVs video, we propose a heterogeneous CPU-GPU moving target detection algorithm for UAV video. More specifically, we use background registration to eliminate the impact of the moving background and frame difference to detect small moving targets. In order to achieve the effect of real-time processing, we design the solution of heterogeneous CPU-GPU framework for our method. The experimental results show that our method can detect the main moving targets from the HD video taken by UAV, and the average process time is 52.16ms per frame which is fast enough to solve the problem.

  13. Camouflage target detection via hyperspectral imaging plus information divergence measurement

    NASA Astrophysics Data System (ADS)

    Chen, Yuheng; Chen, Xinhua; Zhou, Jiankang; Ji, Yiqun; Shen, Weimin

    2016-01-01

    Target detection is one of most important applications in remote sensing. Nowadays accurate camouflage target distinction is often resorted to spectral imaging technique due to its high-resolution spectral/spatial information acquisition ability as well as plenty of data processing methods. In this paper, hyper-spectral imaging technique together with spectral information divergence measure method is used to solve camouflage target detection problem. A self-developed visual-band hyper-spectral imaging device is adopted to collect data cubes of certain experimental scene before spectral information divergences are worked out so as to discriminate target camouflage and anomaly. Full-band information divergences are measured to evaluate target detection effect visually and quantitatively. Information divergence measurement is proved to be a low-cost and effective tool for target detection task and can be further developed to other target detection applications beyond spectral imaging technique.

  14. Infrared maritime target detection using the high order statistic filtering in fractional Fourier domain

    NASA Astrophysics Data System (ADS)

    Zhou, Anran; Xie, Weixin; Pei, Jihong

    2018-06-01

    Accurate detection of maritime targets in infrared imagery under various sea clutter conditions is always a challenging task. The fractional Fourier transform (FRFT) is the extension of the Fourier transform in the fractional order, and has richer spatial-frequency information. By combining it with the high order statistic filtering, a new ship detection method is proposed. First, the proper range of angle parameter is determined to make it easier for the ship components and background to be separated. Second, a new high order statistic curve (HOSC) at each fractional frequency point is designed. It is proved that maximal peak interval in HOSC reflects the target information, while the points outside the interval reflect the background. And the value of HOSC relative to the ship is much bigger than that to the sea clutter. Then, search the curve's maximal target peak interval and extract the interval by bandpass filtering in fractional Fourier domain. The value outside the peak interval of HOSC decreases rapidly to 0, so the background is effectively suppressed. Finally, the detection result is obtained by the double threshold segmenting and the target region selection method. The results show the proposed method is excellent for maritime targets detection with high clutters.

  15. Hyperspectral target detection using manifold learning and multiple target spectra

    DOE PAGES

    Ziemann, Amanda K.; Theiler, James; Messinger, David W.

    2016-03-31

    Imagery collected from satellites and airborne platforms provides an important tool for remotely analyzing the content of a scene. In particular, the ability to remotely detect a specific material within a scene is of critical importance in nonproliferation and other applications. The sensor systems that process hyperspectral images collect the high-dimensional spectral information necessary to perform these detection analyses. For a d-dimensional hyperspectral image, however, where d is the number of spectral bands, it is common for the data to inherently occupy an m-dimensional space with m << d. In the remote sensing community, this has led to recent interestmore » in the use of manifold learning, which seeks to characterize the embedded lower-dimensional, nonlinear manifold that the data discretely approximate. The research presented in this paper focuses on a graph theory and manifold learning approach to target detection, using an adaptive version of locally linear embedding that is biased to separate target pixels from background pixels. Finally, this approach incorporates multiple target signatures for a particular material, accounting for the spectral variability that is often present within a solid material of interest.« less

  16. Bidirectional reflectance distribution function based surface modeling of non-Lambertian using intensity data of light detection and ranging.

    PubMed

    Li, Xiaolu; Liang, Yu; Xu, Lijun

    2014-09-01

    To provide a credible model for light detection and ranging (LiDAR) target classification, the focus of this study is on the relationship between intensity data of LiDAR and the bidirectional reflectance distribution function (BRDF). An integration method based on the built-in-lab coaxial laser detection system was advanced. A kind of intermediary BRDF model advanced by Schlick was introduced into the integration method, considering diffuse and specular backscattering characteristics of the surface. A group of measurement campaigns were carried out to investigate the influence of the incident angle and detection range on the measured intensity data. Two extracted parameters r and S(λ) are influenced by different surface features, which illustrate the surface features of the distribution and magnitude of reflected energy, respectively. The combination of two parameters can be used to describe the surface characteristics for target classification in a more plausible way.

  17. Species-specific markers for the differential diagnosis of Trypanosoma cruzi and Trypanosoma rangeli and polymorphisms detection in Trypanosoma rangeli.

    PubMed

    Ferreira, Keila Adriana Magalhães; Fajardo, Emanuella Francisco; Baptista, Rodrigo P; Macedo, Andrea Mara; Lages-Silva, Eliane; Ramírez, Luis Eduardo; Pedrosa, André Luiz

    2014-06-01

    Trypanosoma cruzi and Trypanosoma rangeli are kinetoplastid parasites which are able to infect humans in Central and South America. Misdiagnosis between these trypanosomes can be avoided by targeting barcoding sequences or genes of each organism. This work aims to analyze the feasibility of using species-specific markers for identification of intraspecific polymorphisms and as target for diagnostic methods by PCR. Accordingly, primers which are able to specifically detect T. cruzi or T. rangeli genomic DNA were characterized. The use of intergenic regions, generally divergent in the trypanosomatids, and the serine carboxypeptidase gene were successful. Using T. rangeli genomic sequences for the identification of group-specific polymorphisms and a polymorphic AT(n) dinucleotide repeat permitted the classification of the strains into two groups, which are entirely coincident with T. rangeli main lineages, KP1 (+) and KP1 (-), previously determined by kinetoplast DNA (kDNA) characterization. The sequences analyzed totalize 622 bp (382 bp represent a hypothetical protein sequence, and 240 bp represent an anonymous sequence), and of these, 581 (93.3%) are conserved sites and 41 bp (6.7%) are polymorphic, with 9 transitions (21.9%), 2 transversions (4.9%), and 30 (73.2%) insertion/deletion events. Taken together, the species-specific markers analyzed may be useful for the development of new strategies for the accurate diagnosis of infections. Furthermore, the identification of T. rangeli polymorphisms has a direct impact in the understanding of the population structure of this parasite.

  18. Subpixel target detection and enhancement in hyperspectral images

    NASA Astrophysics Data System (ADS)

    Tiwari, K. C.; Arora, M.; Singh, D.

    2011-06-01

    Hyperspectral data due to its higher information content afforded by higher spectral resolution is increasingly being used for various remote sensing applications including information extraction at subpixel level. There is however usually a lack of matching fine spatial resolution data particularly for target detection applications. Thus, there always exists a tradeoff between the spectral and spatial resolutions due to considerations of type of application, its cost and other associated analytical and computational complexities. Typically whenever an object, either manmade, natural or any ground cover class (called target, endmembers, components or class) gets spectrally resolved but not spatially, mixed pixels in the image result. Thus, numerous manmade and/or natural disparate substances may occur inside such mixed pixels giving rise to mixed pixel classification or subpixel target detection problems. Various spectral unmixing models such as Linear Mixture Modeling (LMM) are in vogue to recover components of a mixed pixel. Spectral unmixing outputs both the endmember spectrum and their corresponding abundance fractions inside the pixel. It, however, does not provide spatial distribution of these abundance fractions within a pixel. This limits the applicability of hyperspectral data for subpixel target detection. In this paper, a new inverse Euclidean distance based super-resolution mapping method has been presented that achieves subpixel target detection in hyperspectral images by adjusting spatial distribution of abundance fraction within a pixel. Results obtained at different resolutions indicate that super-resolution mapping may effectively aid subpixel target detection.

  19. Texture orientation-based algorithm for detecting infrared maritime targets.

    PubMed

    Wang, Bin; Dong, Lili; Zhao, Ming; Wu, Houde; Xu, Wenhai

    2015-05-20

    Infrared maritime target detection is a key technology for maritime target searching systems. However, in infrared maritime images (IMIs) taken under complicated sea conditions, background clutters, such as ocean waves, clouds or sea fog, usually have high intensity that can easily overwhelm the brightness of real targets, which is difficult for traditional target detection algorithms to deal with. To mitigate this problem, this paper proposes a novel target detection algorithm based on texture orientation. This algorithm first extracts suspected targets by analyzing the intersubband correlation between horizontal and vertical wavelet subbands of the original IMI on the first scale. Then the self-adaptive wavelet threshold denoising and local singularity analysis of the original IMI is combined to remove false alarms further. Experiments show that compared with traditional algorithms, this algorithm can suppress background clutter much better and realize better single-frame detection for infrared maritime targets. Besides, in order to guarantee accurate target extraction further, the pipeline-filtering algorithm is adopted to eliminate residual false alarms. The high practical value and applicability of this proposed strategy is backed strongly by experimental data acquired under different environmental conditions.

  20. Automatic target detection using binary template matching

    NASA Astrophysics Data System (ADS)

    Jun, Dong-San; Sun, Sun-Gu; Park, HyunWook

    2005-03-01

    This paper presents a new automatic target detection (ATD) algorithm to detect targets such as battle tanks and armored personal carriers in ground-to-ground scenarios. Whereas most ATD algorithms were developed for forward-looking infrared (FLIR) images, we have developed an ATD algorithm for charge-coupled device (CCD) images, which have superior quality to FLIR images in daylight. The proposed algorithm uses fast binary template matching with an adaptive binarization, which is robust to various light conditions in CCD images and saves computation time. Experimental results show that the proposed method has good detection performance.

  1. Target recognition of ladar range images using even-order Zernike moments.

    PubMed

    Liu, Zheng-Jun; Li, Qi; Xia, Zhi-Wei; Wang, Qi

    2012-11-01

    Ladar range images have attracted considerable attention in automatic target recognition fields. In this paper, Zernike moments (ZMs) are applied to classify the target of the range image from an arbitrary azimuth angle. However, ZMs suffer from high computational costs. To improve the performance of target recognition based on small samples, even-order ZMs with serial-parallel backpropagation neural networks (BPNNs) are applied to recognize the target of the range image. It is found that the rotation invariance and classified performance of the even-order ZMs are both better than for odd-order moments and for moments compressed by principal component analysis. The experimental results demonstrate that combining the even-order ZMs with serial-parallel BPNNs can significantly improve the recognition rate for small samples.

  2. Initial study of Schroedinger eigenmaps for spectral target detection

    NASA Astrophysics Data System (ADS)

    Dorado-Munoz, Leidy P.; Messinger, David W.

    2016-08-01

    Spectral target detection refers to the process of searching for a specific material with a known spectrum over a large area containing materials with different spectral signatures. Traditional target detection methods in hyperspectral imagery (HSI) require assuming the data fit some statistical or geometric models and based on the model, to estimate parameters for defining a hypothesis test, where one class (i.e., target class) is chosen over the other classes (i.e., background class). Nonlinear manifold learning methods such as Laplacian eigenmaps (LE) have extensively shown their potential use in HSI processing, specifically in classification or segmentation. Recently, Schroedinger eigenmaps (SE), which is built upon LE, has been introduced as a semisupervised classification method. In SE, the former Laplacian operator is replaced by the Schroedinger operator. The Schroedinger operator includes by definition, a potential term V that steers the transformation in certain directions improving the separability between classes. In this regard, we propose a methodology for target detection that is not based on the traditional schemes and that does not need the estimation of statistical or geometric parameters. This method is based on SE, where the potential term V is taken into consideration to include the prior knowledge about the target class and use it to steer the transformation in directions where the target location in the new space is known and the separability between target and background is augmented. An initial study of how SE can be used in a target detection scheme for HSI is shown here. In-scene pixel and spectral signature detection approaches are presented. The HSI data used comprise various target panels for testing simultaneous detection of multiple objects with different complexities.

  3. Data collection and simulation of high range resolution laser radar for surface mine detection

    NASA Astrophysics Data System (ADS)

    Steinvall, Ove; Chevalier, Tomas; Larsson, Håkan

    2006-05-01

    Rapid and efficient detection of surface mines, IED's (Improvised Explosive Devices) and UXO (Unexploded Ordnance) is of high priority in military conflicts. High range resolution laser radars combined with passive hyper/multispectral sensors offer an interesting concept to help solving this problem. This paper reports on laser radar data collection of various surface mines in different types of terrain. In order to evaluate the capability of 3D imaging for detecting and classifying the objects of interest a scanning laser radar was used to scan mines and surrounding terrain with high angular and range resolution. These data were then fed into a laser radar model capable of generating range waveforms for a variety of system parameters and combinations of different targets and backgrounds. We can thus simulate a potential system by down sampling to relevant pixel sizes and laser/receiver characteristics. Data, simulations and examples will be presented.

  4. A new method of small target detection based on neural network

    NASA Astrophysics Data System (ADS)

    Hu, Jing; Hu, Yongli; Lu, Xinxin

    2018-02-01

    The detection and tracking of moving dim target in infrared image have been an research hotspot for many years. The target in each frame of images only occupies several pixels without any shape and structure information. Moreover, infrared small target is often submerged in complicated background with low signal-to-clutter ratio, making the detection very difficult. Different backgrounds exhibit different statistical properties, making it becomes extremely complex to detect the target. If the threshold segmentation is not reasonable, there may be more noise points in the final detection, which is unfavorable for the detection of the trajectory of the target. Single-frame target detection may not be able to obtain the desired target and cause high false alarm rate. We believe the combination of suspicious target detection spatially in each frame and temporal association for target tracking will increase reliability of tracking dim target. The detection of dim target is mainly divided into two parts, In the first part, we adopt bilateral filtering method in background suppression, after the threshold segmentation, the suspicious target in each frame are extracted, then we use LSTM(long short term memory) neural network to predict coordinates of target of the next frame. It is a brand-new method base on the movement characteristic of the target in sequence images which could respond to the changes in the relationship between past and future values of the values. Simulation results demonstrate proposed algorithm can effectively predict the trajectory of the moving small target and work efficiently and robustly with low false alarm.

  5. Infrared small target detection based on Danger Theory

    NASA Astrophysics Data System (ADS)

    Lan, Jinhui; Yang, Xiao

    2009-11-01

    To solve the problem that traditional method can't detect the small objects whose local SNR is less than 2 in IR images, a Danger Theory-based model to detect infrared small target is presented in this paper. First, on the analog with immunology, the definition is given, in this paper, to such terms as dangerous signal, antigens, APC, antibodies. Besides, matching rule between antigen and antibody is improved. Prior to training the detection model and detecting the targets, the IR images are processed utilizing adaptive smooth filter to decrease the stochastic noise. Then at the training process, deleting rule, generating rule, crossover rule and the mutation rule are established after a large number of experiments in order to realize immediate convergence and obtain good antibodies. The Danger Theory-based model is built after the training process, and this model can detect the target whose local SNR is only 1.5.

  6. Infrared small target detection technology based on OpenCV

    NASA Astrophysics Data System (ADS)

    Liu, Lei; Huang, Zhijian

    2013-05-01

    Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. In this paper, some basic principles and the implementing flow charts of a series of algorithms for target detection are described. These algorithms are traditional two-frame difference method, improved three-frame difference method, background estimate and frame difference fusion method, and building background with neighborhood mean method. On the foundation of above works, an infrared target detection software platform which is developed by OpenCV and MFC is introduced. Three kinds of tracking algorithms are integrated in this software. In order to explain the software clearly, the framework and the function are described in this paper. At last, the experiments are performed for some real-life IR images. The whole algorithm implementing processes and results are analyzed, and those algorithms for detection targets are evaluated from the two aspects of subjective and objective. The results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection.

  7. Infrared small target detection technology based on OpenCV

    NASA Astrophysics Data System (ADS)

    Liu, Lei; Huang, Zhijian

    2013-09-01

    Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. In this paper, some basic principles and the implementing flow charts of a series of algorithms for target detection are described. These algorithms are traditional two-frame difference method, improved three-frame difference method, background estimate and frame difference fusion method, and building background with neighborhood mean method. On the foundation of above works, an infrared target detection software platform which is developed by OpenCV and MFC is introduced. Three kinds of tracking algorithms are integrated in this software. In order to explain the software clearly, the framework and the function are described in this paper. At last, the experiments are performed for some real-life IR images. The whole algorithm implementing processes and results are analyzed, and those algorithms for detection targets are evaluated from the two aspects of subjective and objective. The results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection.

  8. Infrared small target detection with kernel Fukunaga Koontz transform

    NASA Astrophysics Data System (ADS)

    Liu, Rui-ming; Liu, Er-qi; Yang, Jie; Zhang, Tian-hao; Wang, Fang-lin

    2007-09-01

    The Fukunaga-Koontz transform (FKT) has been proposed for many years. It can be used to solve two-pattern classification problems successfully. However, there are few researchers who have definitely extended FKT to kernel FKT (KFKT). In this paper, we first complete this task. Then a method based on KFKT is developed to detect infrared small targets. KFKT is a supervised learning algorithm. How to construct training sets is very important. For automatically detecting targets, the synthetic target images and real background images are used to train KFKT. Because KFKT can represent the higher order statistical properties of images, we expect better detection performance of KFKT than that of FKT. The well-devised experiments verify that KFKT outperforms FKT in detecting infrared small targets.

  9. Targeted Analyte Detection by Standard Addition Improves Detection Limits in MALDI Mass Spectrometry

    PubMed Central

    Eshghi, Shadi Toghi; Li, Xingde; Zhang, Hui

    2014-01-01

    Matrix-assisted laser desorption/ionization has proven an effective tool for fast and accurate determination of many molecules. However, the detector sensitivity and chemical noise compromise the detection of many invaluable low-abundance molecules from biological and clinical samples. To challenge this limitation, we developed a targeted analyte detection (TAD) technique. In TAD, the target analyte is selectively elevated by spiking a known amount of that analyte into the sample, thereby raising its concentration above the noise level, where we take advantage of the improved sensitivity to detect the presence of the endogenous analyte in the sample. We assessed TAD on three peptides in simple and complex background solutions with various exogenous analyte concentrations in two MALDI matrices. TAD successfully improved the limit of detection (LOD) of target analytes when the target peptides were added to the sample in a concentration close to optimum concentration. The optimum exogenous concentration was estimated through a quantitative method to be approximately equal to the original LOD for each target. Also, we showed that TAD could achieve LOD improvements on an average of 3-fold in a simple and 2-fold in a complex sample. TAD provides a straightforward assay to improve the LOD of generic target analytes without the need for costly hardware modifications. PMID:22877355

  10. Modeling peripheral vision for moving target search and detection.

    PubMed

    Yang, Ji Hyun; Huston, Jesse; Day, Michael; Balogh, Imre

    2012-06-01

    Most target search and detection models focus on foveal vision. In reality, peripheral vision plays a significant role, especially in detecting moving objects. There were 23 subjects who participated in experiments simulating target detection tasks in urban and rural environments while their gaze parameters were tracked. Button responses associated with foveal object and peripheral object (PO) detection and recognition were recorded. In an urban scenario, pedestrians appearing in the periphery holding guns were threats and pedestrians with empty hands were non-threats. In a rural scenario, non-U.S. unmanned aerial vehicles (UAVs) were considered threats and U.S. UAVs non-threats. On average, subjects missed detecting 2.48 POs among 50 POs in the urban scenario and 5.39 POs in the rural scenario. Both saccade reaction time and button reaction time can be predicted by peripheral angle and entrance speed of POs. Fast moving objects were detected faster than slower objects and POs appearing at wider angles took longer to detect than those closer to the gaze center. A second-order mixed-effect model was applied to provide each subject's prediction model for peripheral target detection performance as a function of eccentricity angle and speed. About half the subjects used active search patterns while the other half used passive search patterns. An interactive 3-D visualization tool was developed to provide a representation of macro-scale head and gaze movement in the search and target detection task. An experimentally validated stochastic model of peripheral vision in realistic target detection scenarios was developed.

  11. Radiance and atmosphere propagation-based method for the target range estimation

    NASA Astrophysics Data System (ADS)

    Cho, Hoonkyung; Chun, Joohwan

    2012-06-01

    Target range estimation is traditionally based on radar and active sonar systems in modern combat system. However, the performance of such active sensor devices is degraded tremendously by jamming signal from the enemy. This paper proposes a simple range estimation method between the target and the sensor. Passive IR sensors measures infrared (IR) light radiance radiating from objects in dierent wavelength and this method shows robustness against electromagnetic jamming. The measured target radiance of each wavelength at the IR sensor depends on the emissive properties of target material and is attenuated by various factors, in particular the distance between the sensor and the target and atmosphere environment. MODTRAN is a tool that models atmospheric propagation of electromagnetic radiation. Based on the result from MODTRAN and measured radiance, the target range is estimated. To statistically analyze the performance of proposed method, we use maximum likelihood estimation (MLE) and evaluate the Cramer-Rao Lower Bound (CRLB) via the probability density function of measured radiance. And we also compare CRLB and the variance of and ML estimation using Monte-Carlo.

  12. Research on the algorithm of infrared target detection based on the frame difference and background subtraction method

    NASA Astrophysics Data System (ADS)

    Liu, Yun; Zhao, Yuejin; Liu, Ming; Dong, Liquan; Hui, Mei; Liu, Xiaohua; Wu, Yijian

    2015-09-01

    As an important branch of infrared imaging technology, infrared target tracking and detection has a very important scientific value and a wide range of applications in both military and civilian areas. For the infrared image which is characterized by low SNR and serious disturbance of background noise, an innovative and effective target detection algorithm is proposed in this paper, according to the correlation of moving target frame-to-frame and the irrelevance of noise in sequential images based on OpenCV. Firstly, since the temporal differencing and background subtraction are very complementary, we use a combined detection method of frame difference and background subtraction which is based on adaptive background updating. Results indicate that it is simple and can extract the foreground moving target from the video sequence stably. For the background updating mechanism continuously updating each pixel, we can detect the infrared moving target more accurately. It paves the way for eventually realizing real-time infrared target detection and tracking, when transplanting the algorithms on OpenCV to the DSP platform. Afterwards, we use the optimal thresholding arithmetic to segment image. It transforms the gray images to black-white images in order to provide a better condition for the image sequences detection. Finally, according to the relevance of moving objects between different frames and mathematical morphology processing, we can eliminate noise, decrease the area, and smooth region boundaries. Experimental results proves that our algorithm precisely achieve the purpose of rapid detection of small infrared target.

  13. Kepler Planet Detection Metrics: Per-Target Detection Contours for Data Release 25

    NASA Technical Reports Server (NTRS)

    Burke, Christopher J.; Catanzarite, Joseph

    2017-01-01

    A necessary input to planet occurrence calculations is an accurate model for the pipeline completeness (Burke et al., 2015). This document describes the use of the Kepler planet occurrence rate products in order to calculate a per-target detection contour for the measured Data Release 25 (DR25) pipeline performance. A per-target detection contour measures for a given combination of orbital period, Porb, and planet radius, Rp, what fraction of transit signals are recoverable by the Kepler pipeline (Twicken et al., 2016; Jenkins et al., 2017). The steps for calculating a detection contour follow the procedure outlined in Burke et al. (2015), but have been updated to provide improved accuracy enabled by the substantially larger database of transit injection and recovery tests that were performed on the final version (i.e., SOC 9.3) of the Kepler pipeline (Christiansen, 2017; Burke Catanzarite, 2017a). In the following sections, we describe the main inputs to the per-target detection contour and provide a worked example of the python software released with this document (Kepler Planet Occurrence Rate Tools KeplerPORTs)1 that illustrates the generation of a detection contour in practice. As background material for this document and its nomenclature, we recommend the reader be familiar with the previous method of calculating a detection contour (Section 2 of Burke et al.,2015), input parameters relevant for describing the data quantity and quality of Kepler targets (Burke Catanzarite, 2017b), and the extensive new transit injection and recovery tests of the Kepler pipeline (Christiansen et al., 2016; Burke Catanzarite, 2017a; Christiansen, 2017).

  14. Robust Small Target Co-Detection from Airborne Infrared Image Sequences.

    PubMed

    Gao, Jingli; Wen, Chenglin; Liu, Meiqin

    2017-09-29

    In this paper, a novel infrared target co-detection model combining the self-correlation features of backgrounds and the commonality features of targets in the spatio-temporal domain is proposed to detect small targets in a sequence of infrared images with complex backgrounds. Firstly, a dense target extraction model based on nonlinear weights is proposed, which can better suppress background of images and enhance small targets than weights of singular values. Secondly, a sparse target extraction model based on entry-wise weighted robust principal component analysis is proposed. The entry-wise weight adaptively incorporates structural prior in terms of local weighted entropy, thus, it can extract real targets accurately and suppress background clutters efficiently. Finally, the commonality of targets in the spatio-temporal domain are used to construct target refinement model for false alarms suppression and target confirmation. Since real targets could appear in both of the dense and sparse reconstruction maps of a single frame, and form trajectories after tracklet association of consecutive frames, the location correlation of the dense and sparse reconstruction maps for a single frame and tracklet association of the location correlation maps for successive frames have strong ability to discriminate between small targets and background clutters. Experimental results demonstrate that the proposed small target co-detection method can not only suppress background clutters effectively, but also detect targets accurately even if with target-like interference.

  15. An Experiment Quantifying The Effect Of Clutter On Target Detection

    NASA Astrophysics Data System (ADS)

    Weathersby, Marshall R.; Schmieder, David E.

    1985-01-01

    Experiments were conducted to determine the influence of background clutter on target detection criteria. The experiment consisted of placing observers in front of displayed images on a TV monitor. Observer ability to detect military targets embedded in simulated natural and manmade background clutter was measured when there was unlimited viewing time. Results were described in terms of detection probability versus target resolution for various signal to clutter ratios (SCR). The experiments were preceded by a search for a meaningful clutter definition. The selected definition was a statistical measure computed by averaging the standard deviation of contiguous scene cells over the whole scene. The cell size was comparable to the target size. Observer test results confirmed the expectation that the resolution required for a given detection probability was a continuum function of the clutter level. At the lower SCRs the resolution required for a high probability of detection was near 6 lines pairs per target (LP/TGT), while at the higher SCRs it was found that a resolution of less than 0.25 LP/TGT would yield a high probability of detection. These results are expected to aid in target acquisition performance modeling and to lead to improved specifications for imaging automatic target screeners.

  16. Small target detection using objectness and saliency

    NASA Astrophysics Data System (ADS)

    Zhang, Naiwen; Xiao, Yang; Fang, Zhiwen; Yang, Jian; Wang, Li; Li, Tao

    2017-10-01

    We are motived by the need for generic object detection algorithm which achieves high recall for small targets in complex scenes with acceptable computational efficiency. We propose a novel object detection algorithm, which has high localization quality with acceptable computational cost. Firstly, we obtain the objectness map as in BING[1] and use NMS to get the top N points. Then, k-means algorithm is used to cluster them into K classes according to their location. We set the center points of the K classes as seed points. For each seed point, an object potential region is extracted. Finally, a fast salient object detection algorithm[2] is applied to the object potential regions to highlight objectlike pixels, and a series of efficient post-processing operations are proposed to locate the targets. Our method runs at 5 FPS on 1000*1000 images, and significantly outperforms previous methods on small targets in cluttered background.

  17. 8. VIEW, LOOKING SOUTHEAST, SHOWING DETAIL OF RANGE 3 TARGET ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    8. VIEW, LOOKING SOUTHEAST, SHOWING DETAIL OF RANGE 3 TARGET END, Interior - Winchester Repeating Arms Company, Tract K Shooting Range, 125 Munson Street (rear section), New Haven, New Haven County, CT

  18. 6. VIEW, LOOKING SOUTHEAST, SHOWING DETAIL OF RANGE 1 TARGET ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    6. VIEW, LOOKING SOUTHEAST, SHOWING DETAIL OF RANGE 1 TARGET END, Interior - Winchester Repeating Arms Company, Tract K Shooting Range, 125 Munson Street (rear section), New Haven, New Haven County, CT

  19. Camouflage, detection and identification of moving targets

    PubMed Central

    Hall, Joanna R.; Cuthill, Innes C.; Baddeley, Roland; Shohet, Adam J.; Scott-Samuel, Nicholas E.

    2013-01-01

    Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation—detection, identification and capture—in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, background-matching and disruptive patterns were found to be most successful. Experiment 2 showed that if stimuli move, an isolated moving object on a stationary background cannot avoid detection or capture regardless of the type of camouflage. Experiment 3 used an identification task and showed that while camouflage is unable to slow detection or capture, camouflaged targets are harder to identify than uncamouflaged targets when similar background objects are present. The specific details of the camouflage patterns have little impact on this effect. If one has to move, camouflage cannot impede detection; but if one is surrounded by similar targets (e.g. other animals in a herd, or moving background distractors), then camouflage can slow identification. Despite previous assumptions, motion does not entirely ‘break’ camouflage. PMID:23486439

  20. Camouflage, detection and identification of moving targets.

    PubMed

    Hall, Joanna R; Cuthill, Innes C; Baddeley, Roland; Shohet, Adam J; Scott-Samuel, Nicholas E

    2013-05-07

    Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation-detection, identification and capture-in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, background-matching and disruptive patterns were found to be most successful. Experiment 2 showed that if stimuli move, an isolated moving object on a stationary background cannot avoid detection or capture regardless of the type of camouflage. Experiment 3 used an identification task and showed that while camouflage is unable to slow detection or capture, camouflaged targets are harder to identify than uncamouflaged targets when similar background objects are present. The specific details of the camouflage patterns have little impact on this effect. If one has to move, camouflage cannot impede detection; but if one is surrounded by similar targets (e.g. other animals in a herd, or moving background distractors), then camouflage can slow identification. Despite previous assumptions, motion does not entirely 'break' camouflage.

  1. Target recognition of log-polar ladar range images using moment invariants

    NASA Astrophysics Data System (ADS)

    Xia, Wenze; Han, Shaokun; Cao, Jie; Yu, Haoyong

    2017-01-01

    The ladar range image has received considerable attentions in the automatic target recognition field. However, previous research does not cover target recognition using log-polar ladar range images. Therefore, we construct a target recognition system based on log-polar ladar range images in this paper. In this system combined moment invariants and backpropagation neural network are selected as shape descriptor and shape classifier, respectively. In order to fully analyze the effect of log-polar sampling pattern on recognition result, several comparative experiments based on simulated and real range images are carried out. Eventually, several important conclusions are drawn: (i) if combined moments are computed directly by log-polar range images, translation, rotation and scaling invariant properties of combined moments will be invalid (ii) when object is located in the center of field of view, recognition rate of log-polar range images is less sensitive to the changing of field of view (iii) as object position changes from center to edge of field of view, recognition performance of log-polar range images will decline dramatically (iv) log-polar range images has a better noise robustness than Cartesian range images. Finally, we give a suggestion that it is better to divide field of view into recognition area and searching area in the real application.

  2. Detection of Non-Nucleic Acid Targets with an Unmodified Aptamer and a Fluorogenic Competitor

    PubMed Central

    Li, Na

    2010-01-01

    Aptamers are oligonucleotides that can bind to various non-nucleic acid targets, ranging from proteins to small molecules, with a specificity and affinity comparable to that of antibodies. Most aptamer-based detection strategies require modification on the aptamer, which could lead to a significant loss in its affinity and specificity to the target. Here we reported a generic strategy to design aptamer-based optical probes. An unmodified aptamer specific to the target and a fluorogenic competitor complementary to the aptamer are utilized for target recognition and signal generation, respectively. The competitor is a hairpin oligonucleotide with a fluorophore attached on one end and a quencher attached on the other. When no target is present, the competitor binds to the aptamer. However, when the target is introduced, the competitor will be displaced from the aptamer by the target, thus resulting in a target-specific decrease in fluorescence signal. Successful application of this strategy to different types of targets (small molecules and proteins) as well as different types of aptamers (DNA and RNA) has been demonstrated. Furthermore, a thermodynamics-based prediction model was established to further rationalize the optimization process. Due to its rapidness and simplicity, this aptamer-based detection strategy holds great promise in high throughput applications. PMID:20563298

  3. Broadly targeted multiprobe QPCR for detection of coronaviruses: Coronavirus is common among mallard ducks (Anas platyrhynchos).

    PubMed

    Muradrasoli, Shaman; Mohamed, Nahla; Hornyák, Akos; Fohlman, Jan; Olsen, Björn; Belák, Sándor; Blomberg, Jonas

    2009-08-01

    Coronaviruses (CoVs) can cause trivial or fatal disease in humans and in animals. Detection methods for a wide range of CoVs are needed, to understand viral evolution, host range, transmission and maintenance in reservoirs. A new concept, "Multiprobe QPCR", which uses a balanced mixture of competing discrete non- or moderately degenerated nuclease degradable (TaqMan) probes was employed. It provides a broadly targeted and rational single tube real-time reverse transcription PCR ("NQPCR") for the generic detection and discovery of CoV. Degenerate primers, previously published, and the new probes, were from a conserved stretch of open reading frame 1b, encoding the replicase. This multiprobe design reduced the degree of probe degeneration, which otherwise decreases the sensitivity, and allowed a preliminary classification of the amplified sequence directly from the QPCR trace. The split probe strategy allowed detection of down to 10 viral nucleic acid equivalents of CoV from all known CoV groups. Evaluation was with reference CoV strains, synthetic targets, human respiratory samples and avian fecal samples. Infectious-Bronchitis-Virus (IBV)-related variants were found in 7 of 35 sample pools, from 100 wild mallards (Anas platyrhynchos). Ducks may spread and harbour CoVs. NQPCR can detect a wide range of CoVs, as illustrated for humans and ducks.

  4. Target attribute-based false alarm rejection in small infrared target detection

    NASA Astrophysics Data System (ADS)

    Kim, Sungho

    2012-11-01

    Infrared search and track is an important research area in military applications. Although there are a lot of works on small infrared target detection methods, we cannot apply them in real field due to high false alarm rate caused by clutters. This paper presents a novel target attribute extraction and machine learning-based target discrimination method. Eight kinds of target features are extracted and analyzed statistically. Learning-based classifiers such as SVM and Adaboost are developed and compared with conventional classifiers for real infrared images. In addition, the generalization capability is also inspected for various infrared clutters.

  5. Highly sensitive and specific colorimetric detection of cancer cells via dual-aptamer target binding strategy.

    PubMed

    Wang, Kun; Fan, Daoqing; Liu, Yaqing; Wang, Erkang

    2015-11-15

    Simple, rapid, sensitive and specific detection of cancer cells is of great importance for early and accurate cancer diagnostics and therapy. By coupling nanotechnology and dual-aptamer target binding strategies, we developed a colorimetric assay for visually detecting cancer cells with high sensitivity and specificity. The nanotechnology including high catalytic activity of PtAuNP and magnetic separation & concentration plays a vital role on the signal amplification and improvement of detection sensitivity. The color change caused by small amount of target cancer cells (10 cells/mL) can be clearly distinguished by naked eyes. The dual-aptamer target binding strategy guarantees the detection specificity that large amount of non-cancer cells and different cancer cells (10(4) cells/mL) cannot cause obvious color change. A detection limit as low as 10 cells/mL with detection linear range from 10 to 10(5) cells/mL was reached according to the experimental detections in phosphate buffer solution as well as serum sample. The developed enzyme-free and cost effective colorimetric assay is simple and no need of instrument while still provides excellent sensitivity, specificity and repeatability, having potential application on point-of-care cancer diagnosis. Copyright © 2015 Elsevier B.V. All rights reserved.

  6. Short-range/Long-range Integrated Target (SLIT) for Video Guidance Sensor Rendezvous and Docking

    NASA Technical Reports Server (NTRS)

    Roe, Fred D. (Inventor); Bryan, Thomas C. (Inventor)

    2009-01-01

    A laser target reflector assembly for mounting upon spacecraft having a long-range reflector array formed from a plurality of unfiltered light reflectors embedded in an array pattern upon a hemispherical reflector disposed upon a mounting plate. The reflector assembly also includes a short-range reflector array positioned upon the mounting body proximate to the long-range reflector array. The short-range reflector array includes three filtered light reflectors positioned upon extensions from the mounting body. The three filtered light reflectors retro-reflect substantially all incident light rays that are transmissive by their monochromatic filters and received by the three filtered light reflectors. In one embodiment the short-range reflector array is embedded within the hemispherical reflector,

  7. Non-Cooperative Target Recognition by Means of Singular Value Decomposition Applied to Radar High Resolution Range Profiles †

    PubMed Central

    López-Rodríguez, Patricia; Escot-Bocanegra, David; Fernández-Recio, Raúl; Bravo, Ignacio

    2015-01-01

    Radar high resolution range profiles are widely used among the target recognition community for the detection and identification of flying targets. In this paper, singular value decomposition is applied to extract the relevant information and to model each aircraft as a subspace. The identification algorithm is based on angle between subspaces and takes place in a transformed domain. In order to have a wide database of radar signatures and evaluate the performance, simulated range profiles are used as the recognition database while the test samples comprise data of actual range profiles collected in a measurement campaign. Thanks to the modeling of aircraft as subspaces only the valuable information of each target is used in the recognition process. Thus, one of the main advantages of using singular value decomposition, is that it helps to overcome the notable dissimilarities found in the shape and signal-to-noise ratio between actual and simulated profiles due to their difference in nature. Despite these differences, the recognition rates obtained with the algorithm are quite promising. PMID:25551484

  8. Extended linear detection range for optical tweezers using image-plane detection scheme

    NASA Astrophysics Data System (ADS)

    Hajizadeh, Faegheh; Masoumeh Mousavi, S.; Khaksar, Zeinab S.; Reihani, S. Nader S.

    2014-10-01

    Ability to measure pico- and femto-Newton range forces using optical tweezers (OT) strongly relies on the sensitivity of its detection system. We show that the commonly used back-focal-plane detection method provides a linear response range which is shorter than that of the restoring force of OT for large beads. This limits measurable force range of OT. We show, both theoretically and experimentally, that utilizing a second laser beam for tracking could solve the problem. We also propose a new detection scheme in which the quadrant photodiode is positioned at the plane optically conjugate to the object plane (image plane). This method solves the problem without need for a second laser beam for the bead sizes that are commonly used in force spectroscopy applications of OT, such as biopolymer stretching.

  9. Assessment of target detection limits in hyperspectral data

    NASA Astrophysics Data System (ADS)

    Gross, W.; Boehler, J.; Schilling, H.; Middelmann, W.; Weyermann, J.; Wellig, P.; Oechslin, R.; Kneubuehler, M.

    2015-10-01

    Hyperspectral remote sensing data can be used for civil and military applications to detect and classify target objects that cannot be reliably separated using broadband sensors. The comparably low spatial resolution is compensated by the fact that small targets, even below image resolution, can still be classified. The goal of this paper is to determine the target size to spatial resolution ratio for successful classification of different target and background materials. Airborne hyperspectral data is used to simulate data with known mixture ratios and to estimate the detection threshold for given false alarm rates. The data was collected in July 2014 over Greding, Germany, using airborne aisaEAGLE and aisaHAWK hyperspectral sensors. On the ground, various target materials were placed on natural background. The targets were four quadratic molton patches with an edge length of 7 meters in the colors black, white, grey and green. Also, two different types of polyethylene (camouflage nets) with an edge length of approximately 5.5 meters were deployed. Synthetic data is generated from the original data using spectral mixtures. Target signatures are linearly combined with different background materials in specific ratios. The simulated mixtures are appended to the original data and the target areas are removed for evaluation. Commonly used classification algorithms, e.g. Matched Filtering, Adaptive Cosine Estimator are used to determine the detection limit. Fixed false alarm rates are employed to find and analyze certain regions where false alarms usually occur first. A combination of 18 targets and 12 backgrounds is analyzed for three VNIR and two SWIR data sets of the same area.

  10. Target detection cycle criteria when using the targeting task performance metric

    NASA Astrophysics Data System (ADS)

    Hixson, Jonathan G.; Jacobs, Eddie L.; Vollmerhausen, Richard H.

    2004-12-01

    The US Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate of the US Army (NVESD) has developed a new target acquisition metric to better predict the performance of modern electro-optical imagers. The TTP metric replaces the Johnson criteria. One problem with transitioning to the new model is that the difficulty of searching in a terrain has traditionally been quantified by an "N50." The N50 is the number of Johnson criteria cycles needed for the observer to detect the target half the time, assuming that the observer is not time limited. In order to make use of this empirical data base, a conversion must be found relating Johnson cycles for detection to TTP cycles for detection. This paper describes how that relationship is established. We have found that the relationship between Johnson and TTP is 1:2.7 for the recognition and identification tasks.

  11. Dim target trajectory-associated detection in bright earth limb background

    NASA Astrophysics Data System (ADS)

    Chen, Penghui; Xu, Xiaojian; He, Xiaoyu; Jiang, Yuesong

    2015-09-01

    The intensive emission of earth limb in the field of view of sensors contributes much to the observation images. Due to the low signal-to-noise ratio (SNR), it is a challenge to detect small targets in earth limb background, especially for the detection of point-like targets from a single frame. To improve the target detection, track before detection (TBD) based on the frame sequence is performed. In this paper, a new technique is proposed to determine the target associated trajectories, which jointly carries out background removing, maximum value projection (MVP) and Hough transform. The background of the bright earth limb in the observation images is removed according to the profile characteristics. For a moving target, the corresponding pixels in the MVP image are shifting approximately regularly in time sequence. And the target trajectory is determined by Hough transform according to the pixel characteristics of the target and the clutter and noise. Comparing with traditional frame-by-frame methods, determining associated trajectories from MVP reduces the computation load. Numerical simulations are presented to demonstrate the effectiveness of the approach proposed.

  12. The big brown bat's perceptual dimension of target range

    NASA Astrophysics Data System (ADS)

    Simmons, James A.

    2005-09-01

    Big brown bats determine the distance to targets from echo delay, but information actually is entered onto the bat's psychological delay scale from two sources. The first is the target-ranging system itself, from the time that elapses between single-spike neural responses evoked by the broadcast and similar responses evoked by echoes at different delays. These responses register the FM sweeps of broadcasts or echoes, and the associated system of neural delay lines and coincidence detectors cross correlates the spectrograms along the time axis. The second source is the echo spectrum, which relates to shape expressed as range profile. The target-ranging system extracts this by fanning out to encompass parallel representations of many possible notch frequencies and notch widths in echoes. Bats perceive delay separations of 5-30 μs and have a resolution limit of about 2 μs, but interference amplifies small delay separations by transposing them into large changes in notch frequency, so only perception of intervals smaller than 5 μs is surprising. Experiments with phase-shifted echoes show that the psychological time scale can represent two different delays originating entirely in the time domain when they are at least as close together as 10 μs. [Work supported by NIH and ONR.

  13. Multi-dynamic range compressional wave detection using optical-frequency comb

    NASA Astrophysics Data System (ADS)

    Minamikawa, Takeo; Masuoka, Takashi; Oe, Ryo; Nakajima, Yoshiaki; Yamaoka, Yoshihisa; Minoshima, Kaoru; Yasui, Takeshi

    2018-02-01

    Compressional wave detection is useful means for health monitoring of building, detection of abnormal vibration of moving objects, defect evaluation, and biomedical imaging such as echography and photoacoustic imaging. The frequency of the compressional wave is varied from quasi-static to a few tens of megahertz depending on applications. Since the dynamic range of general compressional wave detectors is limited, we need to choose a proper compressional wave detector depending on applications. For the compressional wave detection with wide dynamic range, two or more detectors with different detection ranges is required. However, these detectors with different detection ranges generally has different accuracy and precision, disabling the seamless detection over these detection ranges. In this study, we proposed a compressional wave detector employing optical frequency comb (OFC). The compressional wave was sensed with a part of an OFC cavity, being encoded into OFC. The spectrally encoded OFC was converted to radio-frequency by the frequency link nature of OFC. The compressional wave-encoded radio-frequency can therefore be directly measured with a high-speed photodetector. To enhance the dynamic range of the compressional wave detection, we developed a cavityfeedback-based system and a phase-sensitive detection system, both of which the accuracy and precision are coherently linked to these of the OFC. We provided a proof-of-principle demonstration of the detection of compressional wave from quasi-static to ultrasound wave by using the OFC-based compressional wave sensor. Our proposed approach will serve as a unique and powerful tool for detecting compressional wave versatile applications in the future.

  14. Active Stand-off Detection of Gas Leaks Using a Short Range Hard-target Backscatter Differential Optical Absorption System Based on a Quantum Cascade Laser Transmitter

    NASA Astrophysics Data System (ADS)

    Diaz, Adrian; Thomas, Benjamin; Castillo, Paulo; Gross, Barry; Moshary, Fred

    2016-06-01

    Fugitive gas emissions from agricultural or industrial plants and gas pipelines are an important environmental concern as they can contribute to the global increase of greenhouse gas concentration. Moreover, they are also a security and safety concern because of possible risk of fire/explosion or toxicity. This study presents gas concentration measurements using a quantum cascade laser open path system (QCLOPS). The system retrieves the pathaveraged concentration of N2O and CH4 by collecting the backscattered light from a scattering target. The gas concentration measurements have a high temporal resolution (68 ms) and are achieved at sufficient range (up to 40 m, ~ 130 feet) with a detection limit of 2.6 ppm CH4 and 0.4 ppm for N2O. Given these characteristics, this system is promising for mobile/multidirectional remote detection and evaluation of gas leaks. The instrument is monostatic with a tunable QCL emitting at ~ 7.7 μm wavelength range. The backscattered radiation is collected by a Newtonian telescope and focused on an infrared light detector. Puffs of N2O and CH4 are released along the optical path to simulate a gas leak. The measured absorption spectrum is obtained using the thermal intra-pulse frequency chirped DFB QCL and is analyzed to obtain path averaged gas concentrations.

  15. Wavelength band selection method for multispectral target detection.

    PubMed

    Karlholm, Jörgen; Renhorn, Ingmar

    2002-11-10

    A framework is proposed for the selection of wavelength bands for multispectral sensors by use of hyperspectral reference data. Using the results from the detection theory we derive a cost function that is minimized by a set of spectral bands optimal in terms of detection performance for discrimination between a class of small rare targets and clutter with known spectral distribution. The method may be used, e.g., in the design of multispectral infrared search and track and electro-optical missile warning sensors, where a low false-alarm rate and a high-detection probability for detection of small targets against a clutter background are of critical importance, but the required high frame rate prevents the use of hyperspectral sensors.

  16. An Automated Directed Spectral Search Methodology for Small Target Detection

    NASA Astrophysics Data System (ADS)

    Grossman, Stanley I.

    Much of the current efforts in remote sensing tackle macro-level problems such as determining the extent of wheat in a field, the general health of vegetation or the extent of mineral deposits in an area. However, for many of the remaining remote sensing challenges being studied currently, such as border protection, drug smuggling, treaty verification, and the war on terror, most targets are very small in nature - a vehicle or even a person. While in typical macro-level problems the objective vegetation is in the scene, for small target detection problems it is not usually known if the desired small target even exists in the scene, never mind finding it in abundance. The ability to find specific small targets, such as vehicles, typifies this problem. Complicating the analyst's life, the growing number of available sensors is generating mountains of imagery outstripping the analysts' ability to visually peruse them. This work presents the important factors influencing spectral exploitation using multispectral data and suggests a different approach to small target detection. The methodology of directed search is presented, including the use of scene-modeled spectral libraries, various search algorithms, and traditional statistical and ROC curve analysis. The work suggests a new metric to calibrate analysis labeled the analytic sweet spot as well as an estimation method for identifying the sweet spot threshold for an image. It also suggests a new visualization aid for highlighting the target in its entirety called nearest neighbor inflation (NNI). It brings these all together to propose that these additions to the target detection arena allow for the construction of a fully automated target detection scheme. This dissertation next details experiments to support the hypothesis that the optimum detection threshold is the analytic sweet spot and that the estimation method adequately predicts it. Experimental results and analysis are presented for the proposed directed

  17. Twin target self-amplification-based DNA machine for highly sensitive detection of cancer-related gene.

    PubMed

    Xu, Huo; Jiang, Yifan; Liu, Dengyou; Liu, Kai; Zhang, Yafeng; Yu, Suhong; Shen, Zhifa; Wu, Zai-Sheng

    2018-06-29

    The sensitive detection of cancer-related genes is of great significance for early diagnosis and treatment of human cancers, and previous isothermal amplification sensing systems were often based on the reuse of target DNA, the amplification of enzymatic products and the accumulation of reporting probes. However, no reporting probes are able to be transformed into target species and in turn initiate the signal of other probes. Herein we reported a simple, isothermal and highly sensitive homogeneous assay system for tumor suppressor p53 gene detection based on a new autonomous DNA machine, where the signaling probe, molecular beacon (MB), was able to execute the function similar to target DNA besides providing the common signal. In the presence of target p53 gene, the operation of DNA machine can be initiated, and cyclical nucleic acid strand-displacement polymerization (CNDP) and nicking/polymerization cyclical amplification (NPCA) occur, during which the MB was opened by target species and cleaved by restriction endonuclease. In turn, the cleaved fragments could activate the next signaling process as target DNA did. According to the functional similarity, the cleaved fragment was called twin target, and the corresponding fashion to amplify the signal was named twin target self-amplification. Utilizing this newly-proposed DNA machine, the target DNA could be detected down to 0.1 pM with a wide dynamic range (6 orders of magnitude) and single-base mismatched targets were discriminated, indicating a very high assay sensitivity and good specificity. In addition, the DNA machine was not only used to screen the p53 gene in complex biological matrix but also was capable of practically detecting genomic DNA p53 extracted from A549 cell line. This indicates that the proposed DNA machine holds the potential application in biomedical research and early clinical diagnosis. Copyright © 2018 Elsevier B.V. All rights reserved.

  18. Improved target detection algorithm using Fukunaga-Koontz transform and distance classifier correlation filter

    NASA Astrophysics Data System (ADS)

    Bal, A.; Alam, M. S.; Aslan, M. S.

    2006-05-01

    Often sensor ego-motion or fast target movement causes the target to temporarily go out of the field-of-view leading to reappearing target detection problem in target tracking applications. Since the target goes out of the current frame and reenters at a later frame, the reentering location and variations in rotation, scale, and other 3D orientations of the target are not known thus complicating the detection algorithm has been developed using Fukunaga-Koontz Transform (FKT) and distance classifier correlation filter (DCCF). The detection algorithm uses target and background information, extracted from training samples, to detect possible candidate target images. The detected candidate target images are then introduced into the second algorithm, DCCF, called clutter rejection module, to determine the target coordinates are detected and tracking algorithm is initiated. The performance of the proposed FKT-DCCF based target detection algorithm has been tested using real-world forward looking infrared (FLIR) video sequences.

  19. A robust close-range photogrammetric target extraction algorithm for size and type variant targets

    NASA Astrophysics Data System (ADS)

    Nyarko, Kofi; Thomas, Clayton; Torres, Gilbert

    2016-05-01

    The Photo-G program conducted by Naval Air Systems Command at the Atlantic Test Range in Patuxent River, Maryland, uses photogrammetric analysis of large amounts of real-world imagery to characterize the motion of objects in a 3-D scene. Current approaches involve several independent processes including target acquisition, target identification, 2-D tracking of image features, and 3-D kinematic state estimation. Each process has its own inherent complications and corresponding degrees of both human intervention and computational complexity. One approach being explored for automated target acquisition relies on exploiting the pixel intensity distributions of photogrammetric targets, which tend to be patterns with bimodal intensity distributions. The bimodal distribution partitioning algorithm utilizes this distribution to automatically deconstruct a video frame into regions of interest (ROI) that are merged and expanded to target boundaries, from which ROI centroids are extracted to mark target acquisition points. This process has proved to be scale, position and orientation invariant, as well as fairly insensitive to global uniform intensity disparities.

  20. Supervised target detection in hyperspectral images using one-class Fukunaga-Koontz Transform

    NASA Astrophysics Data System (ADS)

    Binol, Hamidullah; Bal, Abdullah

    2016-05-01

    A novel hyperspectral target detection technique based on Fukunaga-Koontz transform (FKT) is presented. FKT offers significant properties for feature selection and ordering. However, it can only be used to solve multi-pattern classification problems. Target detection may be considered as a two-class classification problem, i.e., target versus background clutter. Nevertheless, background clutter typically contains different types of materials. That's why; target detection techniques are different than classification methods by way of modeling clutter. To avoid the modeling of the background clutter, we have improved one-class FKT (OC-FKT) for target detection. The statistical properties of target training samples are used to define tunnel-like boundary of the target class. Non-target samples are then created synthetically as to be outside of the boundary. Thus, only limited target samples become adequate for training of FKT. The hyperspectral image experiments confirm that the proposed OC-FKT technique provides an effective means for target detection.

  1. Single molecule targeted sequencing for cancer gene mutation detection.

    PubMed

    Gao, Yan; Deng, Liwei; Yan, Qin; Gao, Yongqian; Wu, Zengding; Cai, Jinsen; Ji, Daorui; Li, Gailing; Wu, Ping; Jin, Huan; Zhao, Luyang; Liu, Song; Ge, Liangjin; Deem, Michael W; He, Jiankui

    2016-05-19

    With the rapid decline in cost of sequencing, it is now affordable to examine multiple genes in a single disease-targeted clinical test using next generation sequencing. Current targeted sequencing methods require a separate step of targeted capture enrichment during sample preparation before sequencing. Although there are fast sample preparation methods available in market, the library preparation process is still relatively complicated for physicians to use routinely. Here, we introduced an amplification-free Single Molecule Targeted Sequencing (SMTS) technology, which combined targeted capture and sequencing in one step. We demonstrated that this technology can detect low-frequency mutations using artificially synthesized DNA sample. SMTS has several potential advantages, including simple sample preparation thus no biases and errors are introduced by PCR reaction. SMTS has the potential to be an easy and quick sequencing technology for clinical diagnosis such as cancer gene mutation detection, infectious disease detection, inherited condition screening and noninvasive prenatal diagnosis.

  2. Infrared small target detection based on directional zero-crossing measure

    NASA Astrophysics Data System (ADS)

    Zhang, Xiangyue; Ding, Qinghai; Luo, Haibo; Hui, Bin; Chang, Zheng; Zhang, Junchao

    2017-12-01

    Infrared small target detection under complex background and low signal-to-clutter ratio (SCR) condition is of great significance to the development on precision guidance and infrared surveillance. In order to detect targets precisely and extract targets from intricate clutters effectively, a detection method based on zero-crossing saliency (ZCS) map is proposed. The original map is first decomposed into different first-order directional derivative (FODD) maps by using FODD filters. Then the ZCS map is obtained by fusing all directional zero-crossing points. At last, an adaptive threshold is adopted to segment targets from the ZCS map. Experimental results on a series of images show that our method is effective and robust for detection under complex backgrounds. Moreover, compared with other five state-of-the-art methods, our method achieves better performance in terms of detection rate, SCR gain and background suppression factor.

  3. Model-based recognition of 3D articulated target using ladar range data.

    PubMed

    Lv, Dan; Sun, Jian-Feng; Li, Qi; Wang, Qi

    2015-06-10

    Ladar is suitable for 3D target recognition because ladar range images can provide rich 3D geometric surface information of targets. In this paper, we propose a part-based 3D model matching technique to recognize articulated ground military vehicles in ladar range images. The key of this approach is to solve the decomposition and pose estimation of articulated parts of targets. The articulated components were decomposed into isolate parts based on 3D geometric properties of targets, such as surface point normals, data histogram distribution, and data distance relationships. The corresponding poses of these separate parts were estimated through the linear characteristics of barrels. According to these pose parameters, all parts of the target were roughly aligned to 3D point cloud models in a library and fine matching was finally performed to accomplish 3D articulated target recognition. The recognition performance was evaluated with 1728 ladar range images of eight different articulated military vehicles with various part types and orientations. Experimental results demonstrated that the proposed approach achieved a high recognition rate.

  4. Automated multiple target detection and tracking in UAV videos

    NASA Astrophysics Data System (ADS)

    Mao, Hongwei; Yang, Chenhui; Abousleman, Glen P.; Si, Jennie

    2010-04-01

    In this paper, a novel system is presented to detect and track multiple targets in Unmanned Air Vehicles (UAV) video sequences. Since the output of the system is based on target motion, we first segment foreground moving areas from the background in each video frame using background subtraction. To stabilize the video, a multi-point-descriptor-based image registration method is performed where a projective model is employed to describe the global transformation between frames. For each detected foreground blob, an object model is used to describe its appearance and motion information. Rather than immediately classifying the detected objects as targets, we track them for a certain period of time and only those with qualified motion patterns are labeled as targets. In the subsequent tracking process, a Kalman filter is assigned to each tracked target to dynamically estimate its position in each frame. Blobs detected at a later time are used as observations to update the state of the tracked targets to which they are associated. The proposed overlap-rate-based data association method considers the splitting and merging of the observations, and therefore is able to maintain tracks more consistently. Experimental results demonstrate that the system performs well on real-world UAV video sequences. Moreover, careful consideration given to each component in the system has made the proposed system feasible for real-time applications.

  5. Detection range enhancement using circularly polarized light in scattering environments for infrared wavelengths

    DOE PAGES

    van der Laan, J. D.; Sandia National Lab.; Scrymgeour, D. A.; ...

    2015-03-13

    We find for infrared wavelengths there are broad ranges of particle sizes and refractive indices that represent fog and rain where the use of circular polarization can persist to longer ranges than linear polarization. Using polarization tracking Monte Carlo simulations for varying particle size, wavelength, and refractive index, we show that for specific scene parameters circular polarization outperforms linear polarization in maintaining the intended polarization state for large optical depths. This enhancement with circular polarization can be exploited to improve range and target detection in obscurant environments that are important in many critical sensing applications. Specifically, circular polarization persists bettermore » than linear for radiation fog in the short-wave infrared, for advection fog in the short-wave infrared and the long-wave infrared, and large particle sizes of Sahara dust around the 4 micron wavelength.« less

  6. [Passive ranging of infrared target using oxygen A-band and Elsasser model].

    PubMed

    Li, Jin-Hua; Wang, Zhao-Ba; Wang Zhi

    2014-09-01

    Passive ranging method of short range and single band was developed based on target radiation and attenuation characteristic of oxygen spectrum absorption. The relation between transmittance of oxygen A band and range of measured target was analyzed. Radiation strength distribution of measured target can be obtained according to the distribution law of absorption coefficient with environmental parameters. Passive ranging mathematical model of short ranges was established using Elsasser model with Lorentz line shape based on the computational methods of band average transmittance and high-temperature gas radiation narrowband model. The range of measured object was obtained using transmittance fitting with test data calculation and theoretical model. Besides, ranging precision was corrected considering the influence of oxygen absorption with enviromental parameter. The ranging experiment platform was established. The source was a 10 watt black body, and a grating spectrometer with 17 cm(-1) resolution was used. In order to improve the light receiving efficiency, light input was collected with 23 mm calibre telescope. The test data was processed for different range in 200 m. The results show that the transmittance accuracy was better than 2.18% in short range compared to the test data with predicted value in the same conditions.

  7. Development of a microcapillary column for detecting targeted messenger RNA molecules.

    PubMed

    Ohnishi, Michihiro

    2006-03-24

    A capillary column in a rapid-flow system has been developed for detecting targeted messenger RNA (mRNA) molecules. The column has a structure made of two beds-one bed of porous microbeads and one bed of microbeads with a polythymidine base sequence. The targeted eukaryotic mRNA molecules are detected by two-step hybridization (sandwich hybridization) composed of polyadenosine selection of mRNA molecules and formation of a probe-target (targeted mRNA) hybrid. The sandwich hybridization, which is accomplished within 1 h, was tested using synthetic polydeoxynucleotides. Ten picomoles of the targeted polydeoxynucleotide were detected.

  8. Target molecules detection by waveguiding in a photonic silicon membrane

    DOEpatents

    Letant, Sonia E [Livermore, CA; Van Buuren, Anthony [Livermore, CA; Terminello, Louis [Danville, CA; Hart, Bradley R [Brentwood, CA

    2006-12-26

    Disclosed herein is a porous silicon filter capable of binding and detecting biological and chemical target molecules in liquid or gas samples. A photonic waveguiding silicon filter with chemical and/or biological anchors covalently attached to the pore walls bind target molecules. The system uses transmission curve engineering principles to allow measurements to be made in situ and in real time to detect the presence of various target molecules and calculate the concentration of bound target.

  9. Target molecules detection by waveguiding in a photonic silicon membrane

    DOEpatents

    Letant, Sonia; Van Buuren, Anthony; Terminello, Louis

    2004-08-31

    Disclosed herein is a photonic silicon filter capable of binding and detecting biological and chemical target molecules in liquid or gas samples. A photonic waveguiding silicon filter with chemical and/or biological anchors covalently attached to the pore walls selectively bind target molecules. The system uses transmission curve engineering principles to allow measurements to be made in situ and in real time to detect the presence of various target molecules and determine the concentration of bound target.

  10. Target detection using microwave irradiances from natural sources: A passive, local and global surveillance system

    NASA Technical Reports Server (NTRS)

    Stacey, J. M.

    1984-01-01

    Detection of metal objects on or near the Earth's surface was investigated using existing, passive, microwave sensors operating from Earth orbit. The range equations are derived from basic microwave principles and theories and the expressions are given explicitly to estimate the signal to noise ratio for detecting metal targets operating as bistatic scatterers. Actual measurements are made on a range of metal objects observed from orbit using existing passive microwave receiving systems. The details of the measurements and the results are tabulated and discussed. The advantages of a passive microwave sensor as it is applied to surveillance of metal objects as viewed from aerial platforms or from orbit, are examined.

  11. Target detection in insects: optical, neural and behavioral optimizations.

    PubMed

    Gonzalez-Bellido, Paloma T; Fabian, Samuel T; Nordström, Karin

    2016-12-01

    Motion vision provides important cues for many tasks. Flying insects, for example, may pursue small, fast moving targets for mating or feeding purposes, even when these are detected against self-generated optic flow. Since insects are small, with size-constrained eyes and brains, they have evolved to optimize their optical, neural and behavioral target visualization solutions. Indeed, even if evolutionarily distant insects display different pursuit strategies, target neuron physiology is strikingly similar. Furthermore, the coarse spatial resolution of the insect compound eye might actually be beneficial when it comes to detection of moving targets. In conclusion, tiny insects show higher than expected performance in target visualization tasks. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  12. Target recognition of ladar range images using slice image: comparison of four improved algorithms

    NASA Astrophysics Data System (ADS)

    Xia, Wenze; Han, Shaokun; Cao, Jingya; Wang, Liang; Zhai, Yu; Cheng, Yang

    2017-07-01

    Compared with traditional 3-D shape data, ladar range images possess properties of strong noise, shape degeneracy, and sparsity, which make feature extraction and representation difficult. The slice image is an effective feature descriptor to resolve this problem. We propose four improved algorithms on target recognition of ladar range images using slice image. In order to improve resolution invariance of the slice image, mean value detection instead of maximum value detection is applied in these four improved algorithms. In order to improve rotation invariance of the slice image, three new improved feature descriptors-which are feature slice image, slice-Zernike moments, and slice-Fourier moments-are applied to the last three improved algorithms, respectively. Backpropagation neural networks are used as feature classifiers in the last two improved algorithms. The performance of these four improved recognition systems is analyzed comprehensively in the aspects of the three invariances, recognition rate, and execution time. The final experiment results show that the improvements for these four algorithms reach the desired effect, the three invariances of feature descriptors are not directly related to the final recognition performance of recognition systems, and these four improved recognition systems have different performances under different conditions.

  13. A saliency-based approach to detection of infrared target

    NASA Astrophysics Data System (ADS)

    Chen, Yanfei; Sang, Nong; Dan, Zhiping

    2013-10-01

    Automatic target detection in infrared images is a hot research field of national defense technology. We propose a new saliency-based infrared target detection model in this paper, which is based on the fact that human focus of attention is directed towards the relevant target to interpret the most promising information. For a given image, the convolution of the image log amplitude spectrum with a low-pass Gaussian kernel of an appropriate scale is equivalent to an image saliency detector in the frequency domain. At the same time, orientation and shape features extracted are combined into a saliency map in the spatial domain. Our proposed model decides salient targets based on a final saliency map, which is generated by integration of the saliency maps in the frequency and spatial domain. At last, the size of each salient target is obtained by maximizing entropy of the final saliency map. Experimental results show that the proposed model can highlight both small and large salient regions in infrared image, as well as inhibit repeated distractors in cluttered image. In addition, its detecting efficiency has improved significantly.

  14. Lesion detectability in 2D-mammography and digital breast tomosynthesis using different targets and observers

    NASA Astrophysics Data System (ADS)

    Elangovan, Premkumar; Mackenzie, Alistair; Dance, David R.; Young, Kenneth C.; Wells, Kevin

    2018-05-01

    This work investigates the detection performance of specialist and non-specialist observers for different targets in 2D-mammography and digital breast tomosynthesis (DBT) using the OPTIMAM virtual clinical trials (VCT) Toolbox and a 4-alternative forced choice (4AFC) assessment paradigm. Using 2D-mammography and DBT images of virtual breast phantoms, we compare the detection limits of simple uniform spherical targets and irregular solid masses. Target diameters of 4 mm and 6 mm have been chosen to represent target sizes close to the minimum detectable size found in breast screening, across a range of controlled contrast levels. The images were viewed by a set of specialist observers (five medical physicists and six experienced clinical readers) and five non-specialists. Combined results from both observer groups indicate that DBT has a significantly lower detectable threshold contrast than 2D-mammography for small masses (4 mm: 2.1% [DBT] versus 6.9% [2D]; 6 mm: 0.7% [DBT] versus 3.9% [2D]) and spheres (4 mm: 2.9% [DBT] versus 5.3% [2D]; 6 mm: 0.3% [DBT] versus 2.2% [2D]) (p  <  0.0001). Both observer groups found spheres significantly easier to detect than irregular solid masses for both sizes and modalities (p  <  0.0001) (except 4 mm DBT). The detection performances of specialist and non-specialist observers were generally found to be comparable, where each group marginally outperformed the other in particular detection tasks. Within the specialist group, the clinical readers performed better than the medical physicists with irregular masses (p  <  0.0001). The results indicate that using spherical targets in such studies may produce over-optimistic detection thresholds compared to more complex masses, and that the superiority of DBT for detecting masses over 2D-mammography has been quantified. The results also suggest specialist observers may be supplemented by non-specialist observers (with training) in some types of 4AFC studies.

  15. An infrared small target detection method based on multiscale local homogeneity measure

    NASA Astrophysics Data System (ADS)

    Nie, Jinyan; Qu, Shaocheng; Wei, Yantao; Zhang, Liming; Deng, Lizhen

    2018-05-01

    Infrared (IR) small target detection plays an important role in the field of image detection area owing to its intrinsic characteristics. This paper presents a multiscale local homogeneity measure (MLHM) for infrared small target detection, which can enhance the performance of IR small target detection system. Firstly, intra-patch homogeneity of the target itself and the inter-patch heterogeneity between target and the local background regions are integrated to enhance the significant of small target. Secondly, a multiscale measure based on local regions is proposed to obtain the most appropriate response. Finally, an adaptive threshold method is applied to small target segmentation. Experimental results on three different scenarios indicate that the MLHM has good performance under the interference of strong noise.

  16. Incorporating signal-dependent noise for hyperspectral target detection

    NASA Astrophysics Data System (ADS)

    Morman, Christopher J.; Meola, Joseph

    2015-05-01

    The majority of hyperspectral target detection algorithms are developed from statistical data models employing stationary background statistics or white Gaussian noise models. Stationary background models are inaccurate as a result of two separate physical processes. First, varying background classes often exist in the imagery that possess different clutter statistics. Many algorithms can account for this variability through the use of subspaces or clustering techniques. The second physical process, which is often ignored, is a signal-dependent sensor noise term. For photon counting sensors that are often used in hyperspectral imaging systems, sensor noise increases as the measured signal level increases as a result of Poisson random processes. This work investigates the impact of this sensor noise on target detection performance. A linear noise model is developed describing sensor noise variance as a linear function of signal level. The linear noise model is then incorporated for detection of targets using data collected at Wright Patterson Air Force Base.

  17. Colorimetric Detection of Small Molecules in Complex Matrixes via Target-Mediated Growth of Aptamer-Functionalized Gold Nanoparticles.

    PubMed

    Soh, Jun Hui; Lin, Yiyang; Rana, Subinoy; Ying, Jackie Y; Stevens, Molly M

    2015-08-04

    A versatile and sensitive colorimetric assay that allows the rapid detection of small-molecule targets using the naked eye is demonstrated. The working principle of the assay integrates aptamer-target recognition and the aptamer-controlled growth of gold nanoparticles (Au NPs). Aptamer-target interactions modulate the amount of aptamer strands adsorbed on the surface of aptamer-functionalized Au NPs via desorption of the aptamer strands when target molecules bind with the aptamer. Depending on the resulting aptamer coverage, Au NPs grow into morphologically varied nanostructures, which give rise to different colored solutions. Au NPs with low aptamer coverage grow into spherical NPs, which produce red-colored solutions, whereas Au NPs with high aptamer coverage grow into branched NPs, which produce blue-colored solutions. We achieved visible colorimetric response and nanomolar detection limits for the detection of ochratoxin A (1 nM) in red wine samples, as well as cocaine (1 nM) and 17β-estradiol (0.2 nM) in spiked synthetic urine and saliva, respectively. The detection limits were well within clinically and physiologically relevant ranges, and below the maximum food safety limits. The assay is highly sensitive, specific, and able to detect an array of analytes rapidly without requiring sophisticated equipment, making it relevant for many applications, such as high-throughput drug and clinical screening, food sampling, and diagnostics. Furthermore, the assay is easily adapted as a chip-based platform for rapid and portable target detection.

  18. A computational imaging target specific detectivity metric

    NASA Astrophysics Data System (ADS)

    Preece, Bradley L.; Nehmetallah, George

    2017-05-01

    Due to the large quantity of low-cost, high-speed computational processing available today, computational imaging (CI) systems are expected to have a major role for next generation multifunctional cameras. The purpose of this work is to quantify the performance of theses CI systems in a standardized manner. Due to the diversity of CI system designs that are available today or proposed in the near future, significant challenges in modeling and calculating a standardized detection signal-to-noise ratio (SNR) to measure the performance of these systems. In this paper, we developed a path forward for a standardized detectivity metric for CI systems. The detectivity metric is designed to evaluate the performance of a CI system searching for a specific known target or signal of interest, and is defined as the optimal linear matched filter SNR, similar to the Hotelling SNR, calculated in computational space with special considerations for standardization. Therefore, the detectivity metric is designed to be flexible, in order to handle various types of CI systems and specific targets, while keeping the complexity and assumptions of the systems to a minimum.

  19. Target detection method by airborne and spaceborne images fusion based on past images

    NASA Astrophysics Data System (ADS)

    Chen, Shanjing; Kang, Qing; Wang, Zhenggang; Shen, ZhiQiang; Pu, Huan; Han, Hao; Gu, Zhongzheng

    2017-11-01

    To solve the problem that remote sensing target detection method has low utilization rate of past remote sensing data on target area, and can not recognize camouflage target accurately, a target detection method by airborne and spaceborne images fusion based on past images is proposed in this paper. The target area's past of space remote sensing image is taken as background. The airborne and spaceborne remote sensing data is fused and target feature is extracted by the means of airborne and spaceborne images registration, target change feature extraction, background noise suppression and artificial target feature extraction based on real-time aerial optical remote sensing image. Finally, the support vector machine is used to detect and recognize the target on feature fusion data. The experimental results have established that the proposed method combines the target area change feature of airborne and spaceborne remote sensing images with target detection algorithm, and obtains fine detection and recognition effect on camouflage and non-camouflage targets.

  20. Quantum illumination for enhanced detection of Rayleigh-fading targets

    NASA Astrophysics Data System (ADS)

    Zhuang, Quntao; Zhang, Zheshen; Shapiro, Jeffrey H.

    2017-08-01

    Quantum illumination (QI) is an entanglement-enhanced sensing system whose performance advantage over a comparable classical system survives its usage in an entanglement-breaking scenario plagued by loss and noise. In particular, QI's error-probability exponent for discriminating between equally likely hypotheses of target absence or presence is 6 dB higher than that of the optimum classical system using the same transmitted power. This performance advantage, however, presumes that the target return, when present, has known amplitude and phase, a situation that seldom occurs in light detection and ranging (lidar) applications. At lidar wavelengths, most target surfaces are sufficiently rough that their returns are speckled, i.e., they have Rayleigh-distributed amplitudes and uniformly distributed phases. QI's optical parametric amplifier receiver—which affords a 3 dB better-than-classical error-probability exponent for a return with known amplitude and phase—fails to offer any performance gain for Rayleigh-fading targets. We show that the sum-frequency generation receiver [Zhuang et al., Phys. Rev. Lett. 118, 040801 (2017), 10.1103/PhysRevLett.118.040801]—whose error-probability exponent for a nonfading target achieves QI's full 6 dB advantage over optimum classical operation—outperforms the classical system for Rayleigh-fading targets. In this case, QI's advantage is subexponential: its error probability is lower than the classical system's by a factor of 1 /ln(M κ ¯NS/NB) , when M κ ¯NS/NB≫1 , with M ≫1 being the QI transmitter's time-bandwidth product, NS≪1 its brightness, κ ¯ the target return's average intensity, and NB the background light's brightness.

  1. Clever eye algorithm for target detection of remote sensing imagery

    NASA Astrophysics Data System (ADS)

    Geng, Xiurui; Ji, Luyan; Sun, Kang

    2016-04-01

    Target detection algorithms for hyperspectral remote sensing imagery, such as the two most commonly used remote sensing detection algorithms, the constrained energy minimization (CEM) and matched filter (MF), can usually be attributed to the inner product between a weight filter (or detector) and a pixel vector. CEM and MF have the same expression except that MF requires data centralization first. However, this difference leads to a difference in the target detection results. That is to say, the selection of the data origin could directly affect the performance of the detector. Therefore, does there exist another data origin other than the zero and mean-vector points for a better target detection performance? This is a very meaningful issue in the field of target detection, but it has not been paid enough attention yet. In this study, we propose a novel objective function by introducing the data origin as another variable, and the solution of the function is corresponding to the data origin with the minimal output energy. The process of finding the optimal solution can be vividly regarded as a clever eye automatically searching the best observing position and direction in the feature space, which corresponds to the largest separation between the target and background. Therefore, this new algorithm is referred to as the clever eye algorithm (CE). Based on the Sherman-Morrison formula and the gradient ascent method, CE could derive the optimal target detection result in terms of energy. Experiments with both synthetic and real hyperspectral data have verified the effectiveness of our method.

  2. Detection of target phonemes in spontaneous and read speech.

    PubMed

    Mehta, G; Cutler, A

    1988-01-01

    Although spontaneous speech occurs more frequently in most listeners' experience than read speech, laboratory studies of human speech recognition typically use carefully controlled materials read from a script. The phonological and prosodic characteristics of spontaneous and read speech differ considerably, however, which suggests that laboratory results may not generalise to the recognition of spontaneous speech. In the present study listeners were presented with both spontaneous and read speech materials, and their response time to detect word-initial target phonemes was measured. Responses were, overall, equally fast in each speech mode. However, analysis of effects previously reported in phoneme detection studies revealed significant differences between speech modes. In read speech but not in spontaneous speech, later targets were detected more rapidly than targets preceded by short words. In contrast, in spontaneous speech but not in read speech, targets were detected more rapidly in accented than in unaccented words and in strong than in weak syllables. An explanation for this pattern is offered in terms of characteristic prosodic differences between spontaneous and read speech. The results support claims from previous work that listeners pay great attention to prosodic information in the process of recognising speech.

  3. Automatic small target detection in synthetic infrared images

    NASA Astrophysics Data System (ADS)

    Yardımcı, Ozan; Ulusoy, Ä.°lkay

    2017-05-01

    Automatic detection of targets from far distances is a very challenging problem. Background clutter and small target size are the main difficulties which should be solved while reaching a high detection performance as well as a low computational load. The pre-processing, detection and post-processing approaches are very effective on the final results. In this study, first of all, various methods in the literature were evaluated separately for each of these stages using the simulated test scenarios. Then, a full system of detection was constructed among available solutions which resulted in the best performance in terms of detection. However, although a precision rate as 100% was reached, the recall values stayed low around 25-45%. Finally, a post-processing method was proposed which increased the recall value while keeping the precision at 100%. The proposed post-processing method, which is based on local operations, increased the recall value to 65-95% in all test scenarios.

  4. Penalty dynamic programming algorithm for dim targets detection in sensor systems.

    PubMed

    Huang, Dayu; Xue, Anke; Guo, Yunfei

    2012-01-01

    In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations.

  5. Penalty Dynamic Programming Algorithm for Dim Targets Detection in Sensor Systems

    PubMed Central

    Huang, Dayu; Xue, Anke; Guo, Yunfei

    2012-01-01

    In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations. PMID:22666074

  6. High-Speed Incoming Infrared Target Detection by Fusion of Spatial and Temporal Detectors

    PubMed Central

    Kim, Sungho

    2015-01-01

    This paper presents a method for detecting high-speed incoming targets by the fusion of spatial and temporal detectors to achieve a high detection rate for an active protection system (APS). The incoming targets have different image velocities according to the target-camera geometry. Therefore, single-target detector-based approaches, such as a 1D temporal filter, 2D spatial filter and 3D matched filter, cannot provide a high detection rate with moderate false alarms. The target speed variation was analyzed according to the incoming angle and target velocity. The speed of the distant target at the firing time is almost stationary and increases slowly. The speed varying targets are detected stably by fusing the spatial and temporal filters. The stationary target detector is activated by an almost zero temporal contrast filter (TCF) and identifies targets using a spatial filter called the modified mean subtraction filter (M-MSF). A small motion (sub-pixel velocity) target detector is activated by a small TCF value and finds targets using the same spatial filter. A large motion (pixel-velocity) target detector works when the TCF value is high. The final target detection is terminated by fusing the three detectors based on the threat priority. The experimental results of the various target sequences show that the proposed fusion-based target detector produces the highest detection rate with an acceptable false alarm rate. PMID:25815448

  7. An underwater ranging system based on photoacoustic effect occurring on target surface

    NASA Astrophysics Data System (ADS)

    Ni, Kai; Hu, Kai; Li, Xinghui; Wang, Lidai; Zhou, Qian; Wang, Xiaohao

    2016-11-01

    In this paper, an underwater ranging system based on photoacoustic effect occurring on target surface is proposed. In this proposal, laser pulse generated by blue-green laser is directly incident on target surface, where the photoacoustic effect occurs and a sound source is formed. And then the sound wave which is also called photoacoustic signal is received by the ultrasonic receiver after passing through water. According to the time delay between transmitting laser and receiving photoacoustic signal, and sound velocity in water, the distance between the target and the ultrasonic receiver can be calculated. Differing from underwater range finding by only laser, this approach can avoid backscattering of laser beam, so easier to implement. Experimental system according to this principle has been constructed to verify the feasibility of this technology. The experimental results showed that a ranging accuracy of 1 mm can be effectively achieved when the target is close to the ultrasonic receiver.

  8. A chest-shape target automatic detection method based on Deformable Part Models

    NASA Astrophysics Data System (ADS)

    Zhang, Mo; Jin, Weiqi; Li, Li

    2016-10-01

    Automatic weapon platform is one of the important research directions at domestic and overseas, it needs to accomplish fast searching for the object to be shot under complex background. Therefore, fast detection for given target is the foundation of further task. Considering that chest-shape target is common target of shoot practice, this paper treats chestshape target as the target and studies target automatic detection method based on Deformable Part Models. The algorithm computes Histograms of Oriented Gradient(HOG) features of the target and trains a model using Latent variable Support Vector Machine(SVM); In this model, target image is divided into several parts then we can obtain foot filter and part filters; Finally, the algorithm detects the target at the HOG features pyramid with method of sliding window. The running time of extracting HOG pyramid with lookup table can be shorten by 36%. The result indicates that this algorithm can detect the chest-shape target in natural environments indoors or outdoors. The true positive rate of detection reaches 76% with many hard samples, and the false positive rate approaches 0. Running on a PC (Intel(R)Core(TM) i5-4200H CPU) with C++ language, the detection time of images with the resolution of 640 × 480 is 2.093s. According to TI company run library about image pyramid and convolution for DM642 and other hardware, our detection algorithm is expected to be implemented on hardware platform, and it has application prospect in actual system.

  9. Target Detection Using an AOTF Hyperspectral Imager

    NASA Technical Reports Server (NTRS)

    Cheng, L-J.; Mahoney, J.; Reyes, F.; Suiter, H.

    1994-01-01

    This paper reports results of a recent field experiment using a prototype system to evaluate the acousto-optic tunable filter polarimetric hyperspectral imaging technology for target detection applications.

  10. Portable apparatus for separating sample and detecting target analytes

    DOEpatents

    Renzi, Ronald F.; Wally, Karl; Crocker, Robert W.; Stamps, James F.; Griffiths; Stewart K. ,; Fruetel, Julia A.; Horn, Brent A.; Shokair, Isaac R.; Yee, Daniel D.; VanderNoot, Victoria A.; Wiedenman, Boyd J.; West, Jason A. A.; Ferko, Scott M.

    2008-11-18

    Portable devices and methods for determining the presence of a target analyte using a portable device are provided. The portable device is preferably hand-held. A sample is injected to the portable device. A microfluidic separation is performed within the portable device and at least one separated component detected by a detection module within the portable device, in embodiments of the invention. A target analyte is identified, based on the separated component, and the presence of the target analyte is indicated on an output interface of the portable device, in accordance with embodiments of the invention.

  11. Estimate of the influence of muzzle smoke on function range of infrared system

    NASA Astrophysics Data System (ADS)

    Luo, Yan-ling; Wang, Jun; Wu, Jiang-hui; Wu, Jun; Gao, Meng; Gao, Fei; Zhao, Yu-jie; Zhang, Lei

    2013-09-01

    Muzzle smoke produced by weapons shooting has important influence on infrared (IR) system while detecting targets. Based on the theoretical model of detecting spot targets and surface targets of IR system while there is muzzle smoke, the function range for detecting spot targets and surface targets are deduced separately according to the definition of noise equivalent temperature difference(NETD) and minimum resolution temperature difference(MRTD). Also parameters of muzzle smoke affecting function range of IR system are analyzed. Base on measured data of muzzle smoke for single shot, the function range of an IR system for detecting typical targets are calculated separately while there is muzzle smoke and there is no muzzle smoke at 8-12 micron waveband. For our IR system function range has reduced by over 10% for detecting tank if muzzle smoke exists. The results will provide evidence for evaluating the influence of muzzle smoke on IR system and will help researchers to improve ammo craftwork.

  12. Invariant target detection by a correlation radiometer

    NASA Astrophysics Data System (ADS)

    Murza, L. P.

    1986-12-01

    The paper is concerned with the problem of the optimal detection of a heat-emitting target by a two-channel radiometer with an unstable amplification circuit. An expression is obtained for an asymptotically sufficient detection statistic which is invariant to changes in the amplification coefficients of the channels. The algorithm proposed here can be implemented numerically using a relatively simple program.

  13. Studies on Training Ground Observers to Estimate Range to Aerial Targets.

    ERIC Educational Resources Information Center

    McCluskey, Michael R.; And Others

    Six pilot studies were conducted to determine the effects of training on range estimation performance for aerial targets, and to identify some of the relevant variables. Observers were trained to estimate ranges of 350, 400, 800, 1,500, or 2,500 meters. Several variations of range estimation training methods were used, including immediate…

  14. Sensor Compromise Detection in Multiple-Target Tracking Systems

    PubMed Central

    Doucette, Emily A.; Curtis, Jess W.

    2018-01-01

    Tracking multiple targets using a single estimator is a problem that is commonly approached within a trusted framework. There are many weaknesses that an adversary can exploit if it gains control over the sensors. Because the number of targets that the estimator has to track is not known with anticipation, an adversary could cause a loss of information or a degradation in the tracking precision. Other concerns include the introduction of false targets, which would result in a waste of computational and material resources, depending on the application. In this work, we study the problem of detecting compromised or faulty sensors in a multiple-target tracker, starting with the single-sensor case and then considering the multiple-sensor scenario. We propose an algorithm to detect a variety of attacks in the multiple-sensor case, via the application of finite set statistics (FISST), one-class classifiers and hypothesis testing using nonparametric techniques. PMID:29466314

  15. Glint-induced false alarm reduction in signature adaptive target detection

    NASA Astrophysics Data System (ADS)

    Crosby, Frank J.

    2002-07-01

    The signal adaptive target detection algorithm developed by Crosby and Riley uses target geometry to discern anomalies in local backgrounds. Detection is not restricted based on specific target signatures. The robustness of the algorithm is limited by an increased false alarm potential. The base algorithm is extended to eliminate one common source of false alarms in a littoral environment. This common source is glint reflected on the surface of water. The spectral and spatial transience of glint prevent straightforward characterization and complicate exclusion. However, the statistical basis of the detection algorithm and its inherent computations allow for glint discernment and the removal of its influence.

  16. A long-term target detection approach in infrared image sequence

    NASA Astrophysics Data System (ADS)

    Li, Hang; Zhang, Qi; Wang, Xin; Hu, Chao

    2016-10-01

    An automatic target detection method used in long term infrared (IR) image sequence from a moving platform is proposed. Firstly, based on POME(the principle of maximum entropy), target candidates are iteratively segmented. Then the real target is captured via two different selection approaches. At the beginning of image sequence, the genuine target with litter texture is discriminated from other candidates by using contrast-based confidence measure. On the other hand, when the target becomes larger, we apply online EM method to estimate and update the distributions of target's size and position based on the prior detection results, and then recognize the genuine one which satisfies both the constraints of size and position. Experimental results demonstrate that the presented method is accurate, robust and efficient.

  17. The application of IR detector with windowing technique in the small and dim target detection

    NASA Astrophysics Data System (ADS)

    Su, Xiaofeng; Chen, Fansheng; Dong, Yucui; Cui, Kun; Huang, Sijie

    2015-04-01

    The performance of small and dim IR target detection is mostly affected by the signal to noise ratio(SNR) and signal to clutter ratio(SCR), for the MWIR especially LWIR array detector, because of the background radiation and the optical system radiation, the SCR cannot be unlimited increased by using a longer integral time, so the frame rate of the detector was mainly limited by the data readout time especially in a large-scale infrared detector, in this paper a new MWIR array detector with windowing technique was used to do the experiment, which can get a faster frame rate around the target by using the windowing mode, so the redundant information could be ignore, and the background subtraction was used to remove the fixed pattern noise and adjust the dynamic range of the target, then a local NUC(non uniformity correction) technique was proposed to improve the SCR of the target, the advantage between local NUC and global NUC was analyzed in detail, finally the multi local window frame accumulation was adopted to enhance the target further, and the SNR of the target was improved. The experiment showed the SCR of the target can improved from 1.3 to 36 at 30 frames accumulation, which make the target detection and tracking become very easily by using the new method.

  18. Target detection portal

    DOEpatents

    Linker, Kevin L.; Brusseau, Charles A.

    2002-01-01

    A portal apparatus for screening persons or objects for the presence of trace amounts of target substances such as explosives, narcotics, radioactive materials, and certain chemical materials. The portal apparatus can have a one-sided exhaust for an exhaust stream, an interior wall configuration with a concave-shape across a horizontal cross-section for each of two facing sides to result in improved airflow and reduced washout relative to a configuration with substantially flat parallel sides; air curtains to reduce washout; ionizing sprays to collect particles bound by static forces, as well as gas jet nozzles to dislodge particles bound by adhesion to the screened person or object. The portal apparatus can be included in a detection system with a preconcentrator and a detector.

  19. Direct detection of sub-GeV dark matter with semiconductor targets

    DOE PAGES

    Essig, Rouven; Fernández-Serra, Marivi; Mardon, Jeremy; ...

    2016-05-09

    Dark matter in the sub-GeV mass range is a theoretically motivated but largely unexplored paradigm. Such light masses are out of reach for conventional nuclear recoil direct detection experiments, but may be detected through the small ionization signals caused by dark matter-electron scattering. Semiconductors are well-studied and are particularly promising target materials because their O(1 eV) band gaps allow for ionization signals from dark matter particles as light as a few hundred keV. Current direct detection technologies are being adapted for dark matter-electron scattering. In this paper, we provide the theoretical calculations for dark matter-electron scattering rate in semiconductors, overcomingmore » several complications that stem from the many-body nature of the problem. We use density functional theory to numerically calculate the rates for dark matter-electron scattering in silicon and germanium, and estimate the sensitivity for upcoming experiments such as DAMIC and SuperCDMS. We find that the reach for these upcoming experiments has the potential to be orders of magnitude beyond current direct detection constraints and that sub-GeV dark matter has a sizable modulation signal. We also give the first direct detection limits on sub-GeV dark matter from its scattering off electrons in a semiconductor target (silicon) based on published results from DAMIC. We make available publicly our code, QEdark, with which we calculate our results. Our results can be used by experimental collaborations to calculate their own sensitivities based on their specific setup. In conclusion, the searches we propose will probe vast new regions of unexplored dark matter model and parameter space.« less

  20. Carbon nanosphere-based fluorescence aptasensor for targeted detection of breast cancer cell MCF-7.

    PubMed

    Yang, Dandan; Liu, Mei; Xu, Jing; Yang, Chao; Wang, Xiaoxiao; Lou, Yongbing; He, Nongyue; Wang, Zhifei

    2018-08-01

    In this work, carbon nanosphere (CNS)-based fluorescence "turn off/on" aptasensor was developed for targeted detection of breast cancer cell MCF-7 by conjugation with FAM (a dye)-labeled mucin1 (MUC1) aptamer P0 (P0-FAM), which can recognize MUC1 protein overexpressed on the surface of MCF-7. Different from other carbon based fluorescence quenching materials, CNSs prepared by the carbonization of glucose not only have the high fluorescence quenching efficiency (98.8%), but also possess negligible cytotoxicity (in the concentration range of 0-1 mg/mL, which is 10 times higher than that of traditional carbon nanotubes or graphene oxide (0-100 µg/mL)). As for the detection of the mimic of the tumor antigen MUC1, the resulting fluorescence intensity increases nearly linearly in the range of 0-6 μM with the limit of detection (LOD) of 25 nM. Copyright © 2018 Elsevier B.V. All rights reserved.

  1. Flash Detection Efficiencies of Long Range Lightning Detection Networks During GRIP

    NASA Technical Reports Server (NTRS)

    Mach, Douglas M.; Bateman, Monte G.; Blakeslee, Richard J.

    2012-01-01

    We flew our Lightning Instrument Package (LIP) on the NASA Global Hawk as a part of the Genesis and Rapid Intensification Processes (GRIP) field program. The GRIP program was a NASA Earth science field experiment during the months of August and September, 2010. During the program, the LIP detected lighting from 48 of the 213 of the storms overflown by the Global Hawk. The time and location of tagged LIP flashes can be used as a "ground truth" dataset for checking the detection efficiency of the various long or extended range ground-based lightning detection systems available during the GRIP program. The systems analyzed included Vaisala Long Range (LR), Vaisala GLD360, the World Wide Lightning Location Network (WWLLN), and the Earth Networks Total Lightning Network (ENTLN). The long term goal of our research is to help understand the advantages and limitations of these systems so that we can utilize them for both proxy data applications and cross sensor validation of the GOES-R Geostationary Lightning Mapper (GLM) sensor when it is launched in the 2015 timeframe.

  2. Towards Discovery and Targeted Peptide Biomarker Detection Using nanoESI-TIMS-TOF MS

    NASA Astrophysics Data System (ADS)

    Garabedian, Alyssa; Benigni, Paolo; Ramirez, Cesar E.; Baker, Erin S.; Liu, Tao; Smith, Richard D.; Fernandez-Lima, Francisco

    2018-05-01

    In the present work, the potential of trapped ion mobility spectrometry coupled to TOF mass spectrometry (TIMS-TOF MS) for discovery and targeted monitoring of peptide biomarkers from human-in-mouse xenograft tumor tissue was evaluated. In particular, a TIMS-MS workflow was developed for the detection and quantification of peptide biomarkers using internal heavy analogs, taking advantage of the high mobility resolution (R = 150-250) prior to mass analysis. Five peptide biomarkers were separated, identified, and quantified using offline nanoESI-TIMS-CID-TOF MS; the results were in good agreement with measurements using a traditional LC-ESI-MS/MS proteomics workflow. The TIMS-TOF MS analysis permitted peptide biomarker detection based on accurate mobility, mass measurements, and high sequence coverage for concentrations in the 10-200 nM range, while simultaneously achieving discovery measurements of not initially targeted peptides as markers from the same proteins and, eventually, other proteins. [Figure not available: see fulltext.

  3. Applying the log-normal distribution to target detection

    NASA Astrophysics Data System (ADS)

    Holst, Gerald C.

    1992-09-01

    Holst and Pickard experimentally determined that MRT responses tend to follow a log-normal distribution. The log normal distribution appeared reasonable because nearly all visual psychological data is plotted on a logarithmic scale. It has the additional advantage that it is bounded to positive values; an important consideration since probability of detection is often plotted in linear coordinates. Review of published data suggests that the log-normal distribution may have universal applicability. Specifically, the log-normal distribution obtained from MRT tests appears to fit the target transfer function and the probability of detection of rectangular targets.

  4. Contrast, size, and orientation-invariant target detection in infrared imagery

    NASA Astrophysics Data System (ADS)

    Zhou, Yi-Tong; Crawshaw, Richard D.

    1991-08-01

    Automatic target detection in IR imagery is a very difficult task due to variations in target brightness, shape, size, and orientation. In this paper, the authors present a contrast, size, and orientation invariant algorithm based on Gabor functions for detecting targets from a single IR image frame. The algorithms consists of three steps. First, it locates potential targets by using low-resolution Gabor functions which resist noise and background clutter effects, then, it removes false targets and eliminates redundant target points based on a similarity measure. These two steps mimic human vision processing but are different from Zeevi's Foveating Vision System. Finally, it uses both low- and high-resolution Gabor functions to verify target existence. This algorithm has been successfully tested on several IR images that contain multiple examples of military vehicles with different size and brightness in various background scenes and orientations.

  5. Detection and quantification of bacterial biofilms combining high-frequency acoustic microscopy and targeted lipid microparticles

    PubMed Central

    2014-01-01

    Background Immuno-compromised patients such as those undergoing cancer chemotherapy are susceptible to bacterial infections leading to biofilm matrix formation. This surrounding biofilm matrix acts as a diffusion barrier that binds up antibiotics and antibodies, promoting resistance to treatment. Developing non-invasive imaging methods that detect biofilm matrix in the clinic are needed. The use of ultrasound in conjunction with targeted ultrasound contrast agents (UCAs) may provide detection of early stage biofilm matrix formation and facilitate optimal treatment. Results Ligand-targeted UCAs were investigated as a novel method for pre-clinical non-invasive molecular imaging of early and late stage biofilms. These agents were used to target, image and detect Staphylococcus aureus biofilm matrix in vitro. Binding efficacy was assessed on biofilm matrices with respect to their increasing biomass ranging from 3.126 × 103 ± 427 UCAs per mm2 of biofilm surface area within 12 h to 21.985 × 103 ± 855 per mm2 of biofilm matrix surface area at 96 h. High-frequency acoustic microscopy was used to ultrasonically detect targeted UCAs bound to a biofilm matrix and to assess biofilm matrix mechanoelastic physical properties. Acoustic impedance data demonstrated that biofilm matrices exhibit impedance values (1.9 MRayl) close to human tissue (1.35 - 1.85 MRayl for soft tissues). Moreover, the acoustic signature of mature biofilm matrices were evaluated in terms of integrated backscatter (0.0278 - 0.0848 mm-1 × sr-1) and acoustic attenuation (3.9 Np/mm for bound UCAs; 6.58 Np/mm for biofilm alone). Conclusions Early diagnosis of biofilm matrix formation is a challenge in treating cancer patients with infection-associated biofilms. We report for the first time a combined optical and acoustic evaluation of infectious biofilm matrices. We demonstrate that acoustic impedance of biofilms is similar to the impedance of human tissues, making in vivo imaging and detection of biofilm

  6. Detection and quantification of bacterial biofilms combining high-frequency acoustic microscopy and targeted lipid microparticles.

    PubMed

    Anastasiadis, Pavlos; Mojica, Kristina D A; Allen, John S; Matter, Michelle L

    2014-07-06

    Immuno-compromised patients such as those undergoing cancer chemotherapy are susceptible to bacterial infections leading to biofilm matrix formation. This surrounding biofilm matrix acts as a diffusion barrier that binds up antibiotics and antibodies, promoting resistance to treatment. Developing non-invasive imaging methods that detect biofilm matrix in the clinic are needed. The use of ultrasound in conjunction with targeted ultrasound contrast agents (UCAs) may provide detection of early stage biofilm matrix formation and facilitate optimal treatment. Ligand-targeted UCAs were investigated as a novel method for pre-clinical non-invasive molecular imaging of early and late stage biofilms. These agents were used to target, image and detect Staphylococcus aureus biofilm matrix in vitro. Binding efficacy was assessed on biofilm matrices with respect to their increasing biomass ranging from 3.126 × 103 ± 427 UCAs per mm(2) of biofilm surface area within 12 h to 21.985 × 103 ± 855 per mm(2) of biofilm matrix surface area at 96 h. High-frequency acoustic microscopy was used to ultrasonically detect targeted UCAs bound to a biofilm matrix and to assess biofilm matrix mechanoelastic physical properties. Acoustic impedance data demonstrated that biofilm matrices exhibit impedance values (1.9 MRayl) close to human tissue (1.35 - 1.85 MRayl for soft tissues). Moreover, the acoustic signature of mature biofilm matrices were evaluated in terms of integrated backscatter (0.0278 - 0.0848 mm(-1) × sr(-1)) and acoustic attenuation (3.9 Np/mm for bound UCAs; 6.58 Np/mm for biofilm alone). Early diagnosis of biofilm matrix formation is a challenge in treating cancer patients with infection-associated biofilms. We report for the first time a combined optical and acoustic evaluation of infectious biofilm matrices. We demonstrate that acoustic impedance of biofilms is similar to the impedance of human tissues, making in vivo imaging and detection of biofilm matrices difficult

  7. Directional detection of dark matter with two-dimensional targets

    NASA Astrophysics Data System (ADS)

    Hochberg, Yonit; Kahn, Yonatan; Lisanti, Mariangela; Tully, Christopher G.; Zurek, Kathryn M.

    2017-09-01

    We propose two-dimensional materials as targets for direct detection of dark matter. Using graphene as an example, we focus on the case where dark matter scattering deposits sufficient energy on a valence-band electron to eject it from the target. We show that the sensitivity of graphene to dark matter of MeV to GeV mass can be comparable, for similar exposure and background levels, to that of semiconductor targets such as silicon and germanium. Moreover, a two-dimensional target is an excellent directional detector, as the ejected electron retains information about the angular dependence of the incident dark matter particle. This proposal can be implemented by the PTOLEMY experiment, presenting for the first time an opportunity for directional detection of sub-GeV dark matter.

  8. Directional detection of dark matter with two-dimensional targets

    DOE PAGES

    Hochberg, Yonit; Kahn, Yonatan; Lisanti, Mariangela; ...

    2017-09-01

    We propose two-dimensional materials as targets for direct detection of dark matter. Using graphene as an example, we focus on the case where dark matter scattering deposits sufficient energy on a valence-band electron to eject it from the target. Here, we show that the sensitivity of graphene to dark matter of MeV to GeV mass can be comparable, for similar exposure and background levels, to that of semiconductor targets such as silicon and germanium. Moreover, a two-dimensional target is an excellent directional detector, as the ejected electron retains information about the angular dependence of the incident dark matter particle. Ourmore » proposal can be implemented by the PTOLEMY experiment, presenting for the first time an opportunity for directional detection of sub-GeV dark matter.« less

  9. Directional detection of dark matter with two-dimensional targets

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Hochberg, Yonit; Kahn, Yonatan; Lisanti, Mariangela

    We propose two-dimensional materials as targets for direct detection of dark matter. Using graphene as an example, we focus on the case where dark matter scattering deposits sufficient energy on a valence-band electron to eject it from the target. Here, we show that the sensitivity of graphene to dark matter of MeV to GeV mass can be comparable, for similar exposure and background levels, to that of semiconductor targets such as silicon and germanium. Moreover, a two-dimensional target is an excellent directional detector, as the ejected electron retains information about the angular dependence of the incident dark matter particle. Ourmore » proposal can be implemented by the PTOLEMY experiment, presenting for the first time an opportunity for directional detection of sub-GeV dark matter.« less

  10. Detection of dual-band infrared small target based on joint dynamic sparse representation

    NASA Astrophysics Data System (ADS)

    Zhou, Jinwei; Li, Jicheng; Shi, Zhiguang; Lu, Xiaowei; Ren, Dongwei

    2015-10-01

    Infrared small target detection is a crucial and yet still is a difficult issue in aeronautic and astronautic applications. Sparse representation is an important mathematic tool and has been used extensively in image processing in recent years. Joint sparse representation is applied in dual-band infrared dim target detection in this paper. Firstly, according to the characters of dim targets in dual-band infrared images, 2-dimension Gaussian intensity model was used to construct target dictionary, then the dictionary was classified into different sub-classes according to different positions of Gaussian function's center point in image block; The fact that dual-band small targets detection can use the same dictionary and the sparsity doesn't lie in atom-level but in sub-class level was utilized, hence the detection of targets in dual-band infrared images was converted to be a joint dynamic sparse representation problem. And the dynamic active sets were used to describe the sparse constraint of coefficients. Two modified sparsity concentration index (SCI) criteria was proposed to evaluate whether targets exist in the images. In experiments, it shows that the proposed algorithm can achieve better detecting performance and dual-band detection is much more robust to noise compared with single-band detection. Moreover, the proposed method can be expanded to multi-spectrum small target detection.

  11. Neural Dynamics Underlying Target Detection in the Human Brain

    PubMed Central

    Bansal, Arjun K.; Madhavan, Radhika; Agam, Yigal; Golby, Alexandra; Madsen, Joseph R.

    2014-01-01

    Sensory signals must be interpreted in the context of goals and tasks. To detect a target in an image, the brain compares input signals and goals to elicit the correct behavior. We examined how target detection modulates visual recognition signals by recording intracranial field potential responses from 776 electrodes in 10 epileptic human subjects. We observed reliable differences in the physiological responses to stimuli when a cued target was present versus absent. Goal-related modulation was particularly strong in the inferior temporal and fusiform gyri, two areas important for object recognition. Target modulation started after 250 ms post stimulus, considerably after the onset of visual recognition signals. While broadband signals exhibited increased or decreased power, gamma frequency power showed predominantly increases during target presence. These observations support models where task goals interact with sensory inputs via top-down signals that influence the highest echelons of visual processing after the onset of selective responses. PMID:24553944

  12. Sparsity based target detection for compressive spectral imagery

    NASA Astrophysics Data System (ADS)

    Boada, David Alberto; Arguello Fuentes, Henry

    2016-09-01

    Hyperspectral imagery provides significant information about the spectral characteristics of objects and materials present in a scene. It enables object and feature detection, classification, or identification based on the acquired spectral characteristics. However, it relies on sophisticated acquisition and data processing systems able to acquire, process, store, and transmit hundreds or thousands of image bands from a given area of interest which demands enormous computational resources in terms of storage, computationm, and I/O throughputs. Specialized optical architectures have been developed for the compressed acquisition of spectral images using a reduced set of coded measurements contrary to traditional architectures that need a complete set of measurements of the data cube for image acquisition, dealing with the storage and acquisition limitations. Despite this improvement, if any processing is desired, the image has to be reconstructed by an inverse algorithm in order to be processed, which is also an expensive task. In this paper, a sparsity-based algorithm for target detection in compressed spectral images is presented. Specifically, the target detection model adapts a sparsity-based target detector to work in a compressive domain, modifying the sparse representation basis in the compressive sensing problem by means of over-complete training dictionaries and a wavelet basis representation. Simulations show that the presented method can achieve even better detection results than the state of the art methods.

  13. Scan statistics with local vote for target detection in distributed system

    NASA Astrophysics Data System (ADS)

    Luo, Junhai; Wu, Qi

    2017-12-01

    Target detection has occupied a pivotal position in distributed system. Scan statistics, as one of the most efficient detection methods, has been applied to a variety of anomaly detection problems and significantly improves the probability of detection. However, scan statistics cannot achieve the expected performance when the noise intensity is strong, or the signal emitted by the target is weak. The local vote algorithm can also achieve higher target detection rate. After the local vote, the counting rule is always adopted for decision fusion. The counting rule does not use the information about the contiguity of sensors but takes all sensors' data into consideration, which makes the result undesirable. In this paper, we propose a scan statistics with local vote (SSLV) method. This method combines scan statistics with local vote decision. Before scan statistics, each sensor executes local vote decision according to the data of its neighbors and its own. By combining the advantages of both, our method can obtain higher detection rate in low signal-to-noise ratio environment than the scan statistics. After the local vote decision, the distribution of sensors which have detected the target becomes more intensive. To make full use of local vote decision, we introduce a variable-step-parameter for the SSLV. It significantly shortens the scan period especially when the target is absent. Analysis and simulations are presented to demonstrate the performance of our method.

  14. A long-term target detection approach in infrared image sequence

    NASA Astrophysics Data System (ADS)

    Li, Hang; Zhang, Qi; Li, Yuanyuan; Wang, Liqiang

    2015-12-01

    An automatic target detection method used in long term infrared (IR) image sequence from a moving platform is proposed. Firstly, based on non-linear histogram equalization, target candidates are coarse-to-fine segmented by using two self-adapt thresholds generated in the intensity space. Then the real target is captured via two different selection approaches. At the beginning of image sequence, the genuine target with litter texture is discriminated from other candidates by using contrast-based confidence measure. On the other hand, when the target becomes larger, we apply online EM method to iteratively estimate and update the distributions of target's size and position based on the prior detection results, and then recognize the genuine one which satisfies both the constraints of size and position. Experimental results demonstrate that the presented method is accurate, robust and efficient.

  15. Disulfide-induced self-assembled targets: A novel strategy for the label free colorimetric detection of DNAs/RNAs via unmodified gold nanoparticles

    NASA Astrophysics Data System (ADS)

    Shokri, Ehsan; Hosseini, Morteza; Davari, Mehdi D.; Ganjali, Mohammad R.; Peppelenbosch, Maikel P.; Rezaee, Farhad

    2017-04-01

    A modified non-cross-linking gold-nanoparticles (Au-NPs) aggregation strategy has been developed for the label free colorimetric detection of DNAs/RNAs based on self-assembling target species in the presence of thiolated probes. Two complementary thiol- modified probes, each of which specifically binds at one half of the target introduced SH groups at both ends of dsDNA. Continuous disulfide bond formation at 3‧ and 5‧ terminals of targets leads to the self-assembly of dsDNAs into the sulfur- rich and flexible products with different lengths. These products have a high affinity for the surface of Au-NPs and efficiently protect the surface from salt induced aggregation. To evaluate the assay efficacy, a small part of the citrus tristeza virus (CTV) genome was targeted, leading to a detection limit of about 5 × 10-9 mol.L-1 over a linear ranged from 20 × 10-9 to 10 × 10-7 mol.L-1. This approach also exhibits good reproducibility and recovery levels in the presence of plant total RNA or human plasma total circulating RNA extracts. Self-assembled targets can be then sensitively distinguished from non-assembled or mismatched targets after gel electrophoresis. The disulfide reaction method and integrating self-assembled DNAs/RNAs targets with bare AuNPs as a sensitive indicator provide us a powerful and simple visual detection tool for a wide range of applications.

  16. Universal surface-enhanced Raman scattering amplification detector for ultrasensitive detection of multiple target analytes.

    PubMed

    Zheng, Jing; Hu, Yaping; Bai, Junhui; Ma, Cheng; Li, Jishan; Li, Yinhui; Shi, Muling; Tan, Weihong; Yang, Ronghua

    2014-02-18

    Up to now, the successful fabrication of efficient hot-spot substrates for surface-enhanced Raman scattering (SERS) remains an unsolved problem. To address this issue, we describe herein a universal aptamer-based SERS biodetection approach that uses a single-stranded DNA as a universal trigger (UT) to induce SERS-active hot-spot formation, allowing, in turn, detection of a broad range of targets. More specifically, interaction between the aptamer probe and its target perturbs a triple-helix aptamer/UT structure in a manner that activates a hybridization chain reaction (HCR) among three short DNA building blocks that self-assemble into a long DNA polymer. The SERS-active hot-spots are formed by conjugating 4-aminobenzenethiol (4-ABT)-encoded gold nanoparticles with the DNA polymer through a specific Au-S bond. As proof-of-principle, we used this approach to quantify multiple target analytes, including thrombin, adenosine, and CEM cancer cells, achieving lowest limit of detection values of 18 pM, 1.5 nM, and 10 cells/mL, respectively. As a universal SERS detector, this prototype can be applied to many other target analytes through the use of suitable DNA-functional partners, thus inspiring new designs and applications of SERS for bioanalysis.

  17. A Plane Target Detection Algorithm in Remote Sensing Images based on Deep Learning Network Technology

    NASA Astrophysics Data System (ADS)

    Shuxin, Li; Zhilong, Zhang; Biao, Li

    2018-01-01

    Plane is an important target category in remote sensing targets and it is of great value to detect the plane targets automatically. As remote imaging technology developing continuously, the resolution of the remote sensing image has been very high and we can get more detailed information for detecting the remote sensing targets automatically. Deep learning network technology is the most advanced technology in image target detection and recognition, which provided great performance improvement in the field of target detection and recognition in the everyday scenes. We combined the technology with the application in the remote sensing target detection and proposed an algorithm with end to end deep network, which can learn from the remote sensing images to detect the targets in the new images automatically and robustly. Our experiments shows that the algorithm can capture the feature information of the plane target and has better performance in target detection with the old methods.

  18. Multi-target Detection, Tracking, and Data Association on Road Networks Using Unmanned Aerial Vehicles

    NASA Astrophysics Data System (ADS)

    Barkley, Brett E.

    A cooperative detection and tracking algorithm for multiple targets constrained to a road network is presented for fixed-wing Unmanned Air Vehicles (UAVs) with a finite field of view. Road networks of interest are formed into graphs with nodes that indicate the target likelihood ratio (before detection) and position probability (after detection). A Bayesian likelihood ratio tracker recursively assimilates target observations until the cumulative observations at a particular location pass a detection criterion. At this point, a target is considered detected and a position probability is generated for the target on the graph. Data association is subsequently used to route future measurements to update the likelihood ratio tracker (for undetected target) or to update a position probability (a previously detected target). Three strategies for motion planning of UAVs are proposed to balance searching for new targets with tracking known targets for a variety of scenarios. Performance was tested in Monte Carlo simulations for a variety of mission parameters, including tracking on road networks with varying complexity and using UAVs at various altitudes.

  19. Method of detecting luminescent target ions with modified magnetic microspheres

    DOEpatents

    Shkrob, Ilya A; Kaminski, Michael D

    2014-05-13

    This invention provides methods of using modified magnetic microspheres to extract target ions from a sample in order to detect their presence in a microfluidic environment. In one or more embodiments, the microspheres are modified with molecules on the surface that allow the target ions in the sample to form complexes with specific ligand molecules on the microsphere surface. In one or more embodiments, the microspheres are modified with molecules that sequester the target ions from the sample, but specific ligand molecules in solution subsequently re-extract the target ions from the microspheres into the solution, where the complexes form independent of the microsphere surface. Once the complexes form, they are exposed to an excitation wavelength light source suitable for exciting the target ion to emit a luminescent signal pattern. Detection of the luminescent signal pattern allows for determination of the presence of the target ions in the sample.

  20. Remote sensing image ship target detection method based on visual attention model

    NASA Astrophysics Data System (ADS)

    Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

    2017-11-01

    The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.

  1. The influence of the earth radiation on space target detection system

    NASA Astrophysics Data System (ADS)

    Su, Xiaofeng; Chen, FanSheng; Cuikun, .; Liuyan, .

    2017-05-01

    In the view of space remote sensing such as satellite detection space debris detection etc. visible band is usually used in order to have the all-weather detection capability, long wavelength infrared (LWIR) detection is also an important supplement. However, in the tow wave band, the earth can be a very strong interference source, especially in the dim target detecting. When the target is close to the earth, especially the LEO target, the background radiation of the earth will also enter into the baffle, and became the stray light through reflection, the stray light can reduce the signal to clutter ratio (SCR) of the target and make it difficult to be detected. In the visible band, the solar albedo by the earth is the main clutter source while in the LWIR band the radiation of the earth is the main clutter source. So, in this paper, we establish the energy transformation from the earth background radiation to the detection system to assess the effects of the stray light. Firstly, we discretize the surface of the earth to different unit, and using MODTRAN to calculate the radiation of the discrete point in different light and climate conditions, then, we integral all the radiation which can reach the baffle in the same observation angles to get the energy distribution, finally, according the target energy and the non-uniformity of the detector, we can calculate the design requirement of the system stray light suppression, which provides the design basis for the optical system.

  2. Real Time Intelligent Target Detection and Analysis with Machine Vision

    NASA Technical Reports Server (NTRS)

    Howard, Ayanna; Padgett, Curtis; Brown, Kenneth

    2000-01-01

    We present an algorithm for detecting a specified set of targets for an Automatic Target Recognition (ATR) application. ATR involves processing images for detecting, classifying, and tracking targets embedded in a background scene. We address the problem of discriminating between targets and nontarget objects in a scene by evaluating 40x40 image blocks belonging to an image. Each image block is first projected onto a set of templates specifically designed to separate images of targets embedded in a typical background scene from those background images without targets. These filters are found using directed principal component analysis which maximally separates the two groups. The projected images are then clustered into one of n classes based on a minimum distance to a set of n cluster prototypes. These cluster prototypes have previously been identified using a modified clustering algorithm based on prior sensed data. Each projected image pattern is then fed into the associated cluster's trained neural network for classification. A detailed description of our algorithm will be given in this paper. We outline our methodology for designing the templates, describe our modified clustering algorithm, and provide details on the neural network classifiers. Evaluation of the overall algorithm demonstrates that our detection rates approach 96% with a false positive rate of less than 0.03%.

  3. Targeted analyte detection by standard addition improves detection limits in matrix-assisted laser desorption/ionization mass spectrometry.

    PubMed

    Toghi Eshghi, Shadi; Li, Xingde; Zhang, Hui

    2012-09-18

    Matrix-assisted laser desorption/ionization (MALDI) has proven an effective tool for fast and accurate determination of many molecules. However, the detector sensitivity and chemical noise compromise the detection of many invaluable low-abundance molecules from biological and clinical samples. To challenge this limitation, we developed a targeted analyte detection (TAD) technique. In TAD, the target analyte is selectively elevated by spiking a known amount of that analyte into the sample, thereby raising its concentration above the noise level, where we take advantage of the improved sensitivity to detect the presence of the endogenous analyte in the sample. We assessed TAD on three peptides in simple and complex background solutions with various exogenous analyte concentrations in two MALDI matrices. TAD successfully improved the limit of detection (LOD) of target analytes when the target peptides were added to the sample in a concentration close to optimum concentration. The optimum exogenous concentration was estimated through a quantitative method to be approximately equal to the original LOD for each target. Also, we showed that TAD could achieve LOD improvements on an average of 3-fold in a simple and 2-fold in a complex sample. TAD provides a straightforward assay to improve the LOD of generic target analytes without the need for costly hardware modifications.

  4. Attention to baseline: does orienting visuospatial attention really facilitate target detection?

    PubMed

    Albares, Marion; Criaud, Marion; Wardak, Claire; Nguyen, Song Chi Trung; Ben Hamed, Suliann; Boulinguez, Philippe

    2011-08-01

    Standard protocols testing the orientation of visuospatial attention usually present spatial cues before targets and compare valid-cue trials with invalid-cue trials. The valid/invalid contrast results in a relative behavioral or physiological difference that is generally interpreted as a benefit of attention orientation. However, growing evidence suggests that inhibitory control of response is closely involved in this kind of protocol that requires the subjects to withhold automatic responses to cues, probably biasing behavioral and physiological baselines. Here, we used two experiments to disentangle the inhibitory control of automatic responses from orienting of visuospatial attention in a saccadic reaction time task in humans, a variant of the classical cue-target detection task and a sustained visuospatial attentional task. Surprisingly, when referring to a simple target detection task in which there is no need to refrain from reacting to avoid inappropriate responses, we found no consistent evidence of facilitation of target detection at the attended location. Instead, we observed a cost at the unattended location. Departing from the classical view, our results suggest that reaction time measures of visuospatial attention probably relie on the attenuation of elementary processes involved in visual target detection and saccade initiation away from the attended location rather than on facilitation at the attended location. This highlights the need to use proper control conditions in experimental designs to disambiguate relative from absolute cueing benefits on target detection reaction times, both in psychophysical and neurophysiological studies.

  5. panelcn.MOPS: Copy-number detection in targeted NGS panel data for clinical diagnostics.

    PubMed

    Povysil, Gundula; Tzika, Antigoni; Vogt, Julia; Haunschmid, Verena; Messiaen, Ludwine; Zschocke, Johannes; Klambauer, Günter; Hochreiter, Sepp; Wimmer, Katharina

    2017-07-01

    Targeted next-generation-sequencing (NGS) panels have largely replaced Sanger sequencing in clinical diagnostics. They allow for the detection of copy-number variations (CNVs) in addition to single-nucleotide variants and small insertions/deletions. However, existing computational CNV detection methods have shortcomings regarding accuracy, quality control (QC), incidental findings, and user-friendliness. We developed panelcn.MOPS, a novel pipeline for detecting CNVs in targeted NGS panel data. Using data from 180 samples, we compared panelcn.MOPS with five state-of-the-art methods. With panelcn.MOPS leading the field, most methods achieved comparably high accuracy. panelcn.MOPS reliably detected CNVs ranging in size from part of a region of interest (ROI), to whole genes, which may comprise all ROIs investigated in a given sample. The latter is enabled by analyzing reads from all ROIs of the panel, but presenting results exclusively for user-selected genes, thus avoiding incidental findings. Additionally, panelcn.MOPS offers QC criteria not only for samples, but also for individual ROIs within a sample, which increases the confidence in called CNVs. panelcn.MOPS is freely available both as R package and standalone software with graphical user interface that is easy to use for clinical geneticists without any programming experience. panelcn.MOPS combines high sensitivity and specificity with user-friendliness rendering it highly suitable for routine clinical diagnostics. © 2017 The Authors. Human Mutation published by Wiley Periodicals, Inc.

  6. panelcn.MOPS: Copy‐number detection in targeted NGS panel data for clinical diagnostics

    PubMed Central

    Povysil, Gundula; Tzika, Antigoni; Vogt, Julia; Haunschmid, Verena; Messiaen, Ludwine; Zschocke, Johannes; Klambauer, Günter; Wimmer, Katharina

    2017-01-01

    Abstract Targeted next‐generation‐sequencing (NGS) panels have largely replaced Sanger sequencing in clinical diagnostics. They allow for the detection of copy‐number variations (CNVs) in addition to single‐nucleotide variants and small insertions/deletions. However, existing computational CNV detection methods have shortcomings regarding accuracy, quality control (QC), incidental findings, and user‐friendliness. We developed panelcn.MOPS, a novel pipeline for detecting CNVs in targeted NGS panel data. Using data from 180 samples, we compared panelcn.MOPS with five state‐of‐the‐art methods. With panelcn.MOPS leading the field, most methods achieved comparably high accuracy. panelcn.MOPS reliably detected CNVs ranging in size from part of a region of interest (ROI), to whole genes, which may comprise all ROIs investigated in a given sample. The latter is enabled by analyzing reads from all ROIs of the panel, but presenting results exclusively for user‐selected genes, thus avoiding incidental findings. Additionally, panelcn.MOPS offers QC criteria not only for samples, but also for individual ROIs within a sample, which increases the confidence in called CNVs. panelcn.MOPS is freely available both as R package and standalone software with graphical user interface that is easy to use for clinical geneticists without any programming experience. panelcn.MOPS combines high sensitivity and specificity with user‐friendliness rendering it highly suitable for routine clinical diagnostics. PMID:28449315

  7. LWIR hyperspectral change detection for target acquisition and situation awareness in urban areas

    NASA Astrophysics Data System (ADS)

    Dekker, Rob J.; Schwering, Piet B. W.; Benoist, Koen W.; Pignatti, Stefano; Santini, Federico; Friman, Ola

    2013-05-01

    This paper studies change detection of LWIR (Long Wave Infrared) hyperspectral imagery. Goal is to improve target acquisition and situation awareness in urban areas with respect to conventional techniques. Hyperspectral and conventional broadband high-spatial-resolution data were collected during the DUCAS trials in Zeebrugge, Belgium, in June 2011. LWIR data were acquired using the ITRES Thermal Airborne Spectrographic Imager TASI-600 that operates in the spectral range of 8.0-11.5 μm (32 band configuration). Broadband data were acquired using two aeroplanemounted FLIR SC7000 MWIR cameras. Acquisition of the images was around noon. To limit the number of false alarms due to atmospheric changes, the time interval between the images is less than 2 hours. Local co-registration adjustment was applied to compensate for misregistration errors in the order of a few pixels. The targets in the data that will be analysed in this paper are different kinds of vehicles. Change detection algorithms that were applied and evaluated are Euclidean distance, Mahalanobis distance, Chronochrome (CC), Covariance Equalisation (CE), and Hyperbolic Anomalous Change Detection (HACD). Based on Receiver Operating Characteristics (ROC) we conclude that LWIR hyperspectral has an advantage over MWIR broadband change detection. The best hyperspectral detector is HACD because it is most robust to noise. MWIR high spatial-resolution broadband results show that it helps to apply a false alarm reduction strategy based on spatial processing.

  8. Detection of Sub-fM DNA with Target Recycling and Self-Assembly Amplification on Graphene Field-Effect Biosensors

    PubMed Central

    2018-01-01

    All-electronic DNA biosensors based on graphene field-effect transistors (GFETs) offer the prospect of simple and cost-effective diagnostics. For GFET sensors based on complementary probe DNA, the sensitivity is limited by the binding affinity of the target oligonucleotide, in the nM range for 20 mer targets. We report a ∼20 000× improvement in sensitivity through the use of engineered hairpin probe DNA that allows for target recycling and hybridization chain reaction. This enables detection of 21 mer target DNA at sub-fM concentration and provides superior specificity against single-base mismatched oligomers. The work is based on a scalable fabrication process for biosensor arrays that is suitable for multiplexed detection. This approach overcomes the binding-affinity-dependent sensitivity of nucleic acid biosensors and offers a pathway toward multiplexed and label-free nucleic acid testing with high accuracy and selectivity. PMID:29768011

  9. Detection of Sub-fM DNA with Target Recycling and Self-Assembly Amplification on Graphene Field-Effect Biosensors.

    PubMed

    Gao, Zhaoli; Xia, Han; Zauberman, Jonathan; Tomaiuolo, Maurizio; Ping, Jinglei; Zhang, Qicheng; Ducos, Pedro; Ye, Huacheng; Wang, Sheng; Yang, Xinping; Lubna, Fahmida; Luo, Zhengtang; Ren, Li; Johnson, Alan T Charlie

    2018-06-13

    All-electronic DNA biosensors based on graphene field-effect transistors (GFETs) offer the prospect of simple and cost-effective diagnostics. For GFET sensors based on complementary probe DNA, the sensitivity is limited by the binding affinity of the target oligonucleotide, in the nM range for 20 mer targets. We report a ∼20 000× improvement in sensitivity through the use of engineered hairpin probe DNA that allows for target recycling and hybridization chain reaction. This enables detection of 21 mer target DNA at sub-fM concentration and provides superior specificity against single-base mismatched oligomers. The work is based on a scalable fabrication process for biosensor arrays that is suitable for multiplexed detection. This approach overcomes the binding-affinity-dependent sensitivity of nucleic acid biosensors and offers a pathway toward multiplexed and label-free nucleic acid testing with high accuracy and selectivity.

  10. Quantitative subpixel spectral detection of targets in multispectral images. [terrestrial and planetary surfaces

    NASA Technical Reports Server (NTRS)

    Sabol, Donald E., Jr.; Adams, John B.; Smith, Milton O.

    1992-01-01

    The conditions that affect the spectral detection of target materials at the subpixel scale are examined. Two levels of spectral mixture analysis for determining threshold detection limits of target materials in a spectral mixture are presented, the cases where the target is detected as: (1) a component of a spectral mixture (continuum threshold analysis) and (2) residuals (residual threshold analysis). The results of these two analyses are compared under various measurement conditions. The examples illustrate the general approach that can be used for evaluating the spectral detectability of terrestrial and planetary targets at the subpixel scale.

  11. A particle filter for multi-target tracking in track before detect context

    NASA Astrophysics Data System (ADS)

    Amrouche, Naima; Khenchaf, Ali; Berkani, Daoud

    2016-10-01

    The track-before-detect (TBD) approach can be used to track a single target in a highly noisy radar scene. This is because it makes use of unthresholded observations and incorporates a binary target existence variable into its target state estimation process when implemented as a particle filter (PF). This paper proposes the recursive PF-TBD approach to detect multiple targets in low-signal-to noise ratios (SNR). The algorithm's successful performance is demonstrated using a simulated two target example.

  12. Stochastic performance modeling and evaluation of obstacle detectability with imaging range sensors

    NASA Technical Reports Server (NTRS)

    Matthies, Larry; Grandjean, Pierrick

    1993-01-01

    Statistical modeling and evaluation of the performance of obstacle detection systems for Unmanned Ground Vehicles (UGVs) is essential for the design, evaluation, and comparison of sensor systems. In this report, we address this issue for imaging range sensors by dividing the evaluation problem into two levels: quality of the range data itself and quality of the obstacle detection algorithms applied to the range data. We review existing models of the quality of range data from stereo vision and AM-CW LADAR, then use these to derive a new model for the quality of a simple obstacle detection algorithm. This model predicts the probability of detecting obstacles and the probability of false alarms, as a function of the size and distance of the obstacle, the resolution of the sensor, and the level of noise in the range data. We evaluate these models experimentally using range data from stereo image pairs of a gravel road with known obstacles at several distances. The results show that the approach is a promising tool for predicting and evaluating the performance of obstacle detection with imaging range sensors.

  13. Space moving target detection and tracking method in complex background

    NASA Astrophysics Data System (ADS)

    Lv, Ping-Yue; Sun, Sheng-Li; Lin, Chang-Qing; Liu, Gao-Rui

    2018-06-01

    The background of the space-borne detectors in real space-based environment is extremely complex and the signal-to-clutter ratio is very low (SCR ≈ 1), which increases the difficulty for detecting space moving targets. In order to solve this problem, an algorithm combining background suppression processing based on two-dimensional least mean square filter (TDLMS) and target enhancement based on neighborhood gray-scale difference (GSD) is proposed in this paper. The latter can filter out most of the residual background clutter processed by the former such as cloud edge. Through this procedure, both global and local SCR have obtained substantial improvement, indicating that the target has been greatly enhanced. After removing the detector's inherent clutter region through connected domain processing, the image only contains the target point and the isolated noise, in which the isolated noise could be filtered out effectively through multi-frame association. The proposed algorithm in this paper has been compared with some state-of-the-art algorithms for moving target detection and tracking tasks. The experimental results show that the performance of this algorithm is the best in terms of SCR gain, background suppression factor (BSF) and detection results.

  14. Differential Sources for 2 Neural Signatures of Target Detection: An Electrocorticography Study.

    PubMed

    Kam, J W Y; Szczepanski, S M; Canolty, R T; Flinker, A; Auguste, K I; Crone, N E; Kirsch, H E; Kuperman, R A; Lin, J J; Parvizi, J; Knight, R T

    2018-01-01

    Electrophysiology and neuroimaging provide conflicting evidence for the neural contributions to target detection. Scalp electroencephalography (EEG) studies localize the P3b event-related potential component mainly to parietal cortex, whereas neuroimaging studies report activations in both frontal and parietal cortices. We addressed this discrepancy by examining the sources that generate the target-detection process using electrocorticography (ECoG). We recorded ECoG activity from cortex in 14 patients undergoing epilepsy monitoring, as they performed an auditory or visual target-detection task. We examined target-related responses in 2 domains: high frequency band (HFB) activity and the P3b. Across tasks, we observed a greater proportion of electrodes that showed target-specific HFB power relative to P3b over frontal cortex, but their proportions over parietal cortex were comparable. Notably, there was minimal overlap in the electrodes that showed target-specific HFB and P3b activity. These results revealed that the target-detection process is characterized by at least 2 different neural markers with distinct cortical distributions. Our findings suggest that separate neural mechanisms are driving the differential patterns of activity observed in scalp EEG and neuroimaging studies, with the P3b reflecting EEG findings and HFB activity reflecting neuroimaging findings, highlighting the notion that target detection is not a unitary phenomenon. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  15. Research on Aircraft Target Detection Algorithm Based on Improved Radial Gradient Transformation

    NASA Astrophysics Data System (ADS)

    Zhao, Z. M.; Gao, X. M.; Jiang, D. N.; Zhang, Y. Q.

    2018-04-01

    Aiming at the problem that the target may have different orientation in the unmanned aerial vehicle (UAV) image, the target detection algorithm based on the rotation invariant feature is studied, and this paper proposes a method of RIFF (Rotation-Invariant Fast Features) based on look up table and polar coordinate acceleration to be used for aircraft target detection. The experiment shows that the detection performance of this method is basically equal to the RIFF, and the operation efficiency is greatly improved.

  16. Joint detection and tracking of size-varying infrared targets based on block-wise sparse decomposition

    NASA Astrophysics Data System (ADS)

    Li, Miao; Lin, Zaiping; Long, Yunli; An, Wei; Zhou, Yiyu

    2016-05-01

    The high variability of target size makes small target detection in Infrared Search and Track (IRST) a challenging task. A joint detection and tracking method based on block-wise sparse decomposition is proposed to address this problem. For detection, the infrared image is divided into overlapped blocks, and each block is weighted on the local image complexity and target existence probabilities. Target-background decomposition is solved by block-wise inexact augmented Lagrange multipliers. For tracking, label multi-Bernoulli (LMB) tracker tracks multiple targets taking the result of single-frame detection as input, and provides corresponding target existence probabilities for detection. Unlike fixed-size methods, the proposed method can accommodate size-varying targets, due to no special assumption for the size and shape of small targets. Because of exact decomposition, classical target measurements are extended and additional direction information is provided to improve tracking performance. The experimental results show that the proposed method can effectively suppress background clutters, detect and track size-varying targets in infrared images.

  17. Optimal Target Range of Closed-Loop Inspired Oxygen Support in Preterm Infants: A Randomized Cross-Over Study.

    PubMed

    van den Heuvel, Maria Elisabeth Nicoletta; van Zanten, Henriette A; Bachman, Tom E; Te Pas, Arjan B; van Kaam, Anton H; Onland, Wes

    2018-06-01

    To investigate the effect of different pulse oximetry (SpO 2 ) target range settings during automated fraction of inspired oxygen control (A-FiO 2 ) on time spent within a clinically set SpO 2 alarm range in oxygen-dependent infants on noninvasive respiratory support. Forty-one preterm infants (gestational age [median] 26 weeks, age [median] 21 days) on FiO 2  >0.21 receiving noninvasive respiratory support were subjected to A-FiO 2 using 3 SpO 2 target ranges (86%-94%, 88%-92%, or 89%-91%) in random order for 24 hours each. Before switching to the next target range, SpO 2 was manually controlled for 24 hours (washout period). The primary outcome was the time spent within the clinically set alarm limits of 86%-94%. The percent time within the 86%-94% SpO 2 alarm range was similar for all 3 A-FiO 2 target ranges (74%). Time spent in hyperoxemia was not significantly different between target ranges. However, the time spent in severe hypoxemia (SpO 2  <80%) was significantly reduced during the narrowed target ranges of A-FiO 2 (88%-92%; 1.9%, 89%-91%; 1.7%) compared with the wide target range (86%-94%; 3.4%, P < .001). There were no differences between the 88%-92% and 89-91% target range. Narrowing the target range of A-FiO 2 to the desired median ±2% is effective in reducing the time spent in hypoxemia, without increasing the risk of hyperoxemia. www.trialregister.nl: NTR4368. Copyright © 2018 Elsevier Inc. All rights reserved.

  18. Detection and tracking of a moving target using SAR images with the particle filter-based track-before-detect algorithm.

    PubMed

    Gao, Han; Li, Jingwen

    2014-06-19

    A novel approach to detecting and tracking a moving target using synthetic aperture radar (SAR) images is proposed in this paper. Achieved with the particle filter (PF) based track-before-detect (TBD) algorithm, the approach is capable of detecting and tracking the low signal-to-noise ratio (SNR) moving target with SAR systems, which the traditional track-after-detect (TAD) approach is inadequate for. By incorporating the signal model of the SAR moving target into the algorithm, the ambiguity in target azimuth position and radial velocity is resolved while tracking, which leads directly to the true estimation. With the sub-area substituted for the whole area to calculate the likelihood ratio and a pertinent choice of the number of particles, the computational efficiency is improved with little loss in the detection and tracking performance. The feasibility of the approach is validated and the performance is evaluated with Monte Carlo trials. It is demonstrated that the proposed approach is capable to detect and track a moving target with SNR as low as 7 dB, and outperforms the traditional TAD approach when the SNR is below 14 dB.

  19. Detection and Tracking of a Moving Target Using SAR Images with the Particle Filter-Based Track-Before-Detect Algorithm

    PubMed Central

    Gao, Han; Li, Jingwen

    2014-01-01

    A novel approach to detecting and tracking a moving target using synthetic aperture radar (SAR) images is proposed in this paper. Achieved with the particle filter (PF) based track-before-detect (TBD) algorithm, the approach is capable of detecting and tracking the low signal-to-noise ratio (SNR) moving target with SAR systems, which the traditional track-after-detect (TAD) approach is inadequate for. By incorporating the signal model of the SAR moving target into the algorithm, the ambiguity in target azimuth position and radial velocity is resolved while tracking, which leads directly to the true estimation. With the sub-area substituted for the whole area to calculate the likelihood ratio and a pertinent choice of the number of particles, the computational efficiency is improved with little loss in the detection and tracking performance. The feasibility of the approach is validated and the performance is evaluated with Monte Carlo trials. It is demonstrated that the proposed approach is capable to detect and track a moving target with SNR as low as 7 dB, and outperforms the traditional TAD approach when the SNR is below 14 dB. PMID:24949640

  20. Demonstrator Detection System for the Active Target and Time Projection Chamber (ACTAR TPC) project

    NASA Astrophysics Data System (ADS)

    Roger, T.; Pancin, J.; Grinyer, G. F.; Mauss, B.; Laffoley, A. T.; Rosier, P.; Alvarez-Pol, H.; Babo, M.; Blank, B.; Caamaño, M.; Ceruti, S.; Daemen, J.; Damoy, S.; Duclos, B.; Fernández-Domínguez, B.; Flavigny, F.; Giovinazzo, J.; Goigoux, T.; Henares, J. L.; Konczykowski, P.; Marchi, T.; Lebertre, G.; Lecesne, N.; Legeard, L.; Maugeais, C.; Minier, G.; Osmond, B.; Pedroza, J. L.; Pibernat, J.; Poleshchuk, O.; Pollacco, E. C.; Raabe, R.; Raine, B.; Renzi, F.; Saillant, F.; Sénécal, P.; Sizun, P.; Suzuki, D.; Swartz, J. A.; Wouters, C.; Wittwer, G.; Yang, J. C.

    2018-07-01

    The design, realization and operation of a prototype or "demonstrator" version of an active target and time projection chamber (ACTAR TPC) for experiments in nuclear physics is presented in detail. The heart of the detection system features a MICROMEGAS gas amplifier coupled to a high-density pixelated pad plane with square pad sizes of 2 × 2 mm2. The detector has been thoroughly tested with several different gas mixtures over a wide range of pressures and using a variety of sources of ionizing radiation including laser light, an α-particle source and heavy-ion beams of 24Mg and 58Ni accelerated to energies of 4.0 MeV/u. Results from these tests and characterization of the detector response over a wide range of operating conditions will be described. These developments have served as the basis for the design of a larger detection system that is presently under construction.

  1. Sea-Based Infrared Scene Interpretation by Background Type Classification and Coastal Region Detection for Small Target Detection

    PubMed Central

    Kim, Sungho

    2015-01-01

    Sea-based infrared search and track (IRST) is important for homeland security by detecting missiles and asymmetric boats. This paper proposes a novel scheme to interpret various infrared scenes by classifying the infrared background types and detecting the coastal regions in omni-directional images. The background type or region-selective small infrared target detector should be deployed to maximize the detection rate and to minimize the number of false alarms. A spatial filter-based small target detector is suitable for identifying stationary incoming targets in remote sea areas with sky only. Many false detections can occur if there is an image sector containing a coastal region, due to ground clutter and the difficulty in finding true targets using the same spatial filter-based detector. A temporal filter-based detector was used to handle these problems. Therefore, the scene type and coastal region information is critical to the success of IRST in real-world applications. In this paper, the infrared scene type was determined using the relationships between the sensor line-of-sight (LOS) and a horizontal line in an image. The proposed coastal region detector can be activated if the background type of the probing sector is determined to be a coastal region. Coastal regions can be detected by fusing the region map and curve map. The experimental results on real infrared images highlight the feasibility of the proposed sea-based scene interpretation. In addition, the effects of the proposed scheme were analyzed further by applying region-adaptive small target detection. PMID:26404308

  2. Tensor Fukunaga-Koontz transform for small target detection in infrared images

    NASA Astrophysics Data System (ADS)

    Liu, Ruiming; Wang, Jingzhuo; Yang, Huizhen; Gong, Chenglong; Zhou, Yuanshen; Liu, Lipeng; Zhang, Zhen; Shen, Shuli

    2016-09-01

    Infrared small targets detection plays a crucial role in warning and tracking systems. Some novel methods based on pattern recognition technology catch much attention from researchers. However, those classic methods must reshape images into vectors with the high dimensionality. Moreover, vectorizing breaks the natural structure and correlations in the image data. Image representation based on tensor treats images as matrices and can hold the natural structure and correlation information. So tensor algorithms have better classification performance than vector algorithms. Fukunaga-Koontz transform is one of classification algorithms and it is a vector version method with the disadvantage of all vector algorithms. In this paper, we first extended the Fukunaga-Koontz transform into its tensor version, tensor Fukunaga-Koontz transform. Then we designed a method based on tensor Fukunaga-Koontz transform for detecting targets and used it to detect small targets in infrared images. The experimental results, comparison through signal-to-clutter, signal-to-clutter gain and background suppression factor, have validated the advantage of the target detection based on the tensor Fukunaga-Koontz transform over that based on the Fukunaga-Koontz transform.

  3. Statistical-Mechanics-Inspired Optimization of Sensor Field Configuration for Detection of Mobile Targets (PREPRINT)

    DTIC Science & Technology

    2010-11-01

    pected target motion. Along this line, Wettergren [5] analyzed the performance of the track - before - detect schemes for the sensor networks. Furthermore...dressed by Baumgartner and Ferrari [11] for the reorganization of the sensor field to achieve the maximum coverage. The track - before - detect -based optimal...confirming a target. In accordance with the track - before - detect paradigm [4], a moving target is detected if the kd (typically kd = 3 or 4) sensors detect

  4. Infrared moving small target detection based on saliency extraction and image sparse representation

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaomin; Ren, Kan; Gao, Jin; Li, Chaowei; Gu, Guohua; Wan, Minjie

    2016-10-01

    Moving small target detection in infrared image is a crucial technique of infrared search and tracking system. This paper present a novel small target detection technique based on frequency-domain saliency extraction and image sparse representation. First, we exploit the features of Fourier spectrum image and magnitude spectrum of Fourier transform to make a rough extract of saliency regions and use a threshold segmentation system to classify the regions which look salient from the background, which gives us a binary image as result. Second, a new patch-image model and over-complete dictionary were introduced to the detection system, then the infrared small target detection was converted into a problem solving and optimization process of patch-image information reconstruction based on sparse representation. More specifically, the test image and binary image can be decomposed into some image patches follow certain rules. We select the target potential area according to the binary patch-image which contains salient region information, then exploit the over-complete infrared small target dictionary to reconstruct the test image blocks which may contain targets. The coefficients of target image patch satisfy sparse features. Finally, for image sequence, Euclidean distance was used to reduce false alarm ratio and increase the detection accuracy of moving small targets in infrared images due to the target position correlation between frames.

  5. Point target detection utilizing super-resolution strategy for infrared scanning oversampling system

    NASA Astrophysics Data System (ADS)

    Wang, Longguang; Lin, Zaiping; Deng, Xinpu; An, Wei

    2017-11-01

    To improve the resolution of remote sensing infrared images, infrared scanning oversampling system is employed with information amount quadrupled, which contributes to the target detection. Generally the image data from double-line detector of infrared scanning oversampling system is shuffled to a whole oversampled image to be post-processed, whereas the aliasing between neighboring pixels leads to image degradation with a great impact on target detection. This paper formulates a point target detection method utilizing super-resolution (SR) strategy concerning infrared scanning oversampling system, with an accelerated SR strategy proposed to realize fast de-aliasing of the oversampled image and an adaptive MRF-based regularization designed to achieve the preserving and aggregation of target energy. Extensive experiments demonstrate the superior detection performance, robustness and efficiency of the proposed method compared with other state-of-the-art approaches.

  6. Decision-level fusion of SAR and IR sensor information for automatic target detection

    NASA Astrophysics Data System (ADS)

    Cho, Young-Rae; Yim, Sung-Hyuk; Cho, Hyun-Woong; Won, Jin-Ju; Song, Woo-Jin; Kim, So-Hyeon

    2017-05-01

    We propose a decision-level architecture that combines synthetic aperture radar (SAR) and an infrared (IR) sensor for automatic target detection. We present a new size-based feature, called target-silhouette to reduce the number of false alarms produced by the conventional target-detection algorithm. Boolean Map Visual Theory is used to combine a pair of SAR and IR images to generate the target-enhanced map. Then basic belief assignment is used to transform this map into a belief map. The detection results of sensors are combined to build the target-silhouette map. We integrate the fusion mass and the target-silhouette map on the decision level to exclude false alarms. The proposed algorithm is evaluated using a SAR and IR synthetic database generated by SE-WORKBENCH simulator, and compared with conventional algorithms. The proposed fusion scheme achieves higher detection rate and lower false alarm rate than the conventional algorithms.

  7. Detection of multiple airborne targets from multisensor data

    NASA Astrophysics Data System (ADS)

    Foltz, Mark A.; Srivastava, Anuj; Miller, Michael I.; Grenander, Ulf

    1995-08-01

    Previously we presented a jump-diffusion based random sampling algorithm for generating conditional mean estimates of scene representations for the tracking and recongition of maneuvering airborne targets. These representations include target positions and orientations along their trajectories and the target type associated with each trajectory. Taking a Bayesian approach, a posterior measure is defined on the parameter space by combining sensor models with a sophisticated prior based on nonlinear airplane dynamics. The jump-diffusion algorithm constructs a Markov process which visits the elements of the parameter space with frequencies proportional to the posterior probability. It consititutes both the infinitesimal, local search via a sample path continuous diffusion transform and the larger, global steps through discrete jump moves. The jump moves involve the addition and deletion of elements from the scene configuration or changes in the target type assoviated with each target trajectory. One such move results in target detection by the addition of a track seed to the inference set. This provides initial track data for the tracking/recognition algorithm to estimate linear graph structures representing tracks using the other jump moves and the diffusion process, as described in our earlier work. Target detection ideally involves a continuous research over a continuum of the observation space. In this work we conclude that for practical implemenations the search space must be discretized with lattice granularity comparable to sensor resolution, and discuss how fast Fourier transforms are utilized for efficient calcuation of sufficient statistics given our array models. Some results are also presented from our implementation on a networked system including a massively parallel machine architecture and a silicon graphics onyx workstation.

  8. Helicopter main-rotor speed effects: A comparison of predicted ranges of detection from the aural detection program ICHIN and the electronic detection program ARCAS

    NASA Technical Reports Server (NTRS)

    Mueller, Arnold W.; Smith, Charles D.

    1991-01-01

    NASA LaRC personnel have conducted a strudy of the predicted acoustic detection ranges associated with reduced helicopter main rotor speeds. This was accomplished by providing identical input information to both the aural detection program ICHIN 6, (I Can Hear It Now, version 6) and the electronic acoustic detection program ARCAS (Assessment of Rotorcraft Detection by Acoustics Sensing). In this study, it was concluded that reducing the main rotor speed of the helicopter by 27 percent reduced both the predicted aural and electronic detection ranges by approximately 50 percent. Additionally, ARCAS was observed to function better with narrowband spectral input than with one-third octave band spectral inputs and the predicted electronic range of acoustic detection is greater than the predicted aural detection range.

  9. A Parallel Finite Set Statistical Simulator for Multi-Target Detection and Tracking

    NASA Astrophysics Data System (ADS)

    Hussein, I.; MacMillan, R.

    2014-09-01

    Finite Set Statistics (FISST) is a powerful Bayesian inference tool for the joint detection, classification and tracking of multi-target environments. FISST is capable of handling phenomena such as clutter, misdetections, and target birth and decay. Implicit within the approach are solutions to the data association and target label-tracking problems. Finally, FISST provides generalized information measures that can be used for sensor allocation across different types of tasks such as: searching for new targets, and classification and tracking of known targets. These FISST capabilities have been demonstrated on several small-scale illustrative examples. However, for implementation in a large-scale system as in the Space Situational Awareness problem, these capabilities require a lot of computational power. In this paper, we implement FISST in a parallel environment for the joint detection and tracking of multi-target systems. In this implementation, false alarms and misdetections will be modeled. Target birth and decay will not be modeled in the present paper. We will demonstrate the success of the method for as many targets as we possibly can in a desktop parallel environment. Performance measures will include: number of targets in the simulation, certainty of detected target tracks, computational time as a function of clutter returns and number of targets, among other factors.

  10. High-resolution remotely sensed small target detection by imitating fly visual perception mechanism.

    PubMed

    Huang, Fengchen; Xu, Lizhong; Li, Min; Tang, Min

    2012-01-01

    The difficulty and limitation of small target detection methods for high-resolution remote sensing data have been a recent research hot spot. Inspired by the information capture and processing theory of fly visual system, this paper endeavors to construct a characterized model of information perception and make use of the advantages of fast and accurate small target detection under complex varied nature environment. The proposed model forms a theoretical basis of small target detection for high-resolution remote sensing data. After the comparison of prevailing simulation mechanism behind fly visual systems, we propose a fly-imitated visual system method of information processing for high-resolution remote sensing data. A small target detector and corresponding detection algorithm are designed by simulating the mechanism of information acquisition, compression, and fusion of fly visual system and the function of pool cell and the character of nonlinear self-adaption. Experiments verify the feasibility and rationality of the proposed small target detection model and fly-imitated visual perception method.

  11. RNase H-assisted RNA-primed rolling circle amplification for targeted RNA sequence detection.

    PubMed

    Takahashi, Hirokazu; Ohkawachi, Masahiko; Horio, Kyohei; Kobori, Toshiro; Aki, Tsunehiro; Matsumura, Yukihiko; Nakashimada, Yutaka; Okamura, Yoshiko

    2018-05-17

    RNA-primed rolling circle amplification (RPRCA) is a useful laboratory method for RNA detection; however, the detection of RNA is limited by the lack of information on 3'-terminal sequences. We uncovered that conventional RPRCA using pre-circularized probes could potentially detect the internal sequence of target RNA molecules in combination with RNase H. However, the specificity for mRNA detection was low, presumably due to non-specific hybridization of non-target RNA with the circular probe. To overcome this technical problem, we developed a method for detecting a sequence of interest in target RNA molecules via RNase H-assisted RPRCA using padlocked probes. When padlock probes are hybridized to the target RNA molecule, they are converted to the circular form by SplintR ligase. Subsequently, RNase H creates nick sites only in the hybridized RNA sequence, and single-stranded DNA is finally synthesized from the nick site by phi29 DNA polymerase. This method could specifically detect at least 10 fmol of the target RNA molecule without reverse transcription. Moreover, this method detected GFP mRNA present in 10 ng of total RNA isolated from Escherichia coli without background DNA amplification. Therefore, this method can potentially detect almost all types of RNA molecules without reverse transcription and reveal full-length sequence information.

  12. Computational optimisation of targeted DNA sequencing for cancer detection

    NASA Astrophysics Data System (ADS)

    Martinez, Pierre; McGranahan, Nicholas; Birkbak, Nicolai Juul; Gerlinger, Marco; Swanton, Charles

    2013-12-01

    Despite recent progress thanks to next-generation sequencing technologies, personalised cancer medicine is still hampered by intra-tumour heterogeneity and drug resistance. As most patients with advanced metastatic disease face poor survival, there is need to improve early diagnosis. Analysing circulating tumour DNA (ctDNA) might represent a non-invasive method to detect mutations in patients, facilitating early detection. In this article, we define reduced gene panels from publicly available datasets as a first step to assess and optimise the potential of targeted ctDNA scans for early tumour detection. Dividing 4,467 samples into one discovery and two independent validation cohorts, we show that up to 76% of 10 cancer types harbour at least one mutation in a panel of only 25 genes, with high sensitivity across most tumour types. Our analyses demonstrate that targeting ``hotspot'' regions would introduce biases towards in-frame mutations and would compromise the reproducibility of tumour detection.

  13. An electromagnetic induction method for underground target detection and characterization

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bartel, L.C.; Cress, D.H.

    1997-01-01

    An improved capability for subsurface structure detection is needed to support military and nonproliferation requirements for inspection and for surveillance of activities of threatening nations. As part of the DOE/NN-20 program to apply geophysical methods to detect and characterize underground facilities, Sandia National Laboratories (SNL) initiated an electromagnetic induction (EMI) project to evaluate low frequency electromagnetic (EM) techniques for subsurface structure detection. Low frequency, in this case, extended from kilohertz to hundreds of kilohertz. An EMI survey procedure had already been developed for borehole imaging of coal seams and had successfully been applied in a surface mode to detect amore » drug smuggling tunnel. The SNL project has focused on building upon the success of that procedure and applying it to surface and low altitude airborne platforms. Part of SNL`s work has focused on improving that technology through improved hardware and data processing. The improved hardware development has been performed utilizing Laboratory Directed Research and Development (LDRD) funding. In addition, SNL`s effort focused on: (1) improvements in modeling of the basic geophysics of the illuminating electromagnetic field and its coupling to the underground target (partially funded using LDRD funds) and (2) development of techniques for phase-based and multi-frequency processing and spatial processing to support subsurface target detection and characterization. The products of this project are: (1) an evaluation of an improved EM gradiometer, (2) an improved gradiometer concept for possible future development, (3) an improved modeling capability, (4) demonstration of an EM wave migration method for target recognition, and a demonstration that the technology is capable of detecting targets to depths exceeding 25 meters.« less

  14. Coherent and Noncoherent Joint Processing of Sonar for Detection of Small Targets in Shallow Water.

    PubMed

    Pan, Xiang; Jiang, Jingning; Li, Si; Ding, Zhenping; Pan, Chen; Gong, Xianyi

    2018-04-10

    A coherent-noncoherent joint processing framework is proposed for active sonar to combine diversity gain and beamforming gain for detection of a small target in shallow water environments. Sonar utilizes widely-spaced arrays to sense environments and illuminate a target of interest from multiple angles. Meanwhile, it exploits spatial diversity for time-reversal focusing to suppress reverberation, mainly strong bottom reverberation. For enhancement of robustness of time-reversal focusing, an adaptive iterative strategy is utilized in the processing framework. A probing signal is firstly transmitted and echoes of a likely target are utilized as steering vectors for the second transmission. With spatial diversity, target bearing and range are estimated using a broadband signal model. Numerical simulations show that the novel sonar outperforms the traditional phased-array sonar due to benefits of spatial diversity. The effectiveness of the proposed framework has been validated by localization of a small target in at-lake experiments.

  15. Coherent and Noncoherent Joint Processing of Sonar for Detection of Small Targets in Shallow Water

    PubMed Central

    Jiang, Jingning; Li, Si; Ding, Zhenping; Pan, Chen; Gong, Xianyi

    2018-01-01

    A coherent-noncoherent joint processing framework is proposed for active sonar to combine diversity gain and beamforming gain for detection of a small target in shallow water environments. Sonar utilizes widely-spaced arrays to sense environments and illuminate a target of interest from multiple angles. Meanwhile, it exploits spatial diversity for time-reversal focusing to suppress reverberation, mainly strong bottom reverberation. For enhancement of robustness of time-reversal focusing, an adaptive iterative strategy is utilized in the processing framework. A probing signal is firstly transmitted and echoes of a likely target are utilized as steering vectors for the second transmission. With spatial diversity, target bearing and range are estimated using a broadband signal model. Numerical simulations show that the novel sonar outperforms the traditional phased-array sonar due to benefits of spatial diversity. The effectiveness of the proposed framework has been validated by localization of a small target in at-lake experiments. PMID:29642637

  16. Seasonal variability and detection range modeling of baleen whale calls in the Gulf of Alaska, 1999-2002.

    PubMed

    Stafford, Kathleen M; Mellinger, David K; Moore, Sue E; Fox, Christopher G

    2007-12-01

    Five species of large whales, including the blue (Balaenoptera musculus), fin (B. physalus), sei (B. borealis), humpback (Megaptera novaeangliae), and North Pacific right (Eubalaena japonica), were the target of commercial harvests in the Gulf of Alaska (GoA) during the 19th through mid-20th Centuries. Since this time, there have been a few summer time visual surveys for these species, but no overview of year-round use of these waters by endangered whales primarily because standard visual survey data are difficult and costly. From October 1999-May 2002, moored hydrophones were deployed in six locations in the GoA to record whale calls. Reception of calls from fin, humpback, and blue whales and an unknown source, called Watkins' whale, showed seasonal and geographic variation. Calls were detected more often during the winter than during the summer, suggesting that animals inhabit the GoA year-round. To estimate the distance at which species-diagnostic calls could be heard, parabolic equation propagation loss models for frequencies characteristic of each of each call type were run. Maximum detection ranges in the subarctic North Pacific ranged from 45 to 250 km among three species (fin, humpback, blue), although modeled detection ranges varied greatly with input parameters and choice of ambient noise level.

  17. Analysis of Infrared Signature Variation and Robust Filter-Based Supersonic Target Detection

    PubMed Central

    Sun, Sun-Gu; Kim, Kyung-Tae

    2014-01-01

    The difficulty of small infrared target detection originates from the variations of infrared signatures. This paper presents the fundamental physics of infrared target variations and reports the results of variation analysis of infrared images acquired using a long wave infrared camera over a 24-hour period for different types of backgrounds. The detection parameters, such as signal-to-clutter ratio were compared according to the recording time, temperature and humidity. Through variation analysis, robust target detection methodologies are derived by controlling thresholds and designing a temporal contrast filter to achieve high detection rate and low false alarm rate. Experimental results validate the robustness of the proposed scheme by applying it to the synthetic and real infrared sequences. PMID:24672290

  18. Moving target detection method based on improved Gaussian mixture model

    NASA Astrophysics Data System (ADS)

    Ma, J. Y.; Jie, F. R.; Hu, Y. J.

    2017-07-01

    Gaussian Mixture Model is often employed to build background model in background difference methods for moving target detection. This paper puts forward an adaptive moving target detection algorithm based on improved Gaussian Mixture Model. According to the graylevel convergence for each pixel, adaptively choose the number of Gaussian distribution to learn and update background model. Morphological reconstruction method is adopted to eliminate the shadow.. Experiment proved that the proposed method not only has good robustness and detection effect, but also has good adaptability. Even for the special cases when the grayscale changes greatly and so on, the proposed method can also make outstanding performance.

  19. Clinical Validation of Copy Number Variant Detection from Targeted Next-Generation Sequencing Panels.

    PubMed

    Kerkhof, Jennifer; Schenkel, Laila C; Reilly, Jack; McRobbie, Sheri; Aref-Eshghi, Erfan; Stuart, Alan; Rupar, C Anthony; Adams, Paul; Hegele, Robert A; Lin, Hanxin; Rodenhiser, David; Knoll, Joan; Ainsworth, Peter J; Sadikovic, Bekim

    2017-11-01

    Next-generation sequencing (NGS) technology has rapidly replaced Sanger sequencing in the assessment of sequence variations in clinical genetics laboratories. One major limitation of current NGS approaches is the ability to detect copy number variations (CNVs) approximately >50 bp. Because these represent a major mutational burden in many genetic disorders, parallel CNV assessment using alternate supplemental methods, along with the NGS analysis, is normally required, resulting in increased labor, costs, and turnaround times. The objective of this study was to clinically validate a novel CNV detection algorithm using targeted clinical NGS gene panel data. We have applied this approach in a retrospective cohort of 391 samples and a prospective cohort of 2375 samples and found a 100% sensitivity (95% CI, 89%-100%) for 37 unique events and a high degree of specificity to detect CNVs across nine distinct targeted NGS gene panels. This NGS CNV pipeline enables stand-alone first-tier assessment for CNV and sequence variants in a clinical laboratory setting, dispensing with the need for parallel CNV analysis using classic techniques, such as microarray, long-range PCR, or multiplex ligation-dependent probe amplification. This NGS CNV pipeline can also be applied to the assessment of complex genomic regions, including pseudogenic DNA sequences, such as the PMS2CL gene, and to mitochondrial genome heteroplasmy detection. Copyright © 2017 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

  20. Adaptive early detection ML/PDA estimator for LO targets with EO sensors

    NASA Astrophysics Data System (ADS)

    Chummun, Muhammad R.; Kirubarajan, Thiagalingam; Bar-Shalom, Yaakov

    2000-07-01

    The batch Maximum Likelihood Estimator, combined with Probabilistic Data (ML-PDA), has been shown to be effective in acquiring low observable (LO) - low SNR - non-maneuvering targets in the presence of heavy clutter. The use of signal strength or amplitude information (AI) in the ML-PDA estimator with AI in a sliding-window fashion, to detect high- speed targets in heavy clutter using electro-optical (EO) sensors. The initial time and the length of the sliding-window are adjusted adaptively according to the information content of the received measurements. A track validation scheme via hypothesis testing is developed to confirm the estimated track, that is, the presence of a target, in each window. The sliding-window ML-PDA approach, together with track validation, enables early detection by rejecting noninformative scans, target reacquisition in case of temporary target disappearance and the handling of targets with speeds evolving over time. The proposed algorithm is shown to detect the target, which is hidden in as many as 600 false alarms per scan, 10 frames earlier than the Multiple Hypothesis Tracking (MHT) algorithm.

  1. Research on infrared dim-point target detection and tracking under sea-sky-line complex background

    NASA Astrophysics Data System (ADS)

    Dong, Yu-xing; Li, Yan; Zhang, Hai-bo

    2011-08-01

    Target detection and tracking technology in infrared image is an important part of modern military defense system. Infrared dim-point targets detection and recognition under complex background is a difficulty and important strategic value and challenging research topic. The main objects that carrier-borne infrared vigilance system detected are sea-skimming aircrafts and missiles. Due to the characteristics of wide field of view of vigilance system, the target is usually under the sea clutter. Detection and recognition of the target will be taken great difficulties .There are some traditional point target detection algorithms, such as adaptive background prediction detecting method. When background has dispersion-decreasing structure, the traditional target detection algorithms would be more useful. But when the background has large gray gradient, such as sea-sky-line, sea waves etc .The bigger false-alarm rate will be taken in these local area .It could not obtain satisfactory results. Because dim-point target itself does not have obvious geometry or texture feature ,in our opinion , from the perspective of mathematics, the detection of dim-point targets in image is about singular function analysis .And from the perspective image processing analysis , the judgment of isolated singularity in the image is key problem. The foregoing points for dim-point targets detection, its essence is a separation of target and background of different singularity characteristics .The image from infrared sensor usually accompanied by different kinds of noise. These external noises could be caused by the complicated background or from the sensor itself. The noise might affect target detection and tracking. Therefore, the purpose of the image preprocessing is to reduce the effects from noise, also to raise the SNR of image, and to increase the contrast of target and background. According to the low sea-skimming infrared flying small target characteristics , the median filter is used to

  2. Passive Coherent Detection and Target Location with Multiple Non-Cooperative Transmitters

    DTIC Science & Technology

    2015-06-01

    to detect, separate, classify, locate, and track sources of emissions in multi-target environments—triggered the development of passive radar...radar capitalizes on transmitters of opportunity to detect and locate sources of transmission or targets without deliberate emissions . The...equipment as all necessary hardware is currently available on most naval ships. 3 Bistatic radar geometry. Figure 1. B. HISTORY The concept of

  3. Tumor detection and elimination by a targeted gallium corrole

    PubMed Central

    Agadjanian, Hasmik; Ma, Jun; Rentsendorj, Altan; Valluripalli, Vinod; Hwang, Jae Youn; Mahammed, Atif; Farkas, Daniel L.; Gray, Harry B.; Gross, Zeev; Medina-Kauwe, Lali K.

    2009-01-01

    Sulfonated gallium(III) corroles are intensely fluorescent macrocyclic compounds that spontaneously assemble with carrier proteins to undergo cell entry. We report in vivo imaging and therapeutic efficacy of a tumor-targeted corrole noncovalently assembled with a heregulin-modified protein directed at the human epidermal growth factor receptor (HER). Systemic delivery of this protein-corrole complex results in tumor accumulation, which can be visualized in vivo owing to intensely red corrole fluorescence. Targeted delivery in vivo leads to tumor cell death while normal tissue is spared. These findings contrast with the effects of doxorubicin, which can elicit cardiac damage during therapy and required direct intratumoral injection to yield similar levels of tumor shrinkage compared with the systemically delivered corrole. The targeted complex ablated tumors at >5 times a lower dose than untargeted systemic doxorubicin, and the corrole did not damage heart tissue. Complexes remained intact in serum and the carrier protein elicited no detectable immunogenicity. The sulfonated gallium(III) corrole functions both for tumor detection and intervention with safety and targeting advantages over standard chemotherapeutic agents. PMID:19342490

  4. Integrated long-range UAV/UGV collaborative target tracking

    NASA Astrophysics Data System (ADS)

    Moseley, Mark B.; Grocholsky, Benjamin P.; Cheung, Carol; Singh, Sanjiv

    2009-05-01

    Coordinated operations between unmanned air and ground assets allow leveraging of multi-domain sensing and increase opportunities for improving line of sight communications. While numerous military missions would benefit from coordinated UAV-UGV operations, foundational capabilities that integrate stove-piped tactical systems and share available sensor data are required and not yet available. iRobot, AeroVironment, and Carnegie Mellon University are working together, partially SBIR-funded through ARDEC's small unit network lethality initiative, to develop collaborative capabilities for surveillance, targeting, and improved communications based on PackBot UGV and Raven UAV platforms. We integrate newly available technologies into computational, vision, and communications payloads and develop sensing algorithms to support vision-based target tracking. We first simulated and then applied onto real tactical platforms an implementation of Decentralized Data Fusion, a novel technique for fusing track estimates from PackBot and Raven platforms for a moving target in an open environment. In addition, system integration with AeroVironment's Digital Data Link onto both air and ground platforms has extended our capabilities in communications range to operate the PackBot as well as in increased video and data throughput. The system is brought together through a unified Operator Control Unit (OCU) for the PackBot and Raven that provides simultaneous waypoint navigation and traditional teleoperation. We also present several recent capability accomplishments toward PackBot-Raven coordinated operations, including single OCU display design and operation, early target track results, and Digital Data Link integration efforts, as well as our near-term capability goals.

  5. Indoor detection of passive targets recast as an inverse scattering problem

    NASA Astrophysics Data System (ADS)

    Gottardi, G.; Moriyama, T.

    2017-10-01

    The wireless local area networks represent an alternative to custom sensors and dedicated surveillance systems for target indoor detection. The availability of the channel state information has opened the exploitation of the spatial and frequency diversity given by the orthogonal frequency division multiplexing. Such a fine-grained information can be used to solve the detection problem as an inverse scattering problem. The goal of the detection is to reconstruct the properties of the investigation domain, namely to estimate if the domain is empty or occupied by targets, starting from the measurement of the electromagnetic perturbation of the wireless channel. An innovative inversion strategy exploiting both the frequency and the spatial diversity of the channel state information is proposed. The target-dependent features are identified combining the Kruskal-Wallis test and the principal component analysis. The experimental validation points out the detection performance of the proposed method when applied to an existing wireless link of a WiFi architecture deployed in a real indoor scenario. False detection rates lower than 2 [%] have been obtained.

  6. Passive range estimation using dual baseline triangulation

    NASA Astrophysics Data System (ADS)

    Pieper, Ronald J.; Cooper, Alfred W.; Pelegris, G.

    1996-03-01

    Modern combat systems based on active radar sensing suffer disadvantages against low-flying targets in cluttered backgrounds. Use of passive infrared sensors with these systems, either in cooperation or as an alternative, shows potential for improving target detection and declaration range for targets crossing the horizon. Realization of this potential requires fusion of target position data from dissimilar sensors, or passive sensor measurement of target range. The availability of passive sensors that can supply both range and bearing data on such targets would significantly extend the robustness of an integrated ship self-defense system. This paper considers a new method of range determination with passive sensors based on the principle of triangulation, extending the principle to two orthogonal baselines. The performance of single or double baseline triangulation depends on sensor bearing precision and direction to target. An expression for maximum triangulation range at a required accuracy is derived as a function of polar angle relative to the center of the dual-baseline system. Limitations in the dual- baseline model due to the geometrically assessed horizon are also considered.

  7. Hierarchical effects on target detection and conflict monitoring

    PubMed Central

    Cao, Bihua; Gao, Feng; Ren, Maofang; Li, Fuhong

    2016-01-01

    Previous neuroimaging studies have demonstrated a hierarchical functional structure of the frontal cortices of the human brain, but the temporal course and the electrophysiological signature of the hierarchical representation remains unaddressed. In the present study, twenty-one volunteers were asked to perform a nested cue-target task, while their scalp potentials were recorded. The results showed that: (1) in comparison with the lower-level hierarchical targets, the higher-level targets elicited a larger N2 component (220–350 ms) at the frontal sites, and a smaller P3 component (350–500 ms) across the frontal and parietal sites; (2) conflict-related negativity (non-target minus target) was greater for the lower-level hierarchy than the higher-level, reflecting a more intensive process of conflict monitoring at the final step of target detection. These results imply that decision making, context updating, and conflict monitoring differ among different hierarchical levels of abstraction. PMID:27561989

  8. Targets Mask U-Net for Wind Turbines Detection in Remote Sensing Images

    NASA Astrophysics Data System (ADS)

    Han, M.; Wang, H.; Wang, G.; Liu, Y.

    2018-04-01

    To detect wind turbines precisely and quickly in very high resolution remote sensing images (VHRRSI) we propose target mask U-Net. This convolution neural network (CNN), which is carefully designed to be a wide-field detector, models the pixel class assignment to wind turbines and their context information. The shadow, which is the context information of the target in this study, has been regarded as part of a wind turbine instance. We have trained the target mask U-Net on training dataset, which is composed of down sampled image blocks and instance mask blocks. Some post-processes have been integrated to eliminate wrong spots and produce bounding boxes of wind turbine instances. The evaluation metrics prove the reliability and effectiveness of our method for the average F1-score of our detection method is up to 0.97. The comparison of detection accuracy and time consuming with the weakly supervised targets detection method based on CNN illustrates the superiority of our method.

  9. Generic detection of poleroviruses using an RT-PCR assay targeting the RdRp coding sequence.

    PubMed

    Lotos, Leonidas; Efthimiou, Konstantinos; Maliogka, Varvara I; Katis, Nikolaos I

    2014-03-01

    In this study a two-step RT-PCR assay was developed for the generic detection of poleroviruses. The RdRp coding region was selected as the primers' target, since it differs significantly from that of other members in the family Luteoviridae and its sequence can be more informative than other regions in the viral genome. Species specific RT-PCR assays targeting the same region were also developed for the detection of the six most widespread poleroviral species (Beet mild yellowing virus, Beet western yellows virus, Cucurbit aphid-borne virus, Carrot red leaf virus, Potato leafroll virus and Turnip yellows virus) in Greece and the collection of isolates. These isolates along with other characterized ones were used for the evaluation of the generic PCR's detection range. The developed assay efficiently amplified a 593bp RdRp fragment from 46 isolates of 10 different Polerovirus species. Phylogenetic analysis using the generic PCR's amplicon sequence showed that although it cannot accurately infer evolutionary relationships within the genus it can differentiate poleroviruses at the species level. Overall, the described generic assay could be applied for the reliable detection of Polerovirus infections and, in combination with the specific PCRs, for the identification of new and uncharacterized species in the genus. Copyright © 2013 Elsevier B.V. All rights reserved.

  10. High dynamic range electric field sensor for electromagnetic pulse detection.

    PubMed

    Lin, Che-Yun; Wang, Alan X; Lee, Beom Suk; Zhang, Xingyu; Chen, Ray T

    2011-08-29

    We design a high dynamic range electric field sensor based on domain inverted electro-optic (E-O) polymer Y-fed directional coupler for electromagnetic wave detection. This electrode-less, all optical, wideband electrical field sensor is fabricated using standard processing for E-O polymer photonic devices. Experimental results demonstrate effective detection of electric field from 16.7V/m to 750KV/m at a frequency of 1GHz, and spurious free measurement range of 70dB.

  11. Camouflaged target detection based on polarized spectral features

    NASA Astrophysics Data System (ADS)

    Tan, Jian; Zhang, Junping; Zou, Bin

    2016-05-01

    The polarized hyperspectral images (PHSI) include polarization, spectral, spatial and radiant features, which provide more information about objects and scenes than traditional intensity or spectrum ones. And polarization can suppress the background and highlight the object, leading to the high potential to improve camouflaged target detection. So polarized hyperspectral imaging technique has aroused extensive concern in the last few years. Nowadays, the detection methods are still not very mature, most of which are rooted in the detection of hyperspectral image. And before using these algorithms, Stokes vector is used to process the original four-dimensional polarized hyperspectral data firstly. However, when the data is large and complex, the amount of calculation and error will increase. In this paper, tensor is applied to reconstruct the original four-dimensional data into new three-dimensional data, then, the constraint energy minimization (CEM) is used to process the new data, which adds the polarization information to construct the polarized spectral filter operator and takes full advantages of spectral and polarized information. This way deals with the original data without extracting the Stokes vector, so as to reduce the computation and error greatly. The experimental results also show that the proposed method in this paper is more suitable for the target detection of the PHSI.

  12. An Underwater Target Detection System for Electro-Optical Imagery Data

    DTIC Science & Technology

    2010-06-01

    detection and segmentation of underwater mine-like objects in the EO images captured with a CCD-based image sensor. The main focus of this research is to...develop a robust detection algorithm that can be used to detect low contrast and partial underwater objects from the EO imagery with low false alarm rate...underwater target detection I. INTRODUCTION Automatic detection and recognition of underwater objects from EO imagery poses a serious challenge due to poor

  13. Salient target detection based on pseudo-Wigner-Ville distribution and Rényi entropy.

    PubMed

    Xu, Yuannan; Zhao, Yuan; Jin, Chenfei; Qu, Zengfeng; Liu, Liping; Sun, Xiudong

    2010-02-15

    We present what we believe to be a novel method based on pseudo-Wigner-Ville distribution (PWVD) and Rényi entropy for salient targets detection. In the foundation of studying the statistical property of Rényi entropy via PWVD, the residual entropy-based saliency map of an input image can be obtained. From the saliency map, target detection is completed by the simple and convenient threshold segmentation. Experimental results demonstrate the proposed method can detect targets effectively in complex ground scenes.

  14. A novel scattering switch-on detection technique for target-induced plasmon-coupling based sensing by single-particle optical anisotropy imaging.

    PubMed

    Peng, Lan; Cao, Xuan; Xiong, Bin; He, Yan; Yeung, Edward S

    2016-06-18

    We reported a novel scattering switch-on detection technique using flash-lamp polarization darkfield microscopy (FLPDM) for target-induced plasmon-coupling based sensing in homogeneous solution. With this method, we demonstrated sub-nM sensitivity for hydrogen sulfide (H2S) detection over a dynamic range of five orders of magnitude. This robust technique holds great promise for applications in toxic environmental pollutants and biological molecules.

  15. Laser Imaging Detection and Ranging Performance in a High-Fidelity Lunar Terrain Field

    NASA Technical Reports Server (NTRS)

    Chuang, Jason

    2015-01-01

    The prime objective of this project is to evaluate Laser Imaging Detection and Ranging (LIDAR) systems and compare their performance for hazard avoidance when tested at the NASA Marshall Space Flight Center's (MSFC's) lunar high-fidelity terrain field (see fig. 1). Hazard avoidance is the ability to avoid boulders, holes, or slopes that would jeopardize a safe landing and the deployment of scientific payloads. This capability is critical for any sample return mission intending to land in challenging terrain. Since challenging terrain is frequently where the most scientifically attractive targets are, hazard avoidance will be among the highest priorities for future robotic exploration missions. The maturation of hazard avoidance sensing addressed in this project directly supports the MSFC Tier I priority of sample return.

  16. Matched Filter Stochastic Background Characterization for Hyperspectral Target Detection

    DTIC Science & Technology

    2005-09-30

    and Pre- Clustering MVN Test.....................126 4.2.3 Pre- Clustering Detection Results.................................................130...4.2.4 Pre- Clustering Target Influence..................................................134 4.2.5 Statistical Distance Exclusion and Low Contrast...al, 2001] Figure 2.7 ROC Curve Comparison of RX, K-Means, and Bayesian Pre- Clustering Applied to Anomaly Detection [Ashton, 1998] Figure 2.8 ROC

  17. MutScan: fast detection and visualization of target mutations by scanning FASTQ data.

    PubMed

    Chen, Shifu; Huang, Tanxiao; Wen, Tiexiang; Li, Hong; Xu, Mingyan; Gu, Jia

    2018-01-22

    Some types of clinical genetic tests, such as cancer testing using circulating tumor DNA (ctDNA), require sensitive detection of known target mutations. However, conventional next-generation sequencing (NGS) data analysis pipelines typically involve different steps of filtering, which may cause miss-detection of key mutations with low frequencies. Variant validation is also indicated for key mutations detected by bioinformatics pipelines. Typically, this process can be executed using alignment visualization tools such as IGV or GenomeBrowse. However, these tools are too heavy and therefore unsuitable for validating mutations in ultra-deep sequencing data. We developed MutScan to address problems of sensitive detection and efficient validation for target mutations. MutScan involves highly optimized string-searching algorithms, which can scan input FASTQ files to grab all reads that support target mutations. The collected supporting reads for each target mutation will be piled up and visualized using web technologies such as HTML and JavaScript. Algorithms such as rolling hash and bloom filter are applied to accelerate scanning and make MutScan applicable to detect or visualize target mutations in a very fast way. MutScan is a tool for the detection and visualization of target mutations by only scanning FASTQ raw data directly. Compared to conventional pipelines, this offers a very high performance, executing about 20 times faster, and offering maximal sensitivity since it can grab mutations with even one single supporting read. MutScan visualizes detected mutations by generating interactive pile-ups using web technologies. These can serve to validate target mutations, thus avoiding false positives. Furthermore, MutScan can visualize all mutation records in a VCF file to HTML pages for cloud-friendly VCF validation. MutScan is an open source tool available at GitHub: https://github.com/OpenGene/MutScan.

  18. A Camera-Based Target Detection and Positioning UAV System for Search and Rescue (SAR) Purposes

    PubMed Central

    Sun, Jingxuan; Li, Boyang; Jiang, Yifan; Wen, Chih-yung

    2016-01-01

    Wilderness search and rescue entails performing a wide-range of work in complex environments and large regions. Given the concerns inherent in large regions due to limited rescue distribution, unmanned aerial vehicle (UAV)-based frameworks are a promising platform for providing aerial imaging. In recent years, technological advances in areas such as micro-technology, sensors and navigation have influenced the various applications of UAVs. In this study, an all-in-one camera-based target detection and positioning system is developed and integrated into a fully autonomous fixed-wing UAV. The system presented in this paper is capable of on-board, real-time target identification, post-target identification and location and aerial image collection for further mapping applications. Its performance is examined using several simulated search and rescue missions, and the test results demonstrate its reliability and efficiency. PMID:27792156

  19. A Camera-Based Target Detection and Positioning UAV System for Search and Rescue (SAR) Purposes.

    PubMed

    Sun, Jingxuan; Li, Boyang; Jiang, Yifan; Wen, Chih-Yung

    2016-10-25

    Wilderness search and rescue entails performing a wide-range of work in complex environments and large regions. Given the concerns inherent in large regions due to limited rescue distribution, unmanned aerial vehicle (UAV)-based frameworks are a promising platform for providing aerial imaging. In recent years, technological advances in areas such as micro-technology, sensors and navigation have influenced the various applications of UAVs. In this study, an all-in-one camera-based target detection and positioning system is developed and integrated into a fully autonomous fixed-wing UAV. The system presented in this paper is capable of on-board, real-time target identification, post-target identification and location and aerial image collection for further mapping applications. Its performance is examined using several simulated search and rescue missions, and the test results demonstrate its reliability and efficiency.

  20. Helmet-mounted displays in long-range-target visual acquisition

    NASA Astrophysics Data System (ADS)

    Wilkins, Donald F.

    1999-07-01

    Aircrews have always sought a tactical advantage within the visual range (WVR) arena -- usually defined as 'see the opponent first.' Even with radar and interrogation foe/friend (IFF) systems, the pilot who visually acquires his opponent first has a significant advantage. The Helmet Mounted Cueing System (HMCS) equipped with a camera offers an opportunity to correct the problems with the previous approaches. By utilizing real-time image enhancement technique and feeding the image to the pilot on the HMD, the target can be visually acquired well beyond the range provided by the unaided eye. This paper will explore the camera and display requirements for such a system and place those requirements within the context of other requirements, such as weight.

  1. Detection and recognition of targets by using signal polarization properties

    NASA Astrophysics Data System (ADS)

    Ponomaryov, Volodymyr I.; Peralta-Fabi, Ricardo; Popov, Anatoly V.; Babakov, Mikhail F.

    1999-08-01

    The quality of radar target recognition can be enhanced by exploiting its polarization signatures. A specialized X-band polarimetric radar was used for target recognition in experimental investigations. The following polarization characteristics connected to the object geometrical properties were investigated: the amplitudes of the polarization matrix elements; an anisotropy coefficient; depolarization coefficient; asymmetry coefficient; the energy of a backscattering signal; object shape factor. A large quantity of polarimetric radar data was measured and processed to form a database of different object and different weather conditions. The histograms of polarization signatures were approximated by a Nakagami distribution, then used for real- time target recognition. The Neyman-Pearson criterion was used for the target detection, and the criterion of the maximum of a posterior probability was used for recognition problem. Some results of experimental verification of pattern recognition and detection of objects with different electrophysical and geometrical characteristics urban in clutter are presented in this paper.

  2. Detection of target-probe oligonucleotide hybridization using synthetic nanopore resistive pulse sensing.

    PubMed

    Booth, Marsilea Adela; Vogel, Robert; Curran, James M; Harbison, SallyAnn; Travas-Sejdic, Jadranka

    2013-07-15

    Despite the plethora of DNA sensor platforms available, a portable, sensitive, selective and economic sensor able to rival current fluorescence-based techniques would find use in many applications. In this research, probe oligonucleotide-grafted particles are used to detect target DNA in solution through a resistive pulse nanopore detection technique. Using carbodiimide chemistry, functionalized probe DNA strands are attached to carboxylated dextran-based magnetic particles. Subsequent incubation with complementary target DNA yields a change in surface properties as the two DNA strands hybridize. Particle-by-particle analysis with resistive pulse sensing is performed to detect these changes. A variable pressure method allows identification of changes in the surface charge of particles. As proof-of-principle, we demonstrate that target hybridization is selectively detected at micromolar concentrations (nanomoles of target) using resistive pulse sensing, confirmed by fluorescence and phase analysis light scattering as complementary techniques. The advantages, feasibility and limitations of using resistive pulse sensing for sample analysis are discussed. Copyright © 2013 Elsevier B.V. All rights reserved.

  3. Study on the influence factors of camouflage target polarization detection

    NASA Astrophysics Data System (ADS)

    Huang, Yanhua; Chen, Lei; Li, Xia; Wu, Wenyuan

    2016-10-01

    The degree of linear polarization (DOLP) expressions at any polarizer direction (PD) was deduced based on the Stokes vector and Mueller matrix. The outdoors experiments were carried out to demonstrate the expressions. This paper mainly explored the DOLP-image-Contrast (DOLPC) between the target image and the background image, and the PD and RGB waveband that be considered two important influence factors were studied for camouflage target polarization detection. It was found that the DOLPC of target and background was obviously higher than intensity image. When setting the reference direction that polarizer was perpendicular to the incident face, the DOLP image of interval angle 60 degree between PD and reference direction had relatively high DOLPC, the interval angle 45 degree was the second, and the interval angle 35 degree was the third. The outdoors polarization detection experiment of controlling waveband showed that the DOLPC results was significantly different to use 650nm, 550nm and 450nm waveband, and the polarization detection performance by using 650nm band was an optimization method.

  4. A manifold learning approach to target detection in high-resolution hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Ziemann, Amanda K.

    Imagery collected from airborne platforms and satellites provide an important medium for remotely analyzing the content in a scene. In particular, the ability to detect a specific material within a scene is of high importance to both civilian and defense applications. This may include identifying "targets" such as vehicles, buildings, or boats. Sensors that process hyperspectral images provide the high-dimensional spectral information necessary to perform such analyses. However, for a d-dimensional hyperspectral image, it is typical for the data to inherently occupy an m-dimensional space, with m << d. In the remote sensing community, this has led to a recent increase in the use of manifold learning, which aims to characterize the embedded lower-dimensional, non-linear manifold upon which the hyperspectral data inherently lie. Classic hyperspectral data models include statistical, linear subspace, and linear mixture models, but these can place restrictive assumptions on the distribution of the data; this is particularly true when implementing traditional target detection approaches, and the limitations of these models are well-documented. With manifold learning based approaches, the only assumption is that the data reside on an underlying manifold that can be discretely modeled by a graph. The research presented here focuses on the use of graph theory and manifold learning in hyperspectral imagery. Early work explored various graph-building techniques with application to the background model of the Topological Anomaly Detection (TAD) algorithm, which is a graph theory based approach to anomaly detection. This led towards a focus on target detection, and in the development of a specific graph-based model of the data and subsequent dimensionality reduction using manifold learning. An adaptive graph is built on the data, and then used to implement an adaptive version of locally linear embedding (LLE). We artificially induce a target manifold and incorporate it into

  5. Cortical Spatio-Temporal Dynamics Underlying Phonological Target Detection in Humans

    ERIC Educational Resources Information Center

    Chang, Edward F.; Edwards, Erik; Nagarajan, Srikantan S.; Fogelson, Noa; Dalal, Sarang S.; Canolty, Ryan T.; Kirsch, Heidi E.; Barbaro, Nicholas M.; Knight, Robert T.

    2011-01-01

    Selective processing of task-relevant stimuli is critical for goal-directed behavior. We used electrocorticography to assess the spatio-temporal dynamics of cortical activation during a simple phonological target detection task, in which subjects press a button when a prespecified target syllable sound is heard. Simultaneous surface potential…

  6. Rare targets are less susceptible to attention capture once detection has begun.

    PubMed

    Hon, Nicholas; Ng, Gavin; Chan, Gerald

    2016-04-01

    Rare or low probability targets are detected more slowly and/ or less accurately than higher probability counterparts. Various proposals have implicated perceptual and response-based processes in this deficit. Recent evidence, however, suggests that it is attentional in nature, with low probability targets requiring more attentional resources than high probability ones to detect. This difference in attentional requirements, in turn, suggests the possibility that low and high probability targets may have different susceptibilities to attention capture, which is also known to be resource-dependent. Supporting this hypothesis, we found that, once attentional resources have begun to be engaged by detection processes, low, but not high, probability targets have a reduced susceptibility to capture. Our findings speak to several issues. First, they indicate that the likelihood of attention capture occurring when a given task-relevant stimulus is being processed is dependent, to some extent, on how said stimulus is represented within mental task sets. Second, they provide added support for the idea that the behavioural deficit associated with low probability targets is attention-based. Finally, the current data point to reduced top-down biasing of target templates as a likely mechanism underlying the attentional locus of the deficit in question.

  7. Dolphin biosonar target detection in noise: wrap up of a past experiment.

    PubMed

    Au, Whitlow W L

    2014-07-01

    The target detection capability of bottlenose dolphins in the presence of artificial masking noise was first studied by Au and Penner [J. Acoust. Soc. Am. 70, 687-693 (1981)] in which the dolphins' target detection threshold was determined as a function of the ratio of the echo energy flux density and the estimated received noise spectral density. Such a metric was commonly used in human psychoacoustics despite the fact that the echo energy flux density is not compatible with noise spectral density which is averaged intensity per Hz. Since the earlier detection in noise studies, two important parameters, the dolphin integration time applicable to broadband clicks and the dolphin's auditory filter shape, were determined. The inclusion of these two parameters allows for the estimation of the received energy flux density of the masking noise so that the dolphin target detection can now be determined as a function of the ratio of the received energy of the echo over the received noise energy. Using an integration time of 264 μs and an auditory bandwidth of 16.7 kHz, the ratio of the echo energy to noise energy at the target detection threshold is approximately 1 dB.

  8. Moving target parameter estimation of SAR after two looks cancellation

    NASA Astrophysics Data System (ADS)

    Gan, Rongbing; Wang, Jianguo; Gao, Xiang

    2005-11-01

    Moving target detection of synthetic aperture radar (SAR) by two looks cancellation is studied. First, two looks are got by the first and second half of the synthetic aperture. After two looks cancellation, the moving targets are reserved and stationary targets are removed. After that, a Constant False Alarm Rate (CFAR) detector detects moving targets. The ground range velocity and cross-range velocity of moving target can be got by the position shift between the two looks. We developed a method to estimate the cross-range shift due to slant range moving. we estimate cross-range shift by Doppler frequency center. Wigner-Ville Distribution (WVD) is used to estimate the Doppler frequency center (DFC). Because the range position and cross range before correction is known, estimation of DFC is much easier and efficient. Finally experiments results show that our algorithms have good performance. With the algorithms we can estimate the moving target parameter accurately.

  9. Towards Discovery and Targeted Peptide Biomarker Detection Using nanoESI-TIMS-TOF MS

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Garabedian, Alyssa; Benigni, Paolo; Ramirez, Cesar E.

    Abstract. In the present work, the potential of trapped ion mobility spectrometry coupled to TOF mass spectrometry (TIMS-TOF MS) for discovery and targeted monitoring of peptide biomarkers from human-in-mouse xenograft tumor tissue was evaluated. In particular, a TIMS-MS workflow was developed for the detection and quantification of peptide biomarkers using internal heavy analogs, taking advantage of the high mobility resolution (R = 150–250) prior to mass analysis. Five peptide biomarkers were separated, identified, and quantified using offline nanoESI-TIMSCID- TOF MS; the results were in good agreement with measurements using a traditional LC-ESI-MS/MS proteomics workflow. The TIMS-TOF MS analysis permitted peptidemore » biomarker detection based on accurate mobility, mass measurements, and high sequence coverage for concentrations in the 10–200 nM range, while simultaneously achieving discovery measurements« less

  10. Non-invasive timing of gas gun projectiles with light detection and ranging

    NASA Astrophysics Data System (ADS)

    Goodwin, P. M.; Bartram, B. D.; Gibson, L. L.; Wu, M.; Dattelbaum, D. M.

    2014-05-01

    We have developed a Light Detection and Ranging (LIDAR) diagnostic to track the position of a projectile inside of a gas gun launch tube in real-time. This capability permits the generation of precisely timed trigger pulses useful for triggering high-latency diagnostics such as a flash lamp-pumped laser. An initial feasibility test was performed using a 72 mm bore diameter single-stage gas gun routinely used for dynamic research at Los Alamos. A 655 nm pulsed diode laser operating at a pulse repetition rate of 100 kHz was used to interrogate the position of the moving projectile in real-time. The position of the projectile in the gun barrel was tracked over a distance of ~ 3 meters prior to impact. The position record showed that the projectile moved at a velocity of 489 m/s prior to impacting the target. This velocity was in good agreement with independent measurements of the projectile velocity by photon Doppler velocimetry and timing of the passage of the projectile through optical marker beams positioned at the muzzle of the gun. The time-to-amplitude conversion electronics used enable the LIDAR data to be processed in real-time to generate trigger pulses at preset separations between the projectile and target.

  11. Engineered Cpf1 variants with altered PAM specificities increase genome targeting range

    PubMed Central

    Gao, Linyi; Cox, David B.T.; Yan, Winston X.; Manteiga, John C.; Schneider, Martin W.; Yamano, Takashi; Nishimasu, Hiroshi; Nureki, Osamu; Crosetto, Nicola; Zhang, Feng

    2017-01-01

    The RNA-guided endonuclease Cpf1 is a promising tool for genome editing in eukaryotic cells1–7. However, the utility of the commonly used Acidaminococcus sp. BV3L6 Cpf1 (AsCpf1) and Lachnospiraceae bacterium ND2006 Cpf1 (LbCpf1) is limited by their requirement of a TTTV protospacer adjacent motif (PAM) in the DNA substrate. To address this limitation, we performed a structure-guided mutagenesis screen to increase the targeting range of Cpf1. We engineered two AsCpf1 variants carrying the mutations S542R/K607R and S542R/K548V/N552R, which recognize TYCV and TATV PAMs, respectively, with enhanced activities in vitro and in human cells. Genome-wide assessment of off-target activity using BLISS7 assay indicated that these variants retain high DNA targeting specificity, which we further improved by introducing an additional non-PAM-interacting mutation. Introducing the identified mutations at their corresponding positions in LbCpf1 similarly altered its PAM specificity. Together, these variants increase the targeting range of Cpf1 by approximately three-fold in human coding sequences to one cleavage site per ~11 bp. PMID:28581492

  12. Ultra-Wideband EMI Sensing: Non-Metallic Target Detection and Automatic Classification of Unexploded Ordnance

    NASA Astrophysics Data System (ADS)

    Sigman, John Brevard

    Buried explosive hazards present a pressing problem worldwide. Millions of acres and thousands of sites are contaminated in the United States alone [1, 2]. There are three categories of explosive hazards: metallic, intermediate-electrical conducting (IEC), and non-conducting targets. Metallic target detection and classification by electromagnetic (EM) signature has been the subject of research for many years. Key to the success of this research is modern multi-static Electromagnetic Induction (EMI) sensors, which are able to measure the wideband EMI response from metallic buried targets. However, no hardware solutions exist which can characterize IEC and non-conducting targets. While high-conducting metallic targets exhibit a quadrature peak response for frequencies in a traditional EMI regime under 100 kHz, the response of intermediate-conducting objects manifests at higher frequencies, between 100 kHz and 15 MHz. In addition to high-quality electromagnetic sensor data and robust electromagnetic models, a classification procedure is required to discriminate Targets of Interest (TOI) from clutter. Currently, costly human experts are used for this task. This expense and effort can be spared by using statistical signal processing and machine learning. This thesis has two main parts. In the first part, we explore using the high frequency EMI (HFEMI) band (100 kHz-15 MHz) for detection of carbon fiber UXO, voids, and of materials with characteristics that may be associated with improvised explosive devices (IED). We constructed an HFEMI sensing instrument, and apply the techniques of metal detection to sensing in a band of frequencies which are the transition between the induction and radar bands. In this transition domain, physical considerations and technological issues arise that cannot be solved via the approaches used in either of the bracketing lower and higher frequency ranges. In the second half of this thesis, we present a procedure for automatic

  13. Detecting ship targets in spaceborne infrared image based on modeling radiation anomalies

    NASA Astrophysics Data System (ADS)

    Wang, Haibo; Zou, Zhengxia; Shi, Zhenwei; Li, Bo

    2017-09-01

    Using infrared imaging sensors to detect ship target in the ocean environment has many advantages compared to other sensor modalities, such as better thermal sensitivity and all-weather detection capability. We propose a new ship detection method by modeling radiation anomalies for spaceborne infrared image. The proposed method can be decomposed into two stages, where in the first stage, a test infrared image is densely divided into a set of image patches and the radiation anomaly of each patch is estimated by a Gaussian Mixture Model (GMM), and thereby target candidates are obtained from anomaly image patches. In the second stage, target candidates are further checked by a more discriminative criterion to obtain the final detection result. The main innovation of the proposed method is inspired by the biological mechanism that human eyes are sensitive to the unusual and anomalous patches among complex background. The experimental result on short wavelength infrared band (1.560 - 2.300 μm) and long wavelength infrared band (10.30 - 12.50 μm) of Landsat-8 satellite shows the proposed method achieves a desired ship detection accuracy with higher recall than other classical ship detection methods.

  14. Visually directed vs. software-based targeted biopsy compared to transperineal template mapping biopsy in the detection of clinically significant prostate cancer.

    PubMed

    Valerio, Massimo; McCartan, Neil; Freeman, Alex; Punwani, Shonit; Emberton, Mark; Ahmed, Hashim U

    2015-10-01

    Targeted biopsy based on cognitive or software magnetic resonance imaging (MRI) to transrectal ultrasound registration seems to increase the detection rate of clinically significant prostate cancer as compared with standard biopsy. However, these strategies have not been directly compared against an accurate test yet. The aim of this study was to obtain pilot data on the diagnostic ability of visually directed targeted biopsy vs. software-based targeted biopsy, considering transperineal template mapping (TPM) biopsy as the reference test. Prospective paired cohort study included 50 consecutive men undergoing TPM with one or more visible targets detected on preoperative multiparametric MRI. Targets were contoured on the Biojet software. Patients initially underwent software-based targeted biopsies, then visually directed targeted biopsies, and finally systematic TPM. The detection rate of clinically significant disease (Gleason score ≥3+4 and/or maximum cancer core length ≥4mm) of one strategy against another was compared by 3×3 contingency tables. Secondary analyses were performed using a less stringent threshold of significance (Gleason score ≥4+3 and/or maximum cancer core length ≥6mm). Median age was 68 (interquartile range: 63-73); median prostate-specific antigen level was 7.9ng/mL (6.4-10.2). A total of 79 targets were detected with a mean of 1.6 targets per patient. Of these, 27 (34%), 28 (35%), and 24 (31%) were scored 3, 4, and 5, respectively. At a patient level, the detection rate was 32 (64%), 34 (68%), and 38 (76%) for visually directed targeted, software-based biopsy, and TPM, respectively. Combining the 2 targeted strategies would have led to detection rate of 39 (78%). At a patient level and at a target level, software-based targeted biopsy found more clinically significant diseases than did visually directed targeted biopsy, although this was not statistically significant (22% vs. 14%, P = 0.48; 51.9% vs. 44.3%, P = 0.24). Secondary

  15. Target detection using the background model from the topological anomaly detection algorithm

    NASA Astrophysics Data System (ADS)

    Dorado Munoz, Leidy P.; Messinger, David W.; Ziemann, Amanda K.

    2013-05-01

    The Topological Anomaly Detection (TAD) algorithm has been used as an anomaly detector in hyperspectral and multispectral images. TAD is an algorithm based on graph theory that constructs a topological model of the background in a scene, and computes an anomalousness ranking for all of the pixels in the image with respect to the background in order to identify pixels with uncommon or strange spectral signatures. The pixels that are modeled as background are clustered into groups or connected components, which could be representative of spectral signatures of materials present in the background. Therefore, the idea of using the background components given by TAD in target detection is explored in this paper. In this way, these connected components are characterized in three different approaches, where the mean signature and endmembers for each component are calculated and used as background basis vectors in Orthogonal Subspace Projection (OSP) and Adaptive Subspace Detector (ASD). Likewise, the covariance matrix of those connected components is estimated and used in detectors: Constrained Energy Minimization (CEM) and Adaptive Coherence Estimator (ACE). The performance of these approaches and the different detectors is compared with a global approach, where the background characterization is derived directly from the image. Experiments and results using self-test data set provided as part of the RIT blind test target detection project are shown.

  16. Target detection and localization in shallow water: an experimental demonstration of the acoustic barrier problem at the laboratory scale.

    PubMed

    Marandet, Christian; Roux, Philippe; Nicolas, Barbara; Mars, Jérôme

    2011-01-01

    This study demonstrates experimentally at the laboratory scale the detection and localization of a wavelength-sized target in a shallow ultrasonic waveguide between two source-receiver arrays at 3 MHz. In the framework of the acoustic barrier problem, at the 1/1000 scale, the waveguide represents a 1.1-km-long, 52-m-deep ocean acoustic channel in the kilohertz frequency range. The two coplanar arrays record in the time-domain the transfer matrix of the waveguide between each pair of source-receiver transducers. Invoking the reciprocity principle, a time-domain double-beamforming algorithm is simultaneously performed on the source and receiver arrays. This array processing projects the multireverberated acoustic echoes into an equivalent set of eigenrays, which are defined by their launch and arrival angles. Comparison is made between the intensity of each eigenray without and with a target for detection in the waveguide. Localization is performed through tomography inversion of the acoustic impedance of the target, using all of the eigenrays extracted from double beamforming. The use of the diffraction-based sensitivity kernel for each eigenray provides both the localization and the signature of the target. Experimental results are shown in the presence of surface waves, and methodological issues are discussed for detection and localization.

  17. Infrared small target detection based on multiscale center-surround contrast measure

    NASA Astrophysics Data System (ADS)

    Fu, Hao; Long, Yunli; Zhu, Ran; An, Wei

    2018-04-01

    Infrared(IR) small target detection plays a critical role in the Infrared Search And Track (IRST) system. Although it has been studied for years, there are some difficulties remained to the clutter environment. According to the principle of human discrimination of small targets from a natural scene that there is a signature of discontinuity between the object and its neighboring regions, we develop an efficient method for infrared small target detection called multiscale centersurround contrast measure (MCSCM). First, to determine the maximum neighboring window size, an entropy-based window selection technique is used. Then, we construct a novel multiscale center-surround contrast measure to calculate the saliency map. Compared with the original image, the MCSCM map has less background clutters and noise residual. Subsequently, a simple threshold is used to segment the target. Experimental results show our method achieves better performance.

  18. Target Detection over the Diurnal Cycle Using a Multispectral Infrared Sensor.

    PubMed

    Zhao, Huijie; Ji, Zheng; Li, Na; Gu, Jianrong; Li, Yansong

    2016-12-29

    When detecting a target over the diurnal cycle, a conventional infrared thermal sensor might lose the target due to the thermal crossover, which could happen at any time throughout the day when the infrared image contrast between target and background in a scene is indistinguishable due to the temperature variation. In this paper, the benefits of using a multispectral-based infrared sensor over the diurnal cycle have been shown. Firstly, a brief theoretical analysis on how the thermal crossover influences a conventional thermal sensor, within the conditions where the thermal crossover would happen and why the mid-infrared (3~5 μm) multispectral technology is effective, is presented. Furthermore, the effectiveness of this technology is also described and we describe how the prototype design and multispectral technology is employed to help solve the thermal crossover detection problem. Thirdly, several targets are set up outside and imaged in the field experiment over a 24-h period. The experimental results show that the multispectral infrared imaging system can enhance the contrast of the detected images and effectively solve the failure of the conventional infrared sensor during the diurnal cycle, which is of great significance for infrared surveillance applications.

  19. Target Detection over the Diurnal Cycle Using a Multispectral Infrared Sensor

    PubMed Central

    Zhao, Huijie; Ji, Zheng; Li, Na; Gu, Jianrong; Li, Yansong

    2016-01-01

    When detecting a target over the diurnal cycle, a conventional infrared thermal sensor might lose the target due to the thermal crossover, which could happen at any time throughout the day when the infrared image contrast between target and background in a scene is indistinguishable due to the temperature variation. In this paper, the benefits of using a multispectral-based infrared sensor over the diurnal cycle have been shown. Firstly, a brief theoretical analysis on how the thermal crossover influences a conventional thermal sensor, within the conditions where the thermal crossover would happen and why the mid-infrared (3~5 μm) multispectral technology is effective, is presented. Furthermore, the effectiveness of this technology is also described and we describe how the prototype design and multispectral technology is employed to help solve the thermal crossover detection problem. Thirdly, several targets are set up outside and imaged in the field experiment over a 24-h period. The experimental results show that the multispectral infrared imaging system can enhance the contrast of the detected images and effectively solve the failure of the conventional infrared sensor during the diurnal cycle, which is of great significance for infrared surveillance applications. PMID:28036073

  20. Detection technology of polarization target based on curvelet transform in turbid liquid

    NASA Astrophysics Data System (ADS)

    Zhang, Su; Duan, Jin; Fu, Qiang; Zhan, Juntong; Ma, Wanzhuo

    2015-08-01

    To suppress the interference of the target detecting in the turbid medium, a kind of polarization detection technology based on Curvelet transform was applied. This method firstly adjusts the angles of polarizing film to get the intensity images of the situations at 0°,60° and 120°, then deduces the images of Stokes vectors, degree of polarization (DOP) and polarization angle (PA) according to the Mueller matrix. At last the DOP and intensity images can be decomposed by Curvelet transform to realize the fusion of the high and low coefficients respectively, after the processed coefficients are reconstructed, the target which is easier to detect can be achieved. To prove this method, many targets in turbid medium have been detected by polarization method and fused their DOP and intensity images with Curvelet transform algorithm. As an example screws in moderate and high concentration liquid are presented respectively, from which we can see the unpolarized targets are less obvious in higher concentration liquid. When the DOP and intensity images are fused by Curvelet transform, the targets are emerged clearly out of the turbid medium, and the values of the quality evaluation parameters in clarity, degree of contract and spatial frequency are prominently enhanced comparing with the unpolarized images, which can show the feasibility of this method.

  1. Electromagnetic Induction Spectroscopy for the Detection of Subsurface Targets

    DTIC Science & Technology

    2012-12-01

    curves of the proposed method and that of Fails et al.. For the kNN ROC curve, k = 7. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81...et al. [6] and Ramachandran et al. [7] both demonstrated success in detecting mines using the k-nearest-neighbor ( kNN ) algorithm based on the EMI...error is also included in the feature vector. The kNN labels an unknown target based on the closest targets in a training set. Collins et al. [2] and

  2. A high dynamic range pulse counting detection system for mass spectrometry.

    PubMed

    Collings, Bruce A; Dima, Martian D; Ivosev, Gordana; Zhong, Feng

    2014-01-30

    A high dynamic range pulse counting system has been developed that demonstrates an ability to operate at up to 2e8 counts per second (cps) on a triple quadrupole mass spectrometer. Previous pulse counting detection systems have typically been limited to about 1e7 cps at the upper end of the systems dynamic range. Modifications to the detection electronics and dead time correction algorithm are described in this paper. A high gain transimpedance amplifier is employed that allows a multi-channel electron multiplier to be operated at a significantly lower bias potential than in previous pulse counting systems. The system utilises a high-energy conversion dynode, a multi-channel electron multiplier, a high gain transimpedance amplifier, non-paralysing detection electronics and a modified dead time correction algorithm. Modification of the dead time correction algorithm is necessary due to a characteristic of the pulse counting electronics. A pulse counting detection system with the capability to count at ion arrival rates of up to 2e8 cps is described. This is shown to provide a linear dynamic range of nearly five orders of magnitude for a sample of aprazolam with concentrations ranging from 0.0006970 ng/mL to 3333 ng/mL while monitoring the m/z 309.1 → m/z 205.2 transition. This represents an upward extension of the detector's linear dynamic range of about two orders of magnitude. A new high dynamic range pulse counting system has been developed demonstrating the ability to operate at up to 2e8 cps on a triple quadrupole mass spectrometer. This provides an upward extension of the detector's linear dynamic range by about two orders of magnitude over previous pulse counting systems. Copyright © 2013 John Wiley & Sons, Ltd.

  3. Fire flame detection based on GICA and target tracking

    NASA Astrophysics Data System (ADS)

    Rong, Jianzhong; Zhou, Dechuang; Yao, Wei; Gao, Wei; Chen, Juan; Wang, Jian

    2013-04-01

    To improve the video fire detection rate, a robust fire detection algorithm based on the color, motion and pattern characteristics of fire targets was proposed, which proved a satisfactory fire detection rate for different fire scenes. In this fire detection algorithm: (a) a rule-based generic color model was developed based on analysis on a large quantity of flame pixels; (b) from the traditional GICA (Geometrical Independent Component Analysis) model, a Cumulative Geometrical Independent Component Analysis (C-GICA) model was developed for motion detection without static background and (c) a BP neural network fire recognition model based on multi-features of the fire pattern was developed. Fire detection tests on benchmark fire video clips of different scenes have shown the robustness, accuracy and fast-response of the algorithm.

  4. Ultrasensitive electrochemical biosensor for detection of DNA from Bacillus subtilis by coupling target-induced strand displacement and nicking endonuclease signal amplification.

    PubMed

    Hu, Yuhua; Xu, Xueqin; Liu, Qionghua; Wang, Ling; Lin, Zhenyu; Chen, Guonan

    2014-09-02

    A simple, ultrasensitive, and specific electrochemical biosensor was designed to determine the given DNA sequence of Bacillus subtilis by coupling target-induced strand displacement and nicking endonuclease signal amplification. The target DNA (TD, the DNA sequence from the hypervarient region of 16S rDNA of Bacillus subtilis) could be detected by the differential pulse voltammetry (DPV) in a range from 0.1 fM to 20 fM with the detection limit down to 0.08 fM at the 3s(blank) level. This electrochemical biosensor exhibits high distinction ability to single-base mismatch, double-bases mismatch, and noncomplementary DNA sequence, which may be expected to detect single-base mismatch and single nucleotide polymorphisms (SNPs). Moreover, the applicability of the designed biosensor for detecting the given DNA sequence from Bacillus subtilis was investigated. The result obtained by electrochemical method is approximately consistent with that by a real-time quantitative polymerase chain reaction detecting system (QPCR) with SYBR Green.

  5. Assessment of Schrodinger Eigenmaps for target detection

    NASA Astrophysics Data System (ADS)

    Dorado Munoz, Leidy P.; Messinger, David W.; Czaja, Wojtek

    2014-06-01

    Non-linear dimensionality reduction methods have been widely applied to hyperspectral imagery due to its structure as the information can be represented in a lower dimension without losing information, and because the non-linear methods preserve the local geometry of the data while the dimension is reduced. One of these methods is Laplacian Eigenmaps (LE), which assumes that the data lies on a low dimensional manifold embedded in a high dimensional space. LE builds a nearest neighbor graph, computes its Laplacian and performs the eigendecomposition of the Laplacian. These eigenfunctions constitute a basis for the lower dimensional space in which the geometry of the manifold is preserved. In addition to the reduction problem, LE has been widely used in tasks such as segmentation, clustering, and classification. In this regard, a new Schrodinger Eigenmaps (SE) method was developed and presented as a semi-supervised classification scheme in order to improve the classification performance and take advantage of the labeled data. SE is an algorithm built upon LE, where the former Laplacian operator is replaced by the Schrodinger operator. The Schrodinger operator includes a potential term V, that, taking advantage of the additional information such as labeled data, allows clustering of similar points. In this paper, we explore the idea of using SE in target detection. In this way, we present a framework where the potential term V is defined as a barrier potential: a diagonal matrix encoding the spatial position of the target, and the detection performance is evaluated by using different targets and different hyperspectral scenes.

  6. Evaluation of Long-Range Lightning Detection Networks Using TRMM/LIS Observations

    NASA Technical Reports Server (NTRS)

    Rudlosky, Scott D.; Holzworth, Robert H.; Carey, Lawrence D.; Schultz, Chris J.; Bateman, Monte; Cecil, Daniel J.; Cummins, Kenneth L.; Petersen, Walter A.; Blakeslee, Richard J.; Goodman, Steven J.

    2011-01-01

    Recent advances in long-range lightning detection technologies have improved our understanding of thunderstorm evolution in the data sparse oceanic regions. Although the expansion and improvement of long-range lightning datasets have increased their applicability, these applications (e.g., data assimilation, atmospheric chemistry, and aviation weather hazards) require knowledge of the network detection capabilities. Toward this end, the present study evaluates data from the World Wide Lightning Location Network (WWLLN) using observations from the Lightning Imaging Sensor (LIS) aboard the Tropical Rainfall Measurement Mission (TRMM) satellite. The study documents the WWLLN detection efficiency and location accuracy relative to LIS observations, describes the spatial variability in these performance metrics, and documents the characteristics of LIS flashes that are detected by WWLLN. Improved knowledge of the WWLLN detection capabilities will allow researchers, algorithm developers, and operational users to better prepare for the spatial and temporal coverage of the upcoming GOES-R Geostationary Lightning Mapper (GLM).

  7. Aerial surveillance based on hierarchical object classification for ground target detection

    NASA Astrophysics Data System (ADS)

    Vázquez-Cervantes, Alberto; García-Huerta, Juan-Manuel; Hernández-Díaz, Teresa; Soto-Cajiga, J. A.; Jiménez-Hernández, Hugo

    2015-03-01

    Unmanned aerial vehicles have turned important in surveillance application due to the flexibility and ability to inspect and displace in different regions of interest. The instrumentation and autonomy of these vehicles have been increased; i.e. the camera sensor is now integrated. Mounted cameras allow flexibility to monitor several regions of interest, displacing and changing the camera view. A well common task performed by this kind of vehicles correspond to object localization and tracking. This work presents a hierarchical novel algorithm to detect and locate objects. The algorithm is based on a detection-by-example approach; this is, the target evidence is provided at the beginning of the vehicle's route. Afterwards, the vehicle inspects the scenario, detecting all similar objects through UTM-GPS coordinate references. Detection process consists on a sampling information process of the target object. Sampling process encode in a hierarchical tree with different sampling's densities. Coding space correspond to a huge binary space dimension. Properties such as independence and associative operators are defined in this space to construct a relation between the target object and a set of selected features. Different densities of sampling are used to discriminate from general to particular features that correspond to the target. The hierarchy is used as a way to adapt the complexity of the algorithm due to optimized battery duty cycle of the aerial device. Finally, this approach is tested in several outdoors scenarios, proving that the hierarchical algorithm works efficiently under several conditions.

  8. Motion Estimation Utilizing Range Detection-Enhanced Visual Odometry

    NASA Technical Reports Server (NTRS)

    Morris, Daniel Dale (Inventor); Chang, Hong (Inventor); Friend, Paul Russell (Inventor); Chen, Qi (Inventor); Graf, Jodi Seaborn (Inventor)

    2016-01-01

    A motion determination system is disclosed. The system may receive a first and a second camera image from a camera, the first camera image received earlier than the second camera image. The system may identify corresponding features in the first and second camera images. The system may receive range data comprising at least one of a first and a second range data from a range detection unit, corresponding to the first and second camera images, respectively. The system may determine first positions and the second positions of the corresponding features using the first camera image and the second camera image. The first positions or the second positions may be determined by also using the range data. The system may determine a change in position of the machine based on differences between the first and second positions, and a VO-based velocity of the machine based on the determined change in position.

  9. Performance of target detection algorithm in compressive sensing miniature ultraspectral imaging compressed sensing system

    NASA Astrophysics Data System (ADS)

    Gedalin, Daniel; Oiknine, Yaniv; August, Isaac; Blumberg, Dan G.; Rotman, Stanley R.; Stern, Adrian

    2017-04-01

    Compressive sensing theory was proposed to deal with the high quantity of measurements demanded by traditional hyperspectral systems. Recently, a compressive spectral imaging technique dubbed compressive sensing miniature ultraspectral imaging (CS-MUSI) was presented. This system uses a voltage controlled liquid crystal device to create multiplexed hyperspectral cubes. We evaluate the utility of the data captured using the CS-MUSI system for the task of target detection. Specifically, we compare the performance of the matched filter target detection algorithm in traditional hyperspectral systems and in CS-MUSI multiplexed hyperspectral cubes. We found that the target detection algorithm performs similarly in both cases, despite the fact that the CS-MUSI data is up to an order of magnitude less than that in conventional hyperspectral cubes. Moreover, the target detection is approximately an order of magnitude faster in CS-MUSI data.

  10. A speeded-up saliency region-based contrast detection method for small targets

    NASA Astrophysics Data System (ADS)

    Li, Zhengjie; Zhang, Haiying; Bai, Jiaojiao; Zhou, Zhongjun; Zheng, Huihuang

    2018-04-01

    To cope with the rapid development of the real applications for infrared small targets, the researchers have tried their best to pursue more robust detection methods. At present, the contrast measure-based method has become a promising research branch. Following the framework, in this paper, a speeded-up contrast measure scheme is proposed based on the saliency detection and density clustering. First, the saliency region is segmented by saliency detection method, and then, the Multi-scale contrast calculation is carried out on it instead of traversing the whole image. Second, the target with a certain "integrity" property in spatial is exploited to distinguish the target from the isolated noises by density clustering. Finally, the targets are detected by a self-adaptation threshold. Compared with time-consuming MPCM (Multiscale Patch Contrast Map), the time cost of the speeded-up version is within a few seconds. Additional, due to the use of "clustering segmentation", the false alarm caused by heavy noises can be restrained to a lower level. The experiments show that our method has a satisfied FASR (False alarm suppression ratio) and real-time performance compared with the state-of-art algorithms no matter in cloudy sky or sea-sky background.

  11. A sensitive electrochemical aptasensor for multiplex antibiotics detection based on high-capacity magnetic hollow porous nanotracers coupling exonuclease-assisted cascade target recycling.

    PubMed

    Yan, Zhongdan; Gan, Ning; Li, Tianhua; Cao, Yuting; Chen, Yinji

    2016-04-15

    A multiplex electrochemical aptasensor was developed for simultaneous detection of two antibiotics such as chloramphenicol (CAP) and oxytetracycline (OTC), and high-capacity magnetic hollow porous nanotracers coupling exonuclease-assisted target recycling was used to improve sensitivity. The cascade amplification process consists of the exonuclease-assisted target recycling amplification and metal ions encoded magnetic hollow porous nanoparticles (MHPs) to produce voltammetry signals. Upon the specific recognition of aptamers to targets (CAP and OTC), exonuclease I (Exo I) selectively digested the aptamers which were bound with CAP and OTC, then the released CAP and OTC participated new cycling to produce more single DNA, which can act as trigger strands to hybrid with nanotracers to generate further signal amplification. MHPs were used as carriers to load more amounts of metal ions and coupling with Exo I assisted cascade target recycling can amplify the signal for about 12 folds compared with silica based nanotracers. Owing to the dual signal amplification, the linear range between signals and the concentrations of CAP and OTC were obtained in the range of 0.0005-50 ng mL(-1). The detection limits of CAP and OTC were 0.15 and 0.10 ng mL(-1) (S/N=3) which is more than 2 orders lower than commercial enzyme-linked immunosorbent immunoassay (ELISA) method, respectively. The proposed method was successfully applied to simultaneously detection of CAP and OTC in milk samples. Besides, this aptasensor can be applied to other antibiotics detection by changing the corresponding aptamer. The whole scheme is facile, selective and sensitive enough for antibiotics screening in food safety. Copyright © 2015 Elsevier B.V. All rights reserved.

  12. A New Methodology for 3D Target Detection in Automotive Radar Applications

    PubMed Central

    Baselice, Fabio; Ferraioli, Giampaolo; Lukin, Sergyi; Matuozzo, Gianfranco; Pascazio, Vito; Schirinzi, Gilda

    2016-01-01

    Today there is a growing interest in automotive sensor monitoring systems. One of the main challenges is to make them an effective and valuable aid in dangerous situations, improving transportation safety. The main limitation of visual aid systems is that they do not produce accurate results in critical visibility conditions, such as in presence of rain, fog or smoke. Radar systems can greatly help in overcoming such limitations. In particular, imaging radar is gaining interest in the framework of Driver Assistance Systems (DAS). In this manuscript, a new methodology able to reconstruct the 3D imaged scene and to detect the presence of multiple targets within each line of sight is proposed. The technique is based on the use of Compressive Sensing (CS) theory and produces the estimation of multiple targets for each line of sight, their range distance and their reflectivities. Moreover, a fast approach for 2D focus based on the FFT algorithm is proposed. After the description of the proposed methodology, different simulated case studies are reported in order to evaluate the performances of the proposed approach. PMID:27136558

  13. Effects of Alzheimer's Disease on Visual Target Detection: A "Peripheral Bias".

    PubMed

    Vallejo, Vanessa; Cazzoli, Dario; Rampa, Luca; Zito, Giuseppe A; Feuerstein, Flurin; Gruber, Nicole; Müri, René M; Mosimann, Urs P; Nef, Tobias

    2016-01-01

    Visual exploration is an omnipresent activity in everyday life, and might represent an important determinant of visual attention deficits in patients with Alzheimer's Disease (AD). The present study aimed at investigating visual search performance in AD patients, in particular target detection in the far periphery, in daily living scenes. Eighteen AD patients and 20 healthy controls participated in the study. They were asked to freely explore a hemispherical screen, covering ±90°, and to respond to targets presented at 10°, 30°, and 50° eccentricity, while their eye movements were recorded. Compared to healthy controls, AD patients recognized less targets appearing in the center. No difference was found in target detection in the periphery. This pattern was confirmed by the fixation distribution analysis. These results show a neglect for the central part of the visual field for AD patients and provide new insights by mean of a search task involving a larger field of view.

  14. Relative range error evaluation of terrestrial laser scanners using a plate, a sphere, and a novel dual-sphere-plate target.

    PubMed

    Muralikrishnan, Bala; Rachakonda, Prem; Lee, Vincent; Shilling, Meghan; Sawyer, Daniel; Cheok, Geraldine; Cournoyer, Luc

    2017-12-01

    Terrestrial laser scanners (TLS) are a class of 3D imaging systems that produce a 3D point cloud by measuring the range and two angles to a point. The fundamental measurement of a TLS is range. Relative range error is one component of the overall range error of TLS and its estimation is therefore an important aspect in establishing metrological traceability of measurements performed using these systems. Target geometry is an important aspect to consider when realizing the relative range tests. The recently published ASTM E2938-15 mandates the use of a plate target for the relative range tests. While a plate target may reasonably be expected to produce distortion free data even at far distances, the target itself needs careful alignment at each of the relative range test positions. In this paper, we discuss relative range experiments performed using a plate target and then address the advantages and limitations of using a sphere target. We then present a novel dual-sphere-plate target that draws from the advantages of the sphere and the plate without the associated limitations. The spheres in the dual-sphere-plate target are used simply as fiducials to identify a point on the surface of the plate that is common to both the scanner and the reference instrument, thus overcoming the need to carefully align the target.

  15. Method and apparatus for coherent burst ranging

    DOEpatents

    Wachter, Eric A.; Fisher, Walter G.

    1998-01-01

    A high resolution ranging method is described utilizing a novel modulated waveform, hereafter referred to as coherent burst modulation. In the coherent burst method, high frequency modulation of an acoustic or electromagnetic transmitter, such as a laser, is performed at a modulation frequency. This modulation frequency is transmitted quasi-continuously in the form of interrupted bursts of radiation. Energy from the transmitter is directed onto a target, interacts with the target, and the returning energy is collected. The encoded burst pattern contained in the collected return signal is detected coherently by a receiver that is tuned so as to be principally sensitive to the modulation frequency. The receiver signal is processed to determine target range using both time-of-flight of the burst envelope and phase shift of the high frequency modulation. This approach effectively decouples the maximum unambiguous range and range resolution relationship of earlier methods, thereby allowing high precision ranging to be conducted at arbitrarily long distances using at least one burst of encoded energy. The use of a receiver tuned to the high frequency modulation contained within the coherent burst vastly improves both sensitivity in the detection of the target return signal and rejection of background interferences, such as ambient acoustic or electromagnetic noise. Simultaneous transmission at several energies (or wavelengths) is possible by encoding each energy with a separate modulation frequency or pattern; electronic demodulation at the receiver allows the return pattern for each energy to be monitored independently. Radial velocity of a target can also be determined by monitoring change in phase shift of the return signal as a function of time.

  16. Method and apparatus for coherent burst ranging

    DOEpatents

    Wachter, E.A.; Fisher, W.G.

    1998-04-28

    A high resolution ranging method is described utilizing a novel modulated waveform, hereafter referred to as coherent burst modulation. In the coherent burst method, high frequency modulation of an acoustic or electromagnetic transmitter, such as a laser, is performed at a modulation frequency. This modulation frequency is transmitted quasi-continuously in the form of interrupted bursts of radiation. Energy from the transmitter is directed onto a target, interacts with the target, and the returning energy is collected. The encoded burst pattern contained in the collected return signal is detected coherently by a receiver that is tuned so as to be principally sensitive to the modulation frequency. The receiver signal is processed to determine target range using both time-of-flight of the burst envelope and phase shift of the high frequency modulation. This approach effectively decouples the maximum unambiguous range and range resolution relationship of earlier methods, thereby allowing high precision ranging to be conducted at arbitrarily long distances using at least one burst of encoded energy. The use of a receiver tuned to the high frequency modulation contained within the coherent burst vastly improves both sensitivity in the detection of the target return signal and rejection of background interferences, such as ambient acoustic or electromagnetic noise. Simultaneous transmission at several energies (or wavelengths) is possible by encoding each energy with a separate modulation frequency or pattern; electronic demodulation at the receiver allows the return pattern for each energy to be monitored independently. Radial velocity of a target can also be determined by monitoring change in phase shift of the return signal as a function of time. 12 figs.

  17. Target-responsive DNA hydrogel mediated "stop-flow" microfluidic paper-based analytic device for rapid, portable and visual detection of multiple targets.

    PubMed

    Wei, Xiaofeng; Tian, Tian; Jia, Shasha; Zhu, Zhi; Ma, Yanli; Sun, Jianjun; Lin, Zhenyu; Yang, Chaoyong James

    2015-04-21

    A versatile point-of-care assay platform was developed for simultaneous detection of multiple targets based on a microfluidic paper-based analytic device (μPAD) using a target-responsive hydrogel to mediate fluidic flow and signal readout. An aptamer-cross-linked hydrogel was used as a target-responsive flow regulator in the μPAD. In the absence of a target, the hydrogel is formed in the flow channel, stopping the flow in the μPAD and preventing the colored indicator from traveling to the final observation spot, thus yielding a "signal off" readout. In contrast, in the presence of a target, no hydrogel is formed because of the preferential interaction of target and aptamer. This allows free fluidic flow in the μPAD, carrying the indicator to the observation spot and producing a "signal on" readout. The device is inexpensive to fabricate, easy to use, and disposable after detection. Testing results can be obtained within 6 min by the naked eye via a simple loading operation without the need for any auxiliary equipment. Multiple targets, including cocaine, adenosine, and Pb(2+), can be detected simultaneously, even in complex biological matrices such as urine. The reported method offers simple, low cost, rapid, user-friendly, point-of-care testing, which will be useful in many applications.

  18. Small target detection using bilateral filter and temporal cross product in infrared images

    NASA Astrophysics Data System (ADS)

    Bae, Tae-Wuk

    2011-09-01

    We introduce a spatial and temporal target detection method using spatial bilateral filter (BF) and temporal cross product (TCP) of temporal pixels in infrared (IR) image sequences. At first, the TCP is presented to extract the characteristics of temporal pixels by using temporal profile in respective spatial coordinates of pixels. The TCP represents the cross product values by the gray level distance vector of a current temporal pixel and the adjacent temporal pixel, as well as the horizontal distance vector of the current temporal pixel and a temporal pixel corresponding to potential target center. The summation of TCP values of temporal pixels in spatial coordinates makes the temporal target image (TTI), which represents the temporal target information of temporal pixels in spatial coordinates. And then the proposed BF filter is used to extract the spatial target information. In order to predict background without targets, the proposed BF filter uses standard deviations obtained by an exponential mapping of the TCP value corresponding to the coordinate of a pixel processed spatially. The spatial target image (STI) is made by subtracting the predicted image from the original image. Thus, the spatial and temporal target image (STTI) is achieved by multiplying the STI and the TTI, and then targets finally are detected in STTI. In experimental result, the receiver operating characteristics (ROC) curves were computed experimentally to compare the objective performance. From the results, the proposed algorithm shows better discrimination of target and clutters and lower false alarm rates than the existing target detection methods.

  19. Infrared small target detection in heavy sky scene clutter based on sparse representation

    NASA Astrophysics Data System (ADS)

    Liu, Depeng; Li, Zhengzhou; Liu, Bing; Chen, Wenhao; Liu, Tianmei; Cao, Lei

    2017-09-01

    A novel infrared small target detection method based on sky clutter and target sparse representation is proposed in this paper to cope with the representing uncertainty of clutter and target. The sky scene background clutter is described by fractal random field, and it is perceived and eliminated via the sparse representation on fractal background over-complete dictionary (FBOD). The infrared small target signal is simulated by generalized Gaussian intensity model, and it is expressed by the generalized Gaussian target over-complete dictionary (GGTOD), which could describe small target more efficiently than traditional structured dictionaries. Infrared image is decomposed on the union of FBOD and GGTOD, and the sparse representation energy that target signal and background clutter decomposed on GGTOD differ so distinctly that it is adopted to distinguish target from clutter. Some experiments are induced and the experimental results show that the proposed approach could improve the small target detection performance especially under heavy clutter for background clutter could be efficiently perceived and suppressed by FBOD and the changing target could also be represented accurately by GGTOD.

  20. Morphological operators for enhanced polarimetric image target detection

    NASA Astrophysics Data System (ADS)

    Romano, João. M.; Rosario, Dalton S.

    2015-09-01

    We introduce an algorithm based on morphological filters with the Stokes parameters that augments the daytime and nighttime detection of weak-signal manmade objects immersed in a predominant natural background scene. The approach features a tailored sequence of signal-enhancing filters, consisting of core morphological operators (dilation, erosion) and higher level morphological operations (e.g., spatial gradient, opening, closing) to achieve a desired overarching goal. Using representative data from the SPICE database, the results show that the approach was able to automatically and persistently detect with a high confidence level the presence of three mobile military howitzer surrogates (targets) in natural clutter.

  1. Non-Invasive Timing of Gas Gun Projectiles with Light Detection and Ranging

    NASA Astrophysics Data System (ADS)

    Goodwin, Peter; Wu, Ming; Dattelbaum, Dana

    2013-06-01

    We have developed a Light Detection and Ranging (LIDAR) diagnostic to track the position of a projectile inside of the gas gun barrel in real-time. This capability permits the generation of precisely timed trigger pulses useful for pre-triggering high-latency diagnostics such as a flash lamp-pumped laser. An initial feasibility test was performed using a 72 mm bore single-stage gas gun routinely used for dynamic research at Los Alamos National Laboratory. A 655-nm pulsed (~100 ps) diode laser operating at a pulse repetition rate of ~100 kHz was used to interrogate the position of the moving projectile in real-time. The position of the projectile in the gun barrel was tracked over a distance of ~3 meters prior to impact. The position record showed that the projectile moved at a constant velocity (483 m/s) prior to impacting the target. This velocity was in good agreement with independent measurements of the projectile velocity by photon Doppler velocimetry, and timing of the passage of the projectile through optical marker beams positioned at the muzzle of the gun. The LIDAR return can be processed in real-time to generate pre-trigger pulses at preset separations between the projectile and target. Work funded by LANL Laboratory Directed Research Project 2011012DR. LA-UR-13-21121, approved for public release.

  2. Analysis on Target Detection and Classification in LTE Based Passive Forward Scattering Radar

    PubMed Central

    Raja Abdullah, Raja Syamsul Azmir; Abdul Aziz, Noor Hafizah; Abdul Rashid, Nur Emileen; Ahmad Salah, Asem; Hashim, Fazirulhisyam

    2016-01-01

    The passive bistatic radar (PBR) system can utilize the illuminator of opportunity to enhance radar capability. By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. The system is known as passive Forward Scattering Radar (FSR). The passive FSR system can exploit the peculiar advantage of the enhancement in forward scatter radar cross section (FSRCS) for target detection. Thus, the aim of this paper is to show the feasibility of passive FSR for moving target detection and classification by experimental analysis and results. The signal source is coming from the latest technology of 4G Long-Term Evolution (LTE) base station. A detailed explanation on the passive FSR receiver circuit, the detection scheme and the classification algorithm are given. In addition, the proposed passive FSR circuit employs the self-mixing technique at the receiver; hence the synchronization signal from the transmitter is not required. The experimental results confirm the passive FSR system’s capability for ground target detection and classification. Furthermore, this paper illustrates the first classification result in the passive FSR system. The great potential in the passive FSR system provides a new research area in passive radar that can be used for diverse remote monitoring applications. PMID:27690051

  3. Analysis on Target Detection and Classification in LTE Based Passive Forward Scattering Radar.

    PubMed

    Raja Abdullah, Raja Syamsul Azmir; Abdul Aziz, Noor Hafizah; Abdul Rashid, Nur Emileen; Ahmad Salah, Asem; Hashim, Fazirulhisyam

    2016-09-29

    The passive bistatic radar (PBR) system can utilize the illuminator of opportunity to enhance radar capability. By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. The system is known as passive Forward Scattering Radar (FSR). The passive FSR system can exploit the peculiar advantage of the enhancement in forward scatter radar cross section (FSRCS) for target detection. Thus, the aim of this paper is to show the feasibility of passive FSR for moving target detection and classification by experimental analysis and results. The signal source is coming from the latest technology of 4G Long-Term Evolution (LTE) base station. A detailed explanation on the passive FSR receiver circuit, the detection scheme and the classification algorithm are given. In addition, the proposed passive FSR circuit employs the self-mixing technique at the receiver; hence the synchronization signal from the transmitter is not required. The experimental results confirm the passive FSR system's capability for ground target detection and classification. Furthermore, this paper illustrates the first classification result in the passive FSR system. The great potential in the passive FSR system provides a new research area in passive radar that can be used for diverse remote monitoring applications.

  4. Small target detection based on difference accumulation and Gaussian curvature under complex conditions

    NASA Astrophysics Data System (ADS)

    Zhang, He; Niu, Yanxiong; Zhang, Hao

    2017-12-01

    Small target detection is a significant subject in infrared search and track and other photoelectric imaging systems. The small target is imaged under complex conditions, which contains clouds, horizon and bright part. In this paper, a novel small target detection method is proposed based on difference accumulation, clustering and Gaussian curvature. Difference accumulation varies from regions. Therefore, after obtaining difference accumulations, clustering is applied to determine whether the pixel belongs to the heterogeneous region, and eliminate heterogeneous region. Then Gaussian curvature is used to separate target from the homogeneous region. Experiments are conducted for verification, along with comparisons to several other methods. The experimental results demonstrate that our method has an advantage of 1-2 orders of magnitude on SCRG and BSF than others. Given that the false alarm rate is 1, the detection probability can be approximately 0.9 by using proposed method.

  5. Biosonar adjustments to target range of echolocating bottlenose dolphins (Tursiops sp.) in the wild.

    PubMed

    Jensen, F H; Bejder, L; Wahlberg, M; Madsen, P T

    2009-04-01

    Toothed whales use echolocation to locate and track prey. Most knowledge of toothed whale echolocation stems from studies on trained animals, and little is known about how toothed whales regulate and use their biosonar systems in the wild. Recent research suggests that an automatic gain control mechanism in delphinid biosonars adjusts the biosonar output to the one-way transmission loss to the target, possibly a consequence of pneumatic restrictions in how fast the sound generator can be actuated and still maintain high outputs. This study examines the relationships between target range (R), click intervals, and source levels of wild bottlenose dolphins (Tursiops sp.) by recording regular (non-buzz) echolocation clicks with a linear hydrophone array. Dolphins clicked faster with decreasing distance to the array, reflecting a decreasing delay between the outgoing echolocation click and the returning array echo. However, for interclick intervals longer than 30-40 ms, source levels were not limited by the repetition rate. Thus, pneumatic constraints in the sound-production apparatus cannot account for source level adjustments to range as a possible automatic gain control mechanism for target ranges longer than a few body lengths of the dolphin. Source level estimates drop with reducing range between the echolocating dolphins and the target as a function of 17 log(R). This may indicate either (1) an active form of time-varying gain in the biosonar independent of click intervals or (2) a bias in array recordings towards a 20 log(R) relationship for apparent source levels introduced by a threshold on received click levels included in the analysis.

  6. One-step multiplex RT-qPCR detects three citrus viroids from different genera in a wide range of hosts.

    PubMed

    Osman, Fatima; Dang, Tyler; Bodaghi, Sohrab; Vidalakis, Georgios

    2017-07-01

    A one-step multiplex reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR) based on species-specific minor groove binding (MGB) probes, was developed for the simultaneous detection, identification, and quantification of three citrus viroids belonging to different genera. Citrus exocortis viroid (Pospiviroid), Hop stunt viroid (Hostuviroid), and Citrus bark cracking viroid (Cocadviroid) cause a variety of maladies in agriculturally significant crops. Therefore, reliable assays for their detection are essential tools for various government and industry organizations implementing disease management programs. Singleplex qPCR primers and MGB probes were designed individually for the detection of the three targeted viroids, and subsequently combined in a one-step multiplex RT-qPCR reaction. A wide host range of woody plants, including citrus, grapevines, apricots, plums and herbaceous plants such as tomato, cucumber, eggplant and chrysanthemum different world regions were used to validate the assay. Single, double and triple viroid infections were identified in the tested samples. The developed multiplex RT-qPCR assay was compared with a previously reported SYBR Green I RT-qPCR for the universal detection of citrus viroids. Both assays accurately identified all citrus viroid infected samples. The multiplex assay complemented the SYBR Green I universal detection assay by differentiating among citrus viroid species in the positive samples. The developed multiplex RT-qPCR assay has the potential to simultaneously detect each targeted viroid and could be used in high throughput screenings for citrus viroids in field surveys, germplasm banks, nurseries and other viroid disease management programs. Copyright © 2017. Published by Elsevier B.V.

  7. Frequency-Modulated, Continuous-Wave Laser Ranging Using Photon-Counting Detectors

    NASA Technical Reports Server (NTRS)

    Erkmen, Baris I.; Barber, Zeb W.; Dahl, Jason

    2014-01-01

    Optical ranging is a problem of estimating the round-trip flight time of a phase- or amplitude-modulated optical beam that reflects off of a target. Frequency- modulated, continuous-wave (FMCW) ranging systems obtain this estimate by performing an interferometric measurement between a local frequency- modulated laser beam and a delayed copy returning from the target. The range estimate is formed by mixing the target-return field with the local reference field on a beamsplitter and detecting the resultant beat modulation. In conventional FMCW ranging, the source modulation is linear in instantaneous frequency, the reference-arm field has many more photons than the target-return field, and the time-of-flight estimate is generated by balanced difference- detection of the beamsplitter output, followed by a frequency-domain peak search. This work focused on determining the maximum-likelihood (ML) estimation algorithm when continuous-time photoncounting detectors are used. It is founded on a rigorous statistical characterization of the (random) photoelectron emission times as a function of the incident optical field, including the deleterious effects caused by dark current and dead time. These statistics enable derivation of the Cramér-Rao lower bound (CRB) on the accuracy of FMCW ranging, and derivation of the ML estimator, whose performance approaches this bound at high photon flux. The estimation algorithm was developed, and its optimality properties were shown in simulation. Experimental data show that it performs better than the conventional estimation algorithms used. The demonstrated improvement is a factor of 1.414 over frequency-domainbased estimation. If the target interrogating photons and the local reference field photons are costed equally, the optimal allocation of photons between these two arms is to have them equally distributed. This is different than the state of the art, in which the local field is stronger than the target return. The optimal

  8. Long-range surface plasmon polariton detection with a graphene photodetector.

    PubMed

    Ee, Ho-Seok; No, You-Shin; Kim, Jinhyung; Park, Hong-Gyu; Seo, Min-Kyo

    2018-06-15

    We present an integration of a single Ag nanowire (NW) with a graphene photodetector and demonstrate an efficient and compact detection of long-range surface plasmon polaritons (SPPs). Atomically thin graphene provides an ideal platform to detect the evanescent electric field of SPPs extremely bound at the interface of the Ag NW and glass substrate. Scanning photocurrent microscopy directly visualizes a polarization-dependent excitation and detects the SPPs. The SPP detection responsivity is readily controlled up to ∼17  mA/W by the drain-source voltage. We believe that the graphene SPP detector will be a promising building block for highly integrated photonic and optoelectronic circuits.

  9. Gastric cancer target detection using near-infrared hyperspectral imaging with chemometrics

    NASA Astrophysics Data System (ADS)

    Yi, Weisong; Zhang, Jian; Jiang, Houmin; Zhang, Niya

    2014-09-01

    Gastric cancer is one of the leading causes of cancer death in the world due to its high morbidity and mortality. Hyperspectral imaging (HSI) is an emerging, non-destructive, cutting edge analytical technology that combines conventional imaging and spectroscopy in one single system. The manuscript has investigated the application of near-infrared hyperspectral imaging (900-1700 nm) (NIR-HSI) for gastric cancer detection with algorithms. Major spectral differences were observed in three regions (950-1050, 1150-1250, and 1400-1500 nm). By inspecting cancerous mean spectrum three major absorption bands were observed around 975, 1215 and 1450 nm. Furthermore, the cancer target detection results are consistent and conformed with histopathological examination results. These results suggest that NIR-HSI is a simple, feasible and sensitive optical diagnostic technology for gastric cancer target detection with chemometrics.

  10. Real-Time Adaptation of Decision Thresholds in Sensor Networks for Detection of Moving Targets (PREPRINT)

    DTIC Science & Technology

    2010-01-01

    target kinematics for multiple sensor detections is referred to as the track - before - detect strategy, and is commonly adopted in multi-sensor surveillance...of moving targets. Wettergren [4] presented an application of track - before - detect strategies to undersea distributed sensor networks. In de- signing...the deployment of a distributed passive sensor network that employs this track - before - detect procedure, it is impera- tive that the placement of

  11. Bartonella species detection in captive, stranded and free-ranging cetaceans.

    PubMed

    Harms, Craig A; Maggi, Ricardo G; Breitschwerdt, Edward B; Clemons-Chevis, Connie L; Solangi, Mobashir; Rotstein, David S; Fair, Patricia A; Hansen, Larry J; Hohn, Aleta A; Lovewell, Gretchen N; McLellan, William A; Pabst, D Ann; Rowles, Teri K; Schwacke, Lori H; Townsend, Forrest I; Wells, Randall S

    2008-01-01

    We present prevalence of Bartonella spp. for multiple cohorts of wild and captive cetaceans. One hundred and six cetaceans including 86 bottlenose dolphins (71 free-ranging, 14 captive in a facility with a dolphin experiencing debility of unknown origin, 1 stranded), 11 striped dolphins, 4 harbor porpoises, 3 Risso's dolphins, 1 dwarf sperm whale and 1 pygmy sperm whale (all stranded) were sampled. Whole blood (n = 95 live animals) and tissues (n = 15 freshly dead animals) were screened by PCR (n = 106 animals), PCR of enrichment cultures (n = 50 animals), and subcultures (n = 50 animals). Bartonella spp. were detected from 17 cetaceans, including 12 by direct extraction PCR of blood or tissues, 6 by PCR of enrichment cultures, and 4 by subculture isolation. Bartonella spp. were more commonly detected from the captive (6/14, 43%) than from free-ranging (2/71, 2.8%) bottlenose dolphins, and were commonly detected from the stranded animals (9/21, 43%; 3/11 striped dolphins, 3/4 harbor porpoises, 2/3 Risso's dolphins, 1/1 pygmy sperm whale, 0/1 dwarf sperm whale, 0/1 bottlenose dolphin). Sequencing identified a Bartonella spp. most similar to B. henselae San Antonio 2 in eight cases (4 bottlenose dolphins, 2 striped dolphins, 2 harbor porpoises), B. henselae Houston 1 in three cases (2 Risso's dolphins, 1 harbor porpoise), and untyped in six cases (4 bottlenose dolphins, 1 striped dolphin, 1 pygmy sperm whale). Although disease causation has not been established, Bartonella species were detected more commonly from cetaceans that were overtly debilitated or were cohabiting in captivity with a debilitated animal than from free-ranging animals. The detection of Bartonella spp. from cetaceans may be of pathophysiological concern.

  12. Identifying Minefields and Verifying Clearance: Adapting Statistical Methods for UXO Target Detection

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Gilbert, Richard O.; O'Brien, Robert F.; Wilson, John E.

    2003-09-01

    It may not be feasible to completely survey large tracts of land suspected of containing minefields. It is desirable to develop a characterization protocol that will confidently identify minefields within these large land tracts if they exist. Naturally, surveying areas of greatest concern and most likely locations would be necessary but will not provide the needed confidence that an unknown minefield had not eluded detection. Once minefields are detected, methods are needed to bound the area that will require detailed mine detection surveys. The US Department of Defense Strategic Environmental Research and Development Program (SERDP) is sponsoring the development ofmore » statistical survey methods and tools for detecting potential UXO targets. These methods may be directly applicable to demining efforts. Statistical methods are employed to determine the optimal geophysical survey transect spacing to have confidence of detecting target areas of a critical size, shape, and anomaly density. Other methods under development determine the proportion of a land area that must be surveyed to confidently conclude that there are no UXO present. Adaptive sampling schemes are also being developed as an approach for bounding the target areas. These methods and tools will be presented and the status of relevant research in this area will be discussed.« less

  13. A target development program for beamhole spallation neutron sources in the megawatt range

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bauer, G.S.; Atchison, F.

    1995-10-01

    Spallation sources as an alternative to fission neutron sources have been operating successfully up to 160 kW of beam power. With the next generation of these facilities aiming at the medium power range between 0.5 and 5 MW, loads on the targets will be high enough to make present experience of little relevance. With the 0.6 MW continuous facility SINQ under construction, and a 5 MW pulsed facility (ESS) under study in Europe, a research and development program is about to be started which aimes at assessing the limits of stationary and moving solid targets and the feasibility and potentialmore » benefits of flowing liquid metal targets. Apart from theoretical work and examination of existing irradiated material, including used targets from ISIS, it is intended to take advantage of the SINQ solid rod target design to improve the relevant data base by building the target in such a way that individual rods can be equipped as irradiation capsules.« less

  14. Effect of inherent location uncertainty on detection of stationary targets in noisy image sequences.

    PubMed

    Manjeshwar, R M; Wilson, D L

    2001-01-01

    The effect of inherent location uncertainty on the detection of stationary targets was determined in noisy image sequences. Targets were thick and thin projected cylinders mimicking arteries, catheters, and guide wires in medical imaging x-ray fluoroscopy. With the use of an adaptive forced-choice method, detection contrast sensitivity (the inverse of contrast) was measured both with and without marker cues that directed the attention of observers to the target location. With the probability correct clamped at 80%, contrast sensitivity increased an average of 77% when the marker was added to the thin-cylinder target. There was an insignificant effect on the thick cylinder. The large enhancement with the thin cylinder was obtained even though the target was located exactly in the center of a small panel, giving observers the impression that it was well localized. Psychometric functions consisting of d' plotted as a function of the square root of the signal-energy-to-noise-ratio gave a positive x intercept for the case of the thin cylinder without a marker. This x intercept, characteristic of uncertainty in other types of detection experiments, disappeared when the marker was added or when the thick cylinder was used. Inherent location uncertainty was further characterized by using four different markers with varying proximity to the target. Visual detection by human observers increased monotonically as the markers better localized the target. Human performance was modeled as a matched-filter detector with an uncertainty in the placement of the template. The removal of a location cue was modeled by introducing a location uncertainty of approximately equals 0.4 mm on the display device or only 7 microm on the retina, a size on the order of a single photoreceptor field. We conclude that detection is affected by target location uncertainty on the order of cellular dimensions, an observation with important implications for detection mechanisms in humans. In medical

  15. A novel infrared small moving target detection method based on tracking interest points under complicated background

    NASA Astrophysics Data System (ADS)

    Dong, Xiabin; Huang, Xinsheng; Zheng, Yongbin; Bai, Shengjian; Xu, Wanying

    2014-07-01

    Infrared moving target detection is an important part of infrared technology. We introduce a novel infrared small moving target detection method based on tracking interest points under complicated background. Firstly, Difference of Gaussians (DOG) filters are used to detect a group of interest points (including the moving targets). Secondly, a sort of small targets tracking method inspired by Human Visual System (HVS) is used to track these interest points for several frames, and then the correlations between interest points in the first frame and the last frame are obtained. Last, a new clustering method named as R-means is proposed to divide these interest points into two groups according to the correlations, one is target points and another is background points. In experimental results, the target-to-clutter ratio (TCR) and the receiver operating characteristics (ROC) curves are computed experimentally to compare the performances of the proposed method and other five sophisticated methods. From the results, the proposed method shows a better discrimination of targets and clutters and has a lower false alarm rate than the existing moving target detection methods.

  16. An Efficient Moving Target Detection Algorithm Based on Sparsity-Aware Spectrum Estimation

    PubMed Central

    Shen, Mingwei; Wang, Jie; Wu, Di; Zhu, Daiyin

    2014-01-01

    In this paper, an efficient direct data domain space-time adaptive processing (STAP) algorithm for moving targets detection is proposed, which is achieved based on the distinct spectrum features of clutter and target signals in the angle-Doppler domain. To reduce the computational complexity, the high-resolution angle-Doppler spectrum is obtained by finding the sparsest coefficients in the angle domain using the reduced-dimension data within each Doppler bin. Moreover, we will then present a knowledge-aided block-size detection algorithm that can discriminate between the moving targets and the clutter based on the extracted spectrum features. The feasibility and effectiveness of the proposed method are validated through both numerical simulations and raw data processing results. PMID:25222035

  17. Reliable motion detection of small targets in video with low signal-to-clutter ratios

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Nichols, S.A.; Naylor, R.B.

    1995-07-01

    Studies show that vigilance decreases rapidly after several minutes when human operators are required to search live video for infrequent intrusion detections. Therefore, there is a need for systems which can automatically detect targets in live video and reserve the operator`s attention for assessment only. Thus far, automated systems have not simultaneously provided adequate detection sensitivity, false alarm suppression, and ease of setup when used in external, unconstrained environments. This unsatisfactory performance can be exacerbated by poor video imagery with low contrast, high noise, dynamic clutter, image misregistration, and/or the presence of small, slow, or erratically moving targets. This papermore » describes a highly adaptive video motion detection and tracking algorithm which has been developed as part of Sandia`s Advanced Exterior Sensor (AES) program. The AES is a wide-area detection and assessment system for use in unconstrained exterior security applications. The AES detection and tracking algorithm provides good performance under stressing data and environmental conditions. Features of the algorithm include: reliable detection with negligible false alarm rate of variable velocity targets having low signal-to-clutter ratios; reliable tracking of targets that exhibit motion that is non-inertial, i.e., varies in direction and velocity; automatic adaptation to both infrared and visible imagery with variable quality; and suppression of false alarms caused by sensor flaws and/or cutouts.« less

  18. A General Purpose Feature Extractor for Light Detection and Ranging Data

    DTIC Science & Technology

    2010-11-17

    datasets, and the 3D MIT DARPA Urban Challenge dataset. Keywords: SLAM ; LIDARs ; feature detection; uncertainty estimates; descriptors 1. Introduction The...November 2010 Abstract: Feature extraction is a central step of processing Light Detection and Ranging ( LIDAR ) data. Existing detectors tend to exploit...detector for both 2D and 3D LIDAR data that is applicable to virtually any environment. Our method adapts classic feature detection methods from the image

  19. Unsupervised Spatial Event Detection in Targeted Domains with Applications to Civil Unrest Modeling

    PubMed Central

    Zhao, Liang; Chen, Feng; Dai, Jing; Hua, Ting; Lu, Chang-Tien; Ramakrishnan, Naren

    2014-01-01

    Twitter has become a popular data source as a surrogate for monitoring and detecting events. Targeted domains such as crime, election, and social unrest require the creation of algorithms capable of detecting events pertinent to these domains. Due to the unstructured language, short-length messages, dynamics, and heterogeneity typical of Twitter data streams, it is technically difficult and labor-intensive to develop and maintain supervised learning systems. We present a novel unsupervised approach for detecting spatial events in targeted domains and illustrate this approach using one specific domain, viz. civil unrest modeling. Given a targeted domain, we propose a dynamic query expansion algorithm to iteratively expand domain-related terms, and generate a tweet homogeneous graph. An anomaly identification method is utilized to detect spatial events over this graph by jointly maximizing local modularity and spatial scan statistics. Extensive experiments conducted in 10 Latin American countries demonstrate the effectiveness of the proposed approach. PMID:25350136

  20. Scale invariant SURF detector and automatic clustering segmentation for infrared small targets detection

    NASA Astrophysics Data System (ADS)

    Zhang, Haiying; Bai, Jiaojiao; Li, Zhengjie; Liu, Yan; Liu, Kunhong

    2017-06-01

    The detection and discrimination of infrared small dim targets is a challenge in automatic target recognition (ATR), because there is no salient information of size, shape and texture. Many researchers focus on mining more discriminative information of targets in temporal-spatial. However, such information may not be available with the change of imaging environments, and the targets size and intensity keep changing in different imaging distance. So in this paper, we propose a novel research scheme using density-based clustering and backtracking strategy. In this scheme, the speeded up robust feature (SURF) detector is applied to capture candidate targets in single frame at first. And then, these points are mapped into one frame, so that target traces form a local aggregation pattern. In order to isolate the targets from noises, a newly proposed density-based clustering algorithm, fast search and find of density peak (FSFDP for short), is employed to cluster targets by the spatial intensive distribution. Two important factors of the algorithm, percent and γ , are exploited fully to determine the clustering scale automatically, so as to extract the trace with highest clutter suppression ratio. And at the final step, a backtracking algorithm is designed to detect and discriminate target trace as well as to eliminate clutter. The consistence and continuity of the short-time target trajectory in temporal-spatial is incorporated into the bounding function to speed up the pruning. Compared with several state-of-arts methods, our algorithm is more effective for the dim targets with lower signal-to clutter ratio (SCR). Furthermore, it avoids constructing the candidate target trajectory searching space, so its time complexity is limited to a polynomial level. The extensive experimental results show that it has superior performance in probability of detection (Pd) and false alarm suppressing rate aiming at variety of complex backgrounds.

  1. Doppler imaging with dual-detection full-range frequency domain optical coherence tomography

    PubMed Central

    Meemon, Panomsak; Lee, Kye-Sung; Rolland, Jannick P.

    2010-01-01

    Most of full-range techniques for Frequency Domain Optical Coherence Tomography (FD-OCT) reported to date utilize the phase relation between consecutive axial lines to reconstruct a complex interference signal and hence may exhibit degradation in either mirror image suppression performance or detectable velocity dynamic range or both when monitoring a moving sample such as flow activity. We have previously reported a technique of mirror image removal by simultaneous detection of the quadrature components of a complex spectral interference called a Dual-Detection Frequency Domain OCT (DD-FD-OCT) [Opt. Lett. 35, 1058-1060 (2010)]. The technique enables full range imaging without any loss of acquisition speed and is intrinsically less sensitive to phase errors generated by involuntary movements of the subject. In this paper, we demonstrate the application of the DD-FD-OCT to a phase-resolved Doppler imaging without degradation in either mirror image suppression performance or detectable velocity dynamic range that were observed in other full-range Doppler methods. In order to accommodate for Doppler imaging, we have developed a fiber-based DD-FD-OCT that more efficiently utilizes the source power compared with the previous free-space DD-FD-OCT. In addition, the velocity sensitivity of the phase-resolved DD-FD-OCT was investigated, and the relation between the measured Doppler phase shift and set flow velocity of a flow phantom was verified. Finally, we demonstrate the Doppler imaging using the DD-FD-OCT in a biological sample. PMID:21258488

  2. Demonstration of Detection and Ranging Using Solvable Chaos

    NASA Technical Reports Server (NTRS)

    Corron, Ned J.; Stahl, Mark T.; Blakely, Jonathan N.

    2013-01-01

    Acoustic experiments demonstrate a novel approach to ranging and detection that exploits the properties of a solvable chaotic oscillator. This nonlinear oscillator includes an ordinary differential equation and a discrete switching condition. The chaotic waveform generated by this hybrid system is used as the transmitted waveform. The oscillator admits an exact analytic solution that can be written as the linear convolution of binary symbols and a single basis function. This linear representation enables coherent reception using a simple analog matched filter and without need for digital sampling or signal processing. An audio frequency implementation of the transmitter and receiver is described. Successful acoustic ranging measurements are presented to demonstrate the viability of the approach.

  3. A statistical approach to detection of copy number variations in PCR-enriched targeted sequencing data.

    PubMed

    Demidov, German; Simakova, Tamara; Vnuchkova, Julia; Bragin, Anton

    2016-10-22

    Multiplex polymerase chain reaction (PCR) is a common enrichment technique for targeted massive parallel sequencing (MPS) protocols. MPS is widely used in biomedical research and clinical diagnostics as the fast and accurate tool for the detection of short genetic variations. However, identification of larger variations such as structure variants and copy number variations (CNV) is still being a challenge for targeted MPS. Some approaches and tools for structural variants detection were proposed, but they have limitations and often require datasets of certain type, size and expected number of amplicons affected by CNVs. In the paper, we describe novel algorithm for high-resolution germinal CNV detection in the PCR-enriched targeted sequencing data and present accompanying tool. We have developed a machine learning algorithm for the detection of large duplications and deletions in the targeted sequencing data generated with PCR-based enrichment step. We have performed verification studies and established the algorithm's sensitivity and specificity. We have compared developed tool with other available methods applicable for the described data and revealed its higher performance. We showed that our method has high specificity and sensitivity for high-resolution copy number detection in targeted sequencing data using large cohort of samples.

  4. Measuring target detection performance in paradigms with high event rates.

    PubMed

    Bendixen, Alexandra; Andersen, Søren K

    2013-05-01

    Combining behavioral and neurophysiological measurements inevitably implies mutual constraints, such as when the neurophysiological measurement requires fast-paced stimulus presentation and hence the attribution of a behavioral response to a particular preceding stimulus becomes ambiguous. We develop and test a method for validly assessing behavioral detection performance in spite of this ambiguity. We examine four approaches taken in the literature to treat such situations. We analytically derive a new variant of computing the classical parameters of signal detection theory, hit and false alarm rates, adapted to fast-paced paradigms. Each of the previous approaches shows specific shortcomings (susceptibility towards response window choice, biased estimates of behavioral detection performance). Superior performance of our new approach is demonstrated for both simulated and empirical behavioral data. Further evidence is provided by reliable correspondence between behavioral performance and the N2b component as an electrophysiological indicator of target detection. The appropriateness of our approach is substantiated by both theoretical and empirical arguments. We demonstrate an easy-to-implement solution for measuring target detection performance independent of the rate of event presentation. Thus overcoming the measurement bias of previous approaches, our method will help to clarify the behavioral relevance of different measures of cortical activation. Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  5. Aircraft target detection algorithm based on high resolution spaceborne SAR imagery

    NASA Astrophysics Data System (ADS)

    Zhang, Hui; Hao, Mengxi; Zhang, Cong; Su, Xiaojing

    2018-03-01

    In this paper, an image classification algorithm for airport area is proposed, which based on the statistical features of synthetic aperture radar (SAR) images and the spatial information of pixels. The algorithm combines Gamma mixture model and MRF. The algorithm using Gamma mixture model to obtain the initial classification result. Pixel space correlation based on the classification results are optimized by the MRF technique. Additionally, morphology methods are employed to extract airport (ROI) region where the suspected aircraft target samples are clarified to reduce the false alarm and increase the detection performance. Finally, this paper presents the plane target detection, which have been verified by simulation test.

  6. New target and detection methods: active detectors

    NASA Astrophysics Data System (ADS)

    Mittig, W.; Savajols, H.; Demonchy, C. E.; Giot, L.; Roussel-Chomaz, P.; Wang, H.; Ter-Akopian, G.; Fomichev, A.; Golovkov, M. S.; Stepansov, S.; Wolski, R.; Alamanos, N.; Drouart, A.; Gillibert, A.; Lapoux, V.; Pollacco, E.

    2003-07-01

    The study of nuclei far from stability interacting with simple target nuclei, such as protons, deuterons, 3He and 4He implies the use of inverse kinematics. The very special kinematics, together with the low intensities of the beams calls for special techniques. In july 2002 we tested a new detector, in which the detector gas is the target. This allows in principle a 4π solid angle of the detection, and a big effective target thickness without loss of resolution. The detector developped, called Maya, used isobuthane C4H10 as gas in present tests, and other gases are possible. The multiplexed electronics of more than 1000channels allows the reconstruction of the events occuring between the incoming particle and the detector gas atoms in 3D. Here we were interested in the elastic scattering of 8He on protons for the study of the isobaric analogue states (IAS) of 9He. The beam, in this case, is stopped in the detector. The resonance energy is determined by the place of interaction and the energy of the recoiling proton. The design of the detector is shown, together with some preliminary results are discussed.

  7. Camouflage target reconnaissance based on hyperspectral imaging technology

    NASA Astrophysics Data System (ADS)

    Hua, Wenshen; Guo, Tong; Liu, Xun

    2015-08-01

    Efficient camouflaged target reconnaissance technology makes great influence on modern warfare. Hyperspectral images can provide large spectral range and high spectral resolution, which are invaluable in discriminating between camouflaged targets and backgrounds. Hyperspectral target detection and classification technology are utilized to achieve single class and multi-class camouflaged targets reconnaissance respectively. Constrained energy minimization (CEM), a widely used algorithm in hyperspectral target detection, is employed to achieve one class camouflage target reconnaissance. Then, support vector machine (SVM), a classification method, is proposed to achieve multi-class camouflage target reconnaissance. Experiments have been conducted to demonstrate the efficiency of the proposed method.

  8. Growth Outcomes of Preterm Infants Exposed to Different Oxygen Saturation Target Ranges from Birth

    PubMed Central

    Navarrete, Cristina T.; Wrage, Lisa A.; Carlo, Waldemar A.; Walsh, Michele C.; Rich, Wade; Gantz, Marie G.; Das, Abhik; Schibler, Kurt; Newman, Nancy S.; Piazza, Anthony J.; Poindexter, Brenda B.; Shankaran, Seetha; Sánchez, Pablo J.; Morris, Brenda H.; Frantz, Ivan D.; Van Meurs, Krisa P.; Cotten, C. Michael; Ehrenkranz, Richard A.; Bell, Edward F.; Watterberg, Kristi L.; Higgins, Rosemary D.; Duara, Shahnaz

    2017-01-01

    Objective To test whether infants randomized to a lower oxygen saturation (SpO2) target range while on supplemental oxygen from birth will have better growth velocity from birth to 36 weeks postmenstrual age (PMA), and less growth failure at 36 weeks PMA and 18–22 months corrected age. Study design We evaluated a subgroup of 810 preterm infants from the Surfactant, Positive Pressure, and Oxygenation Randomized Trial, randomized at birth to lower (85–89%, n=402, GA 26 ± 1wk, BW 839 ± 186 g) or higher (91–95%, n=408, GA 26 ± 1wk, BW 840 ± 191 g) SpO2 target ranges. Anthropometric measures were obtained at birth, postnatal days 7, 14, 21, and 28; then at 32 and 36 weeks PMA, and 18–22 months corrected age. Growth velocities were estimated using the exponential method and analyzed using linear mixed models. Poor growth outcome, defined as weight < 10th percentile at 36 weeks PMA and 18–22 months corrected age, was compared across the two treatment groups using robust Poisson regression. Results Growth outcomes including growth at 36 weeks PMA and 18–22 months corrected age, as well as growth velocity were similar in the lower and higher SpO2 target groups. Conclusion Targeting different oxygen saturation ranges between 85% and 95% from birth did not impact growth velocity or reduce growth failure in preterm infants. PMID:27344218

  9. The Dynamic Range Paradox: A Central Auditory Model of Intensity Change Detection

    PubMed Central

    Simpson, Andrew J.R.; Reiss, Joshua D.

    2013-01-01

    In this paper we use empirical loudness modeling to explore a perceptual sub-category of the dynamic range problem of auditory neuroscience. Humans are able to reliably report perceived intensity (loudness), and discriminate fine intensity differences, over a very large dynamic range. It is usually assumed that loudness and intensity change detection operate upon the same neural signal, and that intensity change detection may be predicted from loudness data and vice versa. However, while loudness grows as intensity is increased, improvement in intensity discrimination performance does not follow the same trend and so dynamic range estimations of the underlying neural signal from loudness data contradict estimations based on intensity just-noticeable difference (JND) data. In order to account for this apparent paradox we draw on recent advances in auditory neuroscience. We test the hypothesis that a central model, featuring central adaptation to the mean loudness level and operating on the detection of maximum central-loudness rate of change, can account for the paradoxical data. We use numerical optimization to find adaptation parameters that fit data for continuous-pedestal intensity change detection over a wide dynamic range. The optimized model is tested on a selection of equivalent pseudo-continuous intensity change detection data. We also report a supplementary experiment which confirms the modeling assumption that the detection process may be modeled as rate-of-change. Data are obtained from a listening test (N = 10) using linearly ramped increment-decrement envelopes applied to pseudo-continuous noise with an overall level of 33 dB SPL. Increments with half-ramp durations between 5 and 50,000 ms are used. The intensity JND is shown to increase towards long duration ramps (p<10−6). From the modeling, the following central adaptation parameters are derived; central dynamic range of 0.215 sones, 95% central normalization, and a central loudness JND

  10. Key parameters design of an aerial target detection system on a space-based platform

    NASA Astrophysics Data System (ADS)

    Zhu, Hanlu; Li, Yejin; Hu, Tingliang; Rao, Peng

    2018-02-01

    To ensure flight safety of an aerial aircraft and avoid recurrence of aircraft collisions, a method of multi-information fusion is proposed to design the key parameter to realize aircraft target detection on a space-based platform. The key parameters of a detection wave band and spatial resolution using the target-background absolute contrast, target-background relative contrast, and signal-to-clutter ratio were determined. This study also presented the signal-to-interference ratio for analyzing system performance. Key parameters are obtained through the simulation of a specific aircraft. And the simulation results show that the boundary ground sampling distance is 30 and 35 m in the mid- wavelength infrared (MWIR) and long-wavelength infrared (LWIR) bands for most aircraft detection, and the most reasonable detection wavebands is 3.4 to 4.2 μm and 4.35 to 4.5 μm in the MWIR bands, and 9.2 to 9.8 μm in the LWIR bands. We also found that the direction of detection has a great impact on the detection efficiency, especially in MWIR bands.

  11. A Novel Method for Proximity Detection of Moving Targets Using a Large-Scale Planar Capacitive Sensor System

    PubMed Central

    Ye, Yong; Deng, Jiahao; Shen, Sanmin; Hou, Zhuo; Liu, Yuting

    2016-01-01

    A novel method for proximity detection of moving targets (with high dielectric constants) using a large-scale (the size of each sensor is 31 cm × 19 cm) planar capacitive sensor system (PCSS) is proposed. The capacitive variation with distance is derived, and a pair of electrodes in a planar capacitive sensor unit (PCSU) with a spiral shape is found to have better performance on sensitivity distribution homogeneity and dynamic range than three other shapes (comb shape, rectangular shape, and circular shape). A driving excitation circuit with a Clapp oscillator is proposed, and a capacitance measuring circuit with sensitivity of 0.21 Vp−p/pF is designed. The results of static experiments and dynamic experiments demonstrate that the voltage curves of static experiments are similar to those of dynamic experiments; therefore, the static data can be used to simulate the dynamic curves. The dynamic range of proximity detection for three projectiles is up to 60 cm, and the results of the following static experiments show that the PCSU with four neighboring units has the highest sensitivity (the sensitivities of other units are at least 4% lower); when the attack angle decreases, the intensity of sensor signal increases. This proposed method leads to the design of a feasible moving target detector with simple structure and low cost, which can be applied in the interception system. PMID:27196905

  12. Algorithm for Automatic Detection, Localization and Characterization of Magnetic Dipole Targets Using the Laser Scalar Gradiometer

    DTIC Science & Technology

    2016-06-01

    TECHNICAL REPORT Algorithm for Automatic Detection, Localization and Characterization of Magnetic Dipole Targets Using the Laser Scalar...Automatic Detection, Localization and Characterization of Magnetic Dipole Targets Using the Laser Scalar Gradiometer Leon Vaizer, Jesse Angle, Neil...of Magnetic Dipole Targets Using LSG i June 2016 TABLE OF CONTENTS INTRODUCTION

  13. Trifunctional molecular beacon-mediated quadratic amplification for highly sensitive and rapid detection of mercury(II) ion with tunable dynamic range.

    PubMed

    Zhao, Yue; Liu, Huaqing; Chen, Feng; Bai, Min; Zhao, Junwu; Zhao, Yongxi

    2016-12-15

    Analyses of target with low abundance or concentration varying over many orders of magnitude are severe challenges faced by numerous assay methods due to their modest sensitivity and limited dynamic range. Here, we introduce a homogeneous and rapid quadratic polynomial amplification strategy through rational design of a trifunctional molecular beacon, which serves as not only a reporter molecule but also a bridge to couple two stage amplification modules without adding any reaction components or process other than basic linear amplification. As a test bed for our studies, we took mercury(II) ion as an example and obtained a high sensitivity with detection limit down to 200 pM within 30min. In order to create a tunable dynamic range, homotropic allostery is employed to modulate the target specific binding. When the number of metal binding site varies from 1 to 3, signal response is programmed accordingly with useful dynamic range spanning 50, 25 and 10 folds, respectively. Furthermore, the applicability of the proposed method in river water and biological samples are successfully verified with good recovery and reproducibility, indicating considerable potential for its practicality in complex real samples. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. Targeted Feature Detection for Data-Dependent Shotgun Proteomics.

    PubMed

    Weisser, Hendrik; Choudhary, Jyoti S

    2017-08-04

    Label-free quantification of shotgun LC-MS/MS data is the prevailing approach in quantitative proteomics but remains computationally nontrivial. The central data analysis step is the detection of peptide-specific signal patterns, called features. Peptide quantification is facilitated by associating signal intensities in features with peptide sequences derived from MS2 spectra; however, missing values due to imperfect feature detection are a common problem. A feature detection approach that directly targets identified peptides (minimizing missing values) but also offers robustness against false-positive features (by assigning meaningful confidence scores) would thus be highly desirable. We developed a new feature detection algorithm within the OpenMS software framework, leveraging ideas and algorithms from the OpenSWATH toolset for DIA/SRM data analysis. Our software, FeatureFinderIdentification ("FFId"), implements a targeted approach to feature detection based on information from identified peptides. This information is encoded in an MS1 assay library, based on which ion chromatogram extraction and detection of feature candidates are carried out. Significantly, when analyzing data from experiments comprising multiple samples, our approach distinguishes between "internal" and "external" (inferred) peptide identifications (IDs) for each sample. On the basis of internal IDs, two sets of positive (true) and negative (decoy) feature candidates are defined. A support vector machine (SVM) classifier is then trained to discriminate between the sets and is subsequently applied to the "uncertain" feature candidates from external IDs, facilitating selection and confidence scoring of the best feature candidate for each peptide. This approach also enables our algorithm to estimate the false discovery rate (FDR) of the feature selection step. We validated FFId based on a public benchmark data set, comprising a yeast cell lysate spiked with protein standards that provide a known

  15. Random Access Memories: A New Paradigm for Target Detection in High Resolution Aerial Remote Sensing Images.

    PubMed

    Zou, Zhengxia; Shi, Zhenwei

    2018-03-01

    We propose a new paradigm for target detection in high resolution aerial remote sensing images under small target priors. Previous remote sensing target detection methods frame the detection as learning of detection model + inference of class-label and bounding-box coordinates. Instead, we formulate it from a Bayesian view that at inference stage, the detection model is adaptively updated to maximize its posterior that is determined by both training and observation. We call this paradigm "random access memories (RAM)." In this paradigm, "Memories" can be interpreted as any model distribution learned from training data and "random access" means accessing memories and randomly adjusting the model at detection phase to obtain better adaptivity to any unseen distribution of test data. By leveraging some latest detection techniques e.g., deep Convolutional Neural Networks and multi-scale anchors, experimental results on a public remote sensing target detection data set show our method outperforms several other state of the art methods. We also introduce a new data set "LEarning, VIsion and Remote sensing laboratory (LEVIR)", which is one order of magnitude larger than other data sets of this field. LEVIR consists of a large set of Google Earth images, with over 22 k images and 10 k independently labeled targets. RAM gives noticeable upgrade of accuracy (an mean average precision improvement of 1% ~ 4%) of our baseline detectors with acceptable computational overhead.

  16. Staircase-scene-based nonuniformity correction in aerial point target detection systems.

    PubMed

    Huo, Lijun; Zhou, Dabiao; Wang, Dejiang; Liu, Rang; He, Bin

    2016-09-01

    Focal-plane arrays (FPAs) are often interfered by heavy fixed-pattern noise, which severely degrades the detection rate and increases the false alarms in airborne point target detection systems. Thus, high-precision nonuniformity correction is an essential preprocessing step. In this paper, a new nonuniformity correction method is proposed based on a staircase scene. This correction method can compensate for the nonlinear response of the detector and calibrate the entire optical system with computational efficiency and implementation simplicity. Then, a proof-of-concept point target detection system is established with a long-wave Sofradir FPA. Finally, the local standard deviation of the corrected image and the signal-to-clutter ratio of the Airy disk of a Boeing B738 are measured to evaluate the performance of the proposed nonuniformity correction method. Our experimental results demonstrate that the proposed correction method achieves high-quality corrections.

  17. Three plot correlation-based small infrared target detection in dense sun-glint environment for infrared search and track

    NASA Astrophysics Data System (ADS)

    Kim, Sungho; Choi, Byungin; Kim, Jieun; Kwon, Soon; Kim, Kyung-Tae

    2012-05-01

    This paper presents a separate spatio-temporal filter based small infrared target detection method to address the sea-based infrared search and track (IRST) problem in dense sun-glint environment. It is critical to detect small infrared targets such as sea-skimming missiles or asymmetric small ships for national defense. On the sea surface, sun-glint clutters degrade the detection performance. Furthermore, if we have to detect true targets using only three images with a low frame rate camera, then the problem is more difficult. We propose a novel three plot correlation filter and statistics based clutter reduction method to achieve robust small target detection rate in dense sun-glint environment. We validate the robust detection performance of the proposed method via real infrared test sequences including synthetic targets.

  18. Laser radar range and detection performance for MEMS corner cube retroreflector arrays

    NASA Astrophysics Data System (ADS)

    Grasso, Robert J.; Odhner, Jefferson E.; Stewart, Hamilton; McDaniel, Robert V.

    2004-12-01

    BAE SYSTEMS reports on a program to characterize the performance of MEMS corner cube retroreflector arrays under laser illumination. These arrays have significant military and commercial application in the areas of: 1) target identification; 2) target tracking; 3) target location; 4) identification friend-or-foe (IFF); 5) parcel tracking, and; 6) search and rescue assistance. BAE SYSTEMS has theoretically determined the feasibility of these devices to learn if sufficient signal-to-noise performance exists to permit a cooperative laser radar sensor to be considered for device location and interrogation. Results indicate that modest power-apertures are required to achieve SNR performance consistent with high probability of detection and low false alarm rates.

  19. Laser radar range and detection performance for MEMS corner cube retroreflector arrays

    NASA Astrophysics Data System (ADS)

    Grasso, Robert J.; Jost, Steven R.; Smith, M. J.; McDaniel, Robert V.

    2004-01-01

    BAE SYSTEMS reports on a program to characterize the performance of MEMS corner cube retroreflector arrays under laser illumination. These arrays have significant military and commercial application in the areas of: (1) target identification; (2) target tracking; (3) target location; (4) identification friend-or-foe (IFF); (5) parcel tracking, and; (6) search and rescue assistance. BAE SYSTEMS has theoretically determined the feasibility of these devices to learn if sufficient signal-to-noise performance exists to permit a cooperative laser radar sensor to be considered for device location and interrogation. Results indicate that modest power-apertures are required to achieve SNR performance consistent with high probability of detection and low false alarm rates.

  20. Target-protecting dumbbell molecular probe against exonucleases digestion for sensitive detection of ATP and streptavidin.

    PubMed

    Chen, Jinyang; Liu, Yucheng; Ji, Xinghu; He, Zhike

    2016-09-15

    In this work, a versatile dumbbell molecular (DM) probe was designed and employed in the sensitively homogeneous bioassay. In the presence of target molecule, the DM probe was protected from the digestion of exonucleases. Subsequently, the protected DM probe specifically bound to the intercalation dye and resulted in obvious fluorescence signal which was used to determine the target molecule in return. This design allows specific and versatile detection of diverse targets with easy operation and no sophisticated fluorescence labeling. Integrating the idea of target-protecting DM probe with adenosine triphosphate (ATP) involved ligation reaction, the DM probe with 5'-end phosphorylation was successfully constructed for ATP detection, and the limitation of detection was found to be 4.8 pM. Thanks to its excellent selectivity and sensitivity, this sensing strategy was used to detect ATP spiked in human serum as well as cellular ATP. Moreover, the proposed strategy was also applied in the visual detection of ATP in droplet-based microfluidic platform with satisfactory results. Similarly, combining the principle of target-protecting DM probe with streptavidin (SA)-biotin interaction, the DM probe with 3'-end biotinylation was developed for selective and sensitive SA determination, which demonstrated the robustness and versatility of this design. Copyright © 2016 Elsevier B.V. All rights reserved.

  1. SPIDERS: selection of spectroscopic targets using AGN candidates detected in all-sky X-ray surveys

    NASA Astrophysics Data System (ADS)

    Dwelly, T.; Salvato, M.; Merloni, A.; Brusa, M.; Buchner, J.; Anderson, S. F.; Boller, Th.; Brandt, W. N.; Budavári, T.; Clerc, N.; Coffey, D.; Del Moro, A.; Georgakakis, A.; Green, P. J.; Jin, C.; Menzel, M.-L.; Myers, A. D.; Nandra, K.; Nichol, R. C.; Ridl, J.; Schwope, A. D.; Simm, T.

    2017-07-01

    SPIDERS (SPectroscopic IDentification of eROSITA Sources) is a Sloan Digital Sky Survey IV (SDSS-IV) survey running in parallel to the Extended Baryon Oscillation Spectroscopic Survey (eBOSS) cosmology project. SPIDERS will obtain optical spectroscopy for large numbers of X-ray-selected active galactic nuclei (AGN) and galaxy cluster members detected in wide-area eROSITA, XMM-Newton and ROSAT surveys. We describe the methods used to choose spectroscopic targets for two sub-programmes of SPIDERS X-ray selected AGN candidates detected in the ROSAT All Sky and the XMM-Newton Slew surveys. We have exploited a Bayesian cross-matching algorithm, guided by priors based on mid-IR colour-magnitude information from the Wide-field Infrared Survey Explorer survey, to select the most probable optical counterpart to each X-ray detection. We empirically demonstrate the high fidelity of our counterpart selection method using a reference sample of bright well-localized X-ray sources collated from XMM-Newton, Chandra and Swift-XRT serendipitous catalogues, and also by examining blank-sky locations. We describe the down-selection steps which resulted in the final set of SPIDERS-AGN targets put forward for spectroscopy within the eBOSS/TDSS/SPIDERS survey, and present catalogues of these targets. We also present catalogues of ˜12 000 ROSAT and ˜1500 XMM-Newton Slew survey sources that have existing optical spectroscopy from SDSS-DR12, including the results of our visual inspections. On completion of the SPIDERS programme, we expect to have collected homogeneous spectroscopic redshift information over a footprint of ˜7500 deg2 for >85 per cent of the ROSAT and XMM-Newton Slew survey sources having optical counterparts in the magnitude range 17 < r < 22.5, producing a large and highly complete sample of bright X-ray-selected AGN suitable for statistical studies of AGN evolution and clustering.

  2. Automatically detect and track infrared small targets with kernel Fukunaga-Koontz transform and Kalman prediction.

    PubMed

    Liu, Ruiming; Liu, Erqi; Yang, Jie; Zeng, Yong; Wang, Fanglin; Cao, Yuan

    2007-11-01

    Fukunaga-Koontz transform (FKT), stemming from principal component analysis (PCA), is used in many pattern recognition and image-processing fields. It cannot capture the higher-order statistical property of natural images, so its detection performance is not satisfying. PCA has been extended into kernel PCA in order to capture the higher-order statistics. However, thus far there have been no researchers who have definitely proposed kernel FKT (KFKT) and researched its detection performance. For accurately detecting potential small targets from infrared images, we first extend FKT into KFKT to capture the higher-order statistical properties of images. Then a framework based on Kalman prediction and KFKT, which can automatically detect and track small targets, is developed. Results of experiments show that KFKT outperforms FKT and the proposed framework is competent to automatically detect and track infrared point targets.

  3. Automatically detect and track infrared small targets with kernel Fukunaga-Koontz transform and Kalman prediction

    NASA Astrophysics Data System (ADS)

    Liu, Ruiming; Liu, Erqi; Yang, Jie; Zeng, Yong; Wang, Fanglin; Cao, Yuan

    2007-11-01

    Fukunaga-Koontz transform (FKT), stemming from principal component analysis (PCA), is used in many pattern recognition and image-processing fields. It cannot capture the higher-order statistical property of natural images, so its detection performance is not satisfying. PCA has been extended into kernel PCA in order to capture the higher-order statistics. However, thus far there have been no researchers who have definitely proposed kernel FKT (KFKT) and researched its detection performance. For accurately detecting potential small targets from infrared images, we first extend FKT into KFKT to capture the higher-order statistical properties of images. Then a framework based on Kalman prediction and KFKT, which can automatically detect and track small targets, is developed. Results of experiments show that KFKT outperforms FKT and the proposed framework is competent to automatically detect and track infrared point targets.

  4. Automatic detection of small surface targets with electro-optical sensors in a harbor environment

    NASA Astrophysics Data System (ADS)

    Bouma, Henri; de Lange, Dirk-Jan J.; van den Broek, Sebastiaan P.; Kemp, Rob A. W.; Schwering, Piet B. W.

    2008-10-01

    In modern warfare scenarios naval ships must operate in coastal environments. These complex environments, in bays and narrow straits, with cluttered littoral backgrounds and many civilian ships may contain asymmetric threats of fast targets, such as rhibs, cabin boats and jet-skis. Optical sensors, in combination with image enhancement and automatic detection, assist an operator to reduce the response time, which is crucial for the protection of the naval and land-based supporting forces. In this paper, we present our work on automatic detection of small surface targets which includes multi-scale horizon detection and robust estimation of the background intensity. To evaluate the performance of our detection technology, data was recorded with both infrared and visual-light cameras in a coastal zone and in a harbor environment. During these trials multiple small targets were used. Results of this evaluation are shown in this paper.

  5. Hand-held optical imager (Gen-2): improved instrumentation and target detectability

    PubMed Central

    Gonzalez, Jean; DeCerce, Joseph; Erickson, Sarah J.; Martinez, Sergio L.; Nunez, Annie; Roman, Manuela; Traub, Barbara; Flores, Cecilia A.; Roberts, Seigbeh M.; Hernandez, Estrella; Aguirre, Wenceslao; Kiszonas, Richard

    2012-01-01

    Abstract. Hand-held optical imagers are developed by various researchers towards reflectance-based spectroscopic imaging of breast cancer. Recently, a Gen-1 handheld optical imager was developed with capabilities to perform two-dimensional (2-D) spectroscopic as well as three-dimensional (3-D) tomographic imaging studies. However, the imager was bulky with poor surface contact (∼30%) along curved tissues, and limited sensitivity to detect targets consistently. Herein, a Gen-2 hand-held optical imager that overcame the above limitations of the Gen-1 imager has been developed and the instrumentation described. The Gen-2 hand-held imager is less bulky, portable, and has improved surface contact (∼86%) on curved tissues. Additionally, the forked probe head design is capable of simultaneous bilateral reflectance imaging of both breast tissues, and also transillumination imaging of a single breast tissue. Experimental studies were performed on tissue phantoms to demonstrate the improved sensitivity in detecting targets using the Gen-2 imager. The improved instrumentation of the Gen-2 imager allowed detection of targets independent of their location with respect to the illumination points, unlike in Gen-1 imager. The developed imager has potential for future clinical breast imaging with enhanced sensitivity, via both reflectance and transillumination imaging. PMID:23224163

  6. Drivers' detection of roadside targets when driving vehicles with three headlight systems during high beam activation.

    PubMed

    Reagan, Ian J; Brumbelow, Matthew L

    2017-02-01

    A previous open-road experiment indicated that curve-adaptive HID headlights driven with low beams improved drivers' detection of low conspicuity targets compared with fixed halogen and fixed HID low beam systems. The current study used the same test environment and targets to assess whether drivers' detection of targets was affected by the same three headlight systems when using high beams. Twenty drivers search and responded for 60 8×12inch targets of high or low reflectance that were distributed evenly across straight and curved road sections as they drove at 30 mph on an unlit two-lane rural road. The results indicate that target detection performance was generally similar across the three systems. However, one interaction indicated that drivers saw low reflectance targets on straight road sections from further away when driving with the fixed halogen high beam condition compared with curve-adaptive HID high beam headlights and also indicated a possible benefit for the curve-adaptive HID high beams for high reflectance targets placed on the inside of curves. The results of this study conflict with the previous study of low beams, which showed a consistent benefit for the curve-adaptive HID low beams for targets placed on curves compared with fixed HID and fixed halogen low beam conditions. However, a comparison of mean detection distances from the two studies indicated uniformly longer mean target detection distances for participants driving with high beams and implicates the potential visibility benefits for systems that optimize proper high beam use. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array.

    PubMed

    Li, Miao; Li, Jun; Zhou, Yiyu

    2015-12-08

    The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts-MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing.

  8. Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array

    PubMed Central

    Li, Miao; Li, Jun; Zhou, Yiyu

    2015-01-01

    The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts—MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing. PMID:26670234

  9. Laser-ranging scanning system to observe topographical deformations of volcanoes.

    PubMed

    Aoki, T; Takabe, M; Mizutani, K; Itabe, T

    1997-02-20

    We have developed a laser-ranging system to observe the topographical structure of volcanoes. This system can be used to measure the distance to a target by a laser and shows the three-dimensional topographical structure of a volcano with an accuracy of 30 cm. This accuracy is greater than that of a typical laser-ranging system that uses a corner-cube reflector as a target because the reflected light jitters as a result of inclination and unevenness of the target ground surface. However, this laser-ranging system is useful for detecting deformations of topographical features in which placement of a reflector is difficult, such as in volcanic regions.

  10. Programmable near-infrared ranging system

    DOEpatents

    Everett, Jr., Hobart R.

    1989-01-01

    A high angular resolution ranging system particularly suitable for indoor plications involving mobile robot navigation and collision avoidance uses a programmable array of light emitters that can be sequentially incremented by a microprocessor. A plurality of adjustable level threshold detectors are used in an optical receiver for detecting the threshold level of the light echoes produced when light emitted from one or more of the emitters is reflected by a target or object in the scan path of the ranging system.

  11. Real-time multi-target ranging based on chaotic polarization laser radars in the drive-response VCSELs.

    PubMed

    Zhong, Dongzhou; Xu, Geliang; Luo, Wei; Xiao, Zhenzhen

    2017-09-04

    According to the principle of complete chaos synchronization and the theory of Hilbert phase transformation, we propose a novel real-time multi-target ranging scheme by using chaotic polarization laser radar in the drive-response vertical-cavity surface-emitting lasers (VCSELs). In the scheme, to ensure each polarization component (PC) of the master VCSEL (MVCSEL) to be synchronized steadily with that of the slave VCSEL, the output x-PC and y-PC from the MVCSEL in the drive system and those in the response system are modulated by the linear electro-optic effect simultaneously. Under this condition, by simulating the influences of some key parameters of the system on the synchronization quality and the relative errors of the two-target ranging, related operating parameters can be optimized. The x-PC and the y-PC, as two chaotic radar sources, are used to implement the real-time ranging for two targets. It is found that the measured distances of the two targets at arbitrary position exhibit strong real-time stability and only slight jitter. Their resolutions are up to millimeters, and their relative errors are very small and less than 2.7%.

  12. Detection of dim targets in multiple environments

    NASA Astrophysics Data System (ADS)

    Mirsky, Grace M.; Woods, Matthew; Grasso, Robert J.

    2013-10-01

    The proliferation of a wide variety of weapons including Anti-Aircraft Artillery (AAA), rockets, and small arms presents a substantial threat to both military and civilian aircraft. To address this ever-present threat, Northrop Grumman has assessed unguided threat phenomenology to understand the underlying physical principles for detection. These principles, based upon threat transit through the atmosphere, exploit a simple phenomenon universal to all objects moving through an atmosphere comprised of gaseous media to detect and track the threat in the presence of background and clutter. Threat detection has rapidly become a crucial component of aircraft survivability systems that provide situational awareness to the crew. It is particularly important to platforms which may spend a majority of their time at low altitudes and within the effective range of a large variety of weapons. Detection of these threats presents a unique challenge as this class of threat typically has a dim signature coupled with a short duration. Correct identification of each of the threat components (muzzle flash and projectile) is important to determine trajectory and intent while minimizing false alarms and maintaining a high detection probability in all environments.

  13. Target Detection of Quantum Illumination Receiver Based on Photon-subtracted Entanglement State

    NASA Astrophysics Data System (ADS)

    Chi, Jiao; Liu, HongJun; Huang, Nan; Wang, ZhaoLu

    2017-12-01

    We theoretically propose a quantum illumination receiver based on the ideal photon-subtracted two-mode squeezed state (PSTMSS) to efficiently detect the noise-hidden target. This receiver is generated by applying an optical parametric amplifier (OPA) to the cross correlation detection. With analyzing the output performance, it is found that OPA as a preposition technology of the receiver can contribute to the PSTMSS by significantly reducing the error probability than that of the general two-mode squeezed state (TMSS). Comparing with TMSS, the signal-to-noise ratio of quantum illumination based on ideal PSTMSS and OPA is improved more than 4 dB under an optimal gain of OPA. This work may provide a potential improvement in the application of accurate target detection when two kinds of resource have the identical real squeezing parameter.

  14. Multisensor fusion for 3D target tracking using track-before-detect particle filter

    NASA Astrophysics Data System (ADS)

    Moshtagh, Nima; Romberg, Paul M.; Chan, Moses W.

    2015-05-01

    This work presents a novel fusion mechanism for estimating the three-dimensional trajectory of a moving target using images collected by multiple imaging sensors. The proposed projective particle filter avoids the explicit target detection prior to fusion. In projective particle filter, particles that represent the posterior density (of target state in a high-dimensional space) are projected onto the lower-dimensional observation space. Measurements are generated directly in the observation space (image plane) and a marginal (sensor) likelihood is computed. The particles states and their weights are updated using the joint likelihood computed from all the sensors. The 3D state estimate of target (system track) is then generated from the states of the particles. This approach is similar to track-before-detect particle filters that are known to perform well in tracking dim and stealthy targets in image collections. Our approach extends the track-before-detect approach to 3D tracking using the projective particle filter. The performance of this measurement-level fusion method is compared with that of a track-level fusion algorithm using the projective particle filter. In the track-level fusion algorithm, the 2D sensor tracks are generated separately and transmitted to a fusion center, where they are treated as measurements to the state estimator. The 2D sensor tracks are then fused to reconstruct the system track. A realistic synthetic scenario with a boosting target was generated, and used to study the performance of the fusion mechanisms.

  15. Hyperspectral data collection for the assessment of target detection algorithms: the Viareggio 2013 trial

    NASA Astrophysics Data System (ADS)

    Rossi, Alessandro; Acito, Nicola; Diani, Marco; Corsini, Giovanni; De Ceglie, Sergio Ugo; Riccobono, Aldo; Chiarantini, Leandro

    2014-10-01

    Airborne hyperspectral imagery is valuable for military and civilian applications, such as target identification, detection of anomalies and changes within multiple acquisitions. In target detection (TD) applications, the performance assessment of different algorithms is an important and critical issue. In this context, the small number of public available hyperspectral data motivated us to perform an extensive measurement campaign including various operating scenarios. The campaign was organized by CISAM in cooperation with University of Pisa, Selex ES and CSSN-ITE, and it was conducted in Viareggio, Italy in May, 2013. The Selex ES airborne hyperspectral sensor SIM.GA was mounted on board of an airplane to collect images over different sites in the morning and afternoon of two subsequent days. This paper describes the hyperspectral data collection of the trial. Four different sites were set up, representing a complex urban scenario, two parking lots and a rural area. Targets with dimensions comparable to the sensor ground resolution were deployed in the sites to reproduce different operating situations. An extensive ground truth documentation completes the data collection. Experiments to test anomalous change detection techniques were set up changing the position of the deployed targets. Search and rescue scenarios were simulated to evaluate the performance of anomaly detection algorithms. Moreover, the reflectance signatures of the targets were measured on the ground to perform spectral matching in varying atmospheric and illumination conditions. The paper presents some preliminary results that show the effectiveness of hyperspectral data exploitation for the object detection tasks of interest in this work.

  16. Swept-source based, single-shot, multi-detectable velocity range Doppler optical coherence tomography

    PubMed Central

    Meemon, Panomsak; Rolland, Jannick P.

    2010-01-01

    Phase-Resolved Doppler Optical Coherence Tomography (PR-DOCT) allows visualization and characterization of the location, direction, velocity, and profile of flow activity embedded in a static sample structure. The detectable Velocity Dynamic Range (VDR) of each particular PR-DOCT system is governed by a detectable Doppler phase shift, a flow angle, and an acquisition time interval used to determine the Doppler phase shift. In general, the lower boundary of the detectable Doppler phase shift is limited by the phase stability of the system, while the upper boundary is limited by the π phase ambiguity. For a given range of detectable Doppler phase shift, shortening the acquisition duration will increase not only the maximum detectable velocity but unfortunately also the minimum detectable velocity, which may lead to the invisibility of a slow flow. In this paper, we present an alternative acquisition scheme for PR-DOCT that extends the lower limit of the velocity dynamic range, while maintaining the maximum detectable velocity, hence increasing the overall VDR of PR-DOCT system. The essence of the approach is to implement a technique of multi-scale measurement to simultaneously acquire multiple VDRs in a single measurement. We demonstrate an example of implementation of the technique in a dual VDR DOCT, where two Doppler maps having different detectable VDRs were simultaneously detected, processed, and displayed in real time. One was a fixed VDR DOCT capable of measuring axial velocity of up to 10.9 mm/s without phase unwrapping. The other was a variable VDR DOCT capable of adjusting its detectable VDR to reveal slow flow information down to 11.3 μm/s. The technique is shown to effectively extend the overall detectable VDR of the PR-DOCT system. Examples of real time Doppler imaging of an African frog tadpole are demonstrated using the dual-VDR DOCT system. PMID:21258521

  17. Human target acquisition performance

    NASA Astrophysics Data System (ADS)

    Teaney, Brian P.; Du Bosq, Todd W.; Reynolds, Joseph P.; Thompson, Roger; Aghera, Sameer; Moyer, Steven K.; Flug, Eric; Espinola, Richard; Hixson, Jonathan

    2012-06-01

    The battlefield has shifted from armored vehicles to armed insurgents. Target acquisition (identification, recognition, and detection) range performance involving humans as targets is vital for modern warfare. The acquisition and neutralization of armed insurgents while at the same time minimizing fratricide and civilian casualties is a mounting concern. U.S. Army RDECOM CERDEC NVESD has conducted many experiments involving human targets for infrared and reflective band sensors. The target sets include human activities, hand-held objects, uniforms & armament, and other tactically relevant targets. This paper will define a set of standard task difficulty values for identification and recognition associated with human target acquisition performance.

  18. Small maritime target detection through false color fusion

    NASA Astrophysics Data System (ADS)

    Toet, Alexander; Wu, Tirui

    2008-04-01

    We present an algorithm that produces a fused false color representation of a combined multiband IR and visual imaging system for maritime applications. Multispectral IR imaging techniques are increasingly deployed in maritime operations, to detect floating mines or to find small dinghies and swimmers during search and rescue operations. However, maritime backgrounds usually contain a large amount of clutter that severely hampers the detection of small targets. Our new algorithm deploys the correlation between the target signatures in two different IR frequency bands (3-5 and 8-12 μm) to construct a fused IR image with a reduced amount of clutter. The fused IR image is then combined with a visual image in a false color RGB representation for display to a human operator. The algorithm works as follows. First, both individual IR bands are filtered with a morphological opening top-hat transform to extract small details. Second, a common image is extracted from the two filtered IR bands, and assigned to the red channel of an RGB image. Regions of interest that appear in both IR bands remain in this common image, while most uncorrelated noise details are filtered out. Third, the visual band is assigned to the green channel and, after multiplication with a constant (typically 1.6) also to the blue channel. Fourth, the brightness and colors of this intermediate false color image are renormalized by adjusting its first order statistics to those of a representative reference scene. The result of these four steps is a fused color image, with naturalistic colors (bluish sky and grayish water), in which small targets are clearly visible.

  19. Two-dimensional hidden semantic information model for target saliency detection and eyetracking identification

    NASA Astrophysics Data System (ADS)

    Wan, Weibing; Yuan, Lingfeng; Zhao, Qunfei; Fang, Tao

    2018-01-01

    Saliency detection has been applied to the target acquisition case. This paper proposes a two-dimensional hidden Markov model (2D-HMM) that exploits the hidden semantic information of an image to detect its salient regions. A spatial pyramid histogram of oriented gradient descriptors is used to extract features. After encoding the image by a learned dictionary, the 2D-Viterbi algorithm is applied to infer the saliency map. This model can predict fixation of the targets and further creates robust and effective depictions of the targets' change in posture and viewpoint. To validate the model with a human visual search mechanism, two eyetrack experiments are employed to train our model directly from eye movement data. The results show that our model achieves better performance than visual attention. Moreover, it indicates the plausibility of utilizing visual track data to identify targets.

  20. Practical target location and accuracy indicator in digital close range photogrammetry using consumer grade cameras

    NASA Astrophysics Data System (ADS)

    Moriya, Gentaro; Chikatsu, Hirofumi

    2011-07-01

    Recently, pixel numbers and functions of consumer grade digital camera are amazingly increasing by modern semiconductor and digital technology, and there are many low-priced consumer grade digital cameras which have more than 10 mega pixels on the market in Japan. In these circumstances, digital photogrammetry using consumer grade cameras is enormously expected in various application fields. There is a large body of literature on calibration of consumer grade digital cameras and circular target location. Target location with subpixel accuracy had been investigated as a star tracker issue, and many target location algorithms have been carried out. It is widely accepted that the least squares models with ellipse fitting is the most accurate algorithm. However, there are still problems for efficient digital close range photogrammetry. These problems are reconfirmation of the target location algorithms with subpixel accuracy for consumer grade digital cameras, relationship between number of edge points along target boundary and accuracy, and an indicator for estimating the accuracy of normal digital close range photogrammetry using consumer grade cameras. With this motive, an empirical testing of several algorithms for target location with subpixel accuracy and an indicator for estimating the accuracy are investigated in this paper using real data which were acquired indoors using 7 consumer grade digital cameras which have 7.2 mega pixels to 14.7 mega pixels.

  1. Target Detection and Classification Using Seismic and PIR Sensors

    DTIC Science & Technology

    2012-06-01

    time series analysis via wavelet - based partitioning,” Signal Process...regard, this paper presents a wavelet - based method for target detection and classification. The proposed method has been validated on data sets of...The work reported in this paper makes use of a wavelet - based feature extraction method , called Symbolic Dynamic Filtering (SDF) [12]–[14]. The

  2. CD33 monoclonal antibody conjugated Au cluster nano-bioprobe for targeted flow-cytometric detection of acute myeloid leukaemia

    NASA Astrophysics Data System (ADS)

    Retnakumari, Archana; Jayasimhan, Jasusri; Chandran, Parwathy; Menon, Deepthy; Nair, Shantikumar; Mony, Ullas; Koyakutty, Manzoor

    2011-07-01

    Protein stabilized gold nanoclusters (Au-NCs) are biocompatible, near-infrared (NIR) emitting nanosystems having a wide range of biomedical applications. Here, we report the development of a Au-NC based targeted fluorescent nano-bioprobe for the flow-cytometric detection of acute myeloid leukaemia (AML) cells. Au-NCs with ~ 25-28 atoms showing bright red-NIR fluorescence (600-750 nm) and average size of ~ 0.8 nm were prepared by bovine serum albumin assisted reduction-cum-stabilization in aqueous phase. The protein protected clusters were conjugated with monoclonal antibody against CD33 myeloid antigen, which is overexpressed in ~ 99.2% of the primitive population of AML cells, as confirmed by immunophenotyping using flow cytometry. Au-NC-CD33 conjugates having average size of ~ 12 nm retained bright fluorescence over an extended duration of ~ a year, as the albumin protein protects Au-NCs against degradation. Nanotoxicity studies revealed excellent biocompatibility of Au-NC conjugates, as they showed no adverse effect on the cell viability and inflammatory response. Target specificity of the conjugates for detecting CD33 expressing AML cells (KG1a) in flow cytometry showed specific staining of ~ 95.4% of leukaemia cells within 1-2 h compared to a non-specific uptake of ~ 8.2% in human peripheral blood cells (PBMCs) which are CD33low. The confocal imaging also demonstrated the targeted uptake of CD33 conjugated Au-NCs by leukaemia cells, thus confirming the flow cytometry results. This study demonstrates that novel nano-bioprobes can be developed using protein protected fluorescent nanoclusters of Au for the molecular receptor targeted flow cytometry based detection and imaging of cancer cells.

  3. SU-F-J-197: A Novel Intra-Beam Range Detection and Adaptation Strategy for Particle Therapy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Chen, M; Jiang, S; Shao, Y

    2016-06-15

    Purpose: In-vivo range detection/verification is crucial in particle therapy for effective and safe delivery. The state-of-art techniques are not sufficient for in-vivo on-line range verification due to conflicts among patient dose, signal statistics and imaging time. We propose a novel intra-beam range detection and adaptation strategy for particle therapy. Methods: This strategy uses the planned mid-range spots as probing beams without adding extra radiation to patients. Such choice of probing beams ensures the Bragg peaks to remain inside the tumor even with significant range variation from the plan. It offers sufficient signal statistics for in-beam positron emission tomography (PET) duemore » to high positron activity of therapeutic dose. The probing beam signal can be acquired and reconstructed using in-beam PET that allows for delineation of the Bragg peaks and detection of range shift with ease of detection enabled by single-layered spots. If the detected range shift is within a pre-defined tolerance, the remaining spots will be delivered as the original plan. Otherwise, a fast re-optimization using range-shifted beamlets and accounting for the probing beam dose is applied to consider the tradeoffs posed by the online anatomy. Simulated planning and delivery studies were used to demonstrate the effectiveness of the proposed techniques. Results: Simulations with online range variations due to shifts of various foreign objects into the beam path showed successful delineation of the Bragg peaks as a result of delivering probing beams. Without on-line delivery adaptation, dose distribution was significantly distorted. In contrast, delivery adaptation incorporating detected range shift recovered well the planned dose. Conclusion: The proposed intra-beam range detection and adaptation utilizing the planned mid-range spots as probing beams, which illuminate the beam range with strong and accurate PET signals, is a safe, practical, yet effective approach to

  4. Switchable DNA interfaces for the highly sensitive detection of label-free DNA targets.

    PubMed

    Rant, Ulrich; Arinaga, Kenji; Scherer, Simon; Pringsheim, Erika; Fujita, Shozo; Yokoyama, Naoki; Tornow, Marc; Abstreiter, Gerhard

    2007-10-30

    We report a method to detect label-free oligonucleotide targets. The conformation of surface-tethered probe nucleic acids is modulated by alternating electric fields, which cause the molecules to extend away from or fold onto the biased surface. Binding (hybridization) of targets to the single-stranded probes results in a pronounced enhancement of the layer-height modulation amplitude, monitored optically in real time. The method features an exceptional detection limit of <3 x 10(8) bound targets per cm(2) sensor area. Single base-pair mismatches in the sequences of DNA complements may readily be identified; moreover, binding kinetics and binding affinities can be determined with high accuracy. When driving the DNA to oscillate at frequencies in the kHz regime, distinct switching kinetics are revealed for single- and double-stranded DNA. Molecular dynamics are used to identify the binding state of molecules according to their characteristic kinetic fingerprints by using a chip-compatible detection format.

  5. Switchable DNA interfaces for the highly sensitive detection of label-free DNA targets

    PubMed Central

    Rant, Ulrich; Arinaga, Kenji; Scherer, Simon; Pringsheim, Erika; Fujita, Shozo; Yokoyama, Naoki; Tornow, Marc; Abstreiter, Gerhard

    2007-01-01

    We report a method to detect label-free oligonucleotide targets. The conformation of surface-tethered probe nucleic acids is modulated by alternating electric fields, which cause the molecules to extend away from or fold onto the biased surface. Binding (hybridization) of targets to the single-stranded probes results in a pronounced enhancement of the layer-height modulation amplitude, monitored optically in real time. The method features an exceptional detection limit of <3 × 108 bound targets per cm2 sensor area. Single base-pair mismatches in the sequences of DNA complements may readily be identified; moreover, binding kinetics and binding affinities can be determined with high accuracy. When driving the DNA to oscillate at frequencies in the kHz regime, distinct switching kinetics are revealed for single- and double-stranded DNA. Molecular dynamics are used to identify the binding state of molecules according to their characteristic kinetic fingerprints by using a chip-compatible detection format. PMID:17951434

  6. Flash trajectory imaging of target 3D motion

    NASA Astrophysics Data System (ADS)

    Wang, Xinwei; Zhou, Yan; Fan, Songtao; He, Jun; Liu, Yuliang

    2011-03-01

    We present a flash trajectory imaging technique which can directly obtain target trajectory and realize non-contact measurement of motion parameters by range-gated imaging and time delay integration. Range-gated imaging gives the range of targets and realizes silhouette detection which can directly extract targets from complex background and decrease the complexity of moving target image processing. Time delay integration increases information of one single frame of image so that one can directly gain the moving trajectory. In this paper, we have studied the algorithm about flash trajectory imaging and performed initial experiments which successfully obtained the trajectory of a falling badminton. Our research demonstrates that flash trajectory imaging is an effective approach to imaging target trajectory and can give motion parameters of moving targets.

  7. Tree-species range shifts in a changing climate: detecting, modeling, assisting

    Treesearch

    Louis R. Iverson; Donald McKenzie

    2013-01-01

    In these times of rapidly changing climate, the science of detecting and modeling shifts in the ranges of tree species is advancing of necessity. We briefly review the current state of the science on several fronts. First, we review current and historical evidence for shifting ranges and migration. Next, we review two broad categories of methods, focused on the spatial...

  8. Autonomous long-range open area fire detection and reporting

    NASA Astrophysics Data System (ADS)

    Engelhaupt, Darell E.; Reardon, Patrick J.; Blackwell, Lisa; Warden, Lance; Ramsey, Brian D.

    2005-03-01

    Approximately 5 billion dollars in US revenue was lost in 2003 due to open area fires. In addition many lives are lost annually. Early detection of open area fires is typically performed by manned observatories, random reporting and aerial surveillance. Optical IR flame detectors have been developed previously. They typically have experienced high false alarms and low flame detection sensitivity due to interference from solar and other causes. Recently a combination of IR detectors has been used in a two or three color mode to reduce false alarms from solar, or background sources. A combination of ultra-violet C (UVC) and near infra-red (NIR) detectors has also been developed recently for flame discrimination. Relatively solar-blind basic detectors are now available but typically detect at only a few tens of meters at ~ 1 square meter fuel flame. We quantify the range and solar issues for IR and visible detectors and qualitatively define UV sensor requirements in terms of the mode of operation, collection area issues and flame signal output by combustion photochemistry. We describe innovative flame signal collection optics for multiple wavelengths using UV and IR as low false alarm detection of open area fires at long range (8-10 km/m2) in daylight (or darkness). A circular array detector and UV-IR reflective and refractive devices including cylindrical or toroidal lens elements for the IR are described. The dispersion in a refractive cylindrical IR lens characterizes the fire and allows a stationary line or circle generator to locate the direction and different flame IR "colors" from a wide FOV. The line generator will produce spots along the line corresponding to the fire which can be discriminated with a linear detector. We demonstrate prototype autonomous sensors with RF digital reporting from various sites.

  9. Targeted Feature Detection for Data-Dependent Shotgun Proteomics

    PubMed Central

    2017-01-01

    Label-free quantification of shotgun LC–MS/MS data is the prevailing approach in quantitative proteomics but remains computationally nontrivial. The central data analysis step is the detection of peptide-specific signal patterns, called features. Peptide quantification is facilitated by associating signal intensities in features with peptide sequences derived from MS2 spectra; however, missing values due to imperfect feature detection are a common problem. A feature detection approach that directly targets identified peptides (minimizing missing values) but also offers robustness against false-positive features (by assigning meaningful confidence scores) would thus be highly desirable. We developed a new feature detection algorithm within the OpenMS software framework, leveraging ideas and algorithms from the OpenSWATH toolset for DIA/SRM data analysis. Our software, FeatureFinderIdentification (“FFId”), implements a targeted approach to feature detection based on information from identified peptides. This information is encoded in an MS1 assay library, based on which ion chromatogram extraction and detection of feature candidates are carried out. Significantly, when analyzing data from experiments comprising multiple samples, our approach distinguishes between “internal” and “external” (inferred) peptide identifications (IDs) for each sample. On the basis of internal IDs, two sets of positive (true) and negative (decoy) feature candidates are defined. A support vector machine (SVM) classifier is then trained to discriminate between the sets and is subsequently applied to the “uncertain” feature candidates from external IDs, facilitating selection and confidence scoring of the best feature candidate for each peptide. This approach also enables our algorithm to estimate the false discovery rate (FDR) of the feature selection step. We validated FFId based on a public benchmark data set, comprising a yeast cell lysate spiked with protein standards

  10. Multispectral photoacoustic decomposition with localized regularization for detecting targeted contrast agent

    NASA Astrophysics Data System (ADS)

    Tavakoli, Behnoosh; Chen, Ying; Guo, Xiaoyu; Kang, Hyun Jae; Pomper, Martin; Boctor, Emad M.

    2015-03-01

    Targeted contrast agents can improve the sensitivity of imaging systems for cancer detection and monitoring the treatment. In order to accurately detect contrast agent concentration from photoacoustic images, we developed a decomposition algorithm to separate photoacoustic absorption spectrum into components from individual absorbers. In this study, we evaluated novel prostate-specific membrane antigen (PSMA) targeted agents for imaging prostate cancer. Three agents were synthesized through conjugating PSMA-targeting urea with optical dyes ICG, IRDye800CW and ATTO740 respectively. In our preliminary PA study, dyes were injected in a thin wall plastic tube embedded in water tank. The tube was illuminated with pulsed laser light using a tunable Q-switch ND-YAG laser. PA signal along with the B-mode ultrasound images were detected with a diagnostic ultrasound probe in orthogonal mode. PA spectrums of each dye at 0.5 to 20 μM concentrations were estimated using the maximum PA signal extracted from images which are obtained at illumination wavelengths of 700nm-850nm. Subsequently, we developed nonnegative linear least square optimization method along with localized regularization to solve the spectral unmixing. The algorithm was tested by imaging mixture of those dyes. The concentration of each dye was estimated with about 20% error on average from almost all mixtures albeit the small separation between dyes spectrums.

  11. Multi-dimensional position sensor using range detectors

    DOEpatents

    Vann, Charles S.

    2000-01-01

    A small, non-contact optical sensor uses ranges and images to detect its relative position to an object in up to six degrees of freedom. The sensor has three light emitting range detectors which illuminate a target and can be used to determine distance and two tilt angles. A camera located between the three range detectors senses the three remaining degrees of freedom, two translations and one rotation. Various range detectors, with different light sources, e.g. lasers and LEDs, different collection options, and different detection schemes, e.g. diminishing return and time of flight can be used. This sensor increases the capability and flexibility of computer controlled machines, e.g. it can instruct a robot how to adjust automatically to different positions and orientations of a part.

  12. 33 CFR 334.200 - Chesapeake Bay, Point Lookout to Cedar Point; aerial and surface firing range and target area, U...

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... Cedar Point; aerial and surface firing range and target area, U.S. Naval Air Station, Patuxent River... Chesapeake Bay, Point Lookout to Cedar Point; aerial and surface firing range and target area, U.S. Naval Air...) The regulations. (i) Through navigation of surface craft outside the target areas will be permitted at...

  13. Bias-Corrected Targeted Next-Generation Sequencing for Rapid, Multiplexed Detection of Actionable Alterations in Cell-Free DNA from Advanced Lung Cancer Patients.

    PubMed

    Paweletz, Cloud P; Sacher, Adrian G; Raymond, Chris K; Alden, Ryan S; O'Connell, Allison; Mach, Stacy L; Kuang, Yanan; Gandhi, Leena; Kirschmeier, Paul; English, Jessie M; Lim, Lee P; Jänne, Pasi A; Oxnard, Geoffrey R

    2016-02-15

    Tumor genotyping is a powerful tool for guiding non-small cell lung cancer (NSCLC) care; however, comprehensive tumor genotyping can be logistically cumbersome. To facilitate genotyping, we developed a next-generation sequencing (NGS) assay using a desktop sequencer to detect actionable mutations and rearrangements in cell-free plasma DNA (cfDNA). An NGS panel was developed targeting 11 driver oncogenes found in NSCLC. Targeted NGS was performed using a novel methodology that maximizes on-target reads, and minimizes artifact, and was validated on DNA dilutions derived from cell lines. Plasma NGS was then blindly performed on 48 patients with advanced, progressive NSCLC and a known tumor genotype, and explored in two patients with incomplete tumor genotyping. NGS could identify mutations present in DNA dilutions at ≥ 0.4% allelic frequency with 100% sensitivity/specificity. Plasma NGS detected a broad range of driver and resistance mutations, including ALK, ROS1, and RET rearrangements, HER2 insertions, and MET amplification, with 100% specificity. Sensitivity was 77% across 62 known driver and resistance mutations from the 48 cases; in 29 cases with common EGFR and KRAS mutations, sensitivity was similar to droplet digital PCR. In two cases with incomplete tumor genotyping, plasma NGS rapidly identified a novel EGFR exon 19 deletion and a missed case of MET amplification. Blinded to tumor genotype, this plasma NGS approach detected a broad range of targetable genomic alterations in NSCLC with no false positives including complex mutations like rearrangements and unexpected resistance mutations such as EGFR C797S. Through use of widely available vacutainers and a desktop sequencing platform, this assay has the potential to be implemented broadly for patient care and translational research. ©2015 American Association for Cancer Research.

  14. Bias-corrected targeted next-generation sequencing for rapid, multiplexed detection of actionable alterations in cell-free DNA from advanced lung cancer patients

    PubMed Central

    Paweletz, Cloud P.; Sacher, Adrian G.; Raymond, Chris K.; Alden, Ryan S.; O'Connell, Allison; Mach, Stacy L.; Kuang, Yanan; Gandhi, Leena; Kirschmeier, Paul; English, Jessie M.; Lim, Lee P.; Jänne, Pasi A.; Oxnard, Geoffrey R.

    2015-01-01

    Purpose Tumor genotyping is a powerful tool for guiding non-small cell lung cancer (NSCLC) care, however comprehensive tumor genotyping can be logistically cumbersome. To facilitate genotyping, we developed a next-generation sequencing (NGS) assay using a desktop sequencer to detect actionable mutations and rearrangements in cell-free plasma DNA (cfDNA). Experimental Design An NGS panel was developed targeting 11 driver oncogenes found in NSCLC. Targeted NGS was performed using a novel methodology that maximizes on-target reads, and minimizes artifact, and was validated on DNA dilutions derived from cell lines. Plasma NGS was then blindly performed on 48 patients with advanced, progressive NSCLC and a known tumor genotype, and explored in two patients with incomplete tumor genotyping. Results NGS could identify mutations present in DNA dilutions at ≥0.4% allelic frequency with 100% sensitivity/specificity. Plasma NGS detected a broad range of driver and resistance mutations, including ALK, ROS1, and RET rearrangements, HER2 insertions, and MET amplification, with 100% specificity. Sensitivity was 77% across 62 known driver and resistance mutations from the 48 cases; in 29 cases with common EGFR and KRAS mutations, sensitivity was similar to droplet digital PCR. In two cases with incomplete tumor genotyping, plasma NGS rapidly identified a novel EGFR exon 19 deletion and a missed case of MET amplification. Conclusion Blinded to tumor genotype, this plasma NGS approach detected a broad range of targetable genomic alterations in NSCLC with no false positives including complex mutations like rearrangements and unexpected resistance mutations such as EGFR C797S. Through use of widely available vacutainers and a desktop sequencing platform, this assay has the potential to be implemented broadly for patient care and translational research. PMID:26459174

  15. Aspects of detection and tracking of ground targets from an airborne EO/IR sensor

    NASA Astrophysics Data System (ADS)

    Balaji, Bhashyam; Sithiravel, Rajiv; Daya, Zahir; Kirubarajan, Thiagalingam

    2015-05-01

    An airborne EO/IR (electro-optical/infrared) camera system comprises of a suite of sensors, such as a narrow and wide field of view (FOV) EO and mid-wave IR sensors. EO/IR camera systems are regularly employed on military and search and rescue aircrafts. The EO/IR system can be used to detect and identify objects rapidly in daylight and at night, often with superior performance in challenging conditions such as fog. There exist several algorithms for detecting potential targets in the bearing elevation grid. The nonlinear filtering problem is one of estimation of the kinematic parameters from bearing and elevation measurements from a moving platform. In this paper, we developed a complete model for the state of a target as detected by an airborne EO/IR system and simulated a typical scenario with single target with 1 or 2 airborne sensors. We have demonstrated the ability to track the target with `high precision' and noted the improvement from using two sensors on a single platform or on separate platforms. The performance of the Extended Kalman filter (EKF) is investigated on simulated data. Image/video data collected from an IR sensor on an airborne platform are processed using an image tracking by detection algorithm.

  16. Infrared images target detection based on background modeling in the discrete cosine domain

    NASA Astrophysics Data System (ADS)

    Ye, Han; Pei, Jihong

    2018-02-01

    Background modeling is the critical technology to detect the moving target for video surveillance. Most background modeling techniques are aimed at land monitoring and operated in the spatial domain. A background establishment becomes difficult when the scene is a complex fluctuating sea surface. In this paper, the background stability and separability between target are analyzed deeply in the discrete cosine transform (DCT) domain, on this basis, we propose a background modeling method. The proposed method models each frequency point as a single Gaussian model to represent background, and the target is extracted by suppressing the background coefficients. Experimental results show that our approach can establish an accurate background model for seawater, and the detection results outperform other background modeling methods in the spatial domain.

  17. A neural mechanism for detecting the distance of a selected target by modulating the FM sweep rate of biosonar in echolocation of bat.

    PubMed

    Kamata, Eigo; Inoue, Satoru; Zheng, MeiHong; Kashimori, Yoshiki; Kambara, Takeshi

    2004-01-01

    Most species of bats making echolocation use frequency modulated (FM) ultrasonic pulses to measure the distance to targets. These bats detect with a high accuracy the arrival time differences between emitted pulses and their echoes generated by targets. In order to clarify the neural mechanism for echolocation, we present neural model of inferior colliculus (IC), medial geniculate body (MGB) and auditory cortex (AC) along which information of echo delay times is processed. The bats increase the downward frequency sweep rate of emitted FM pulse as they approach the target. The functional role of this modulation of sweep rate is not yet clear. In order to investigate the role, we calculated the response properties of our models of IC, MGB, and AC changing the target distance and the sweep rate. We found based on the simulations that the distance of a target in various ranges may be encoded the most clearly into the activity pattern of delay time map network in AC, when the sweep rate of FM pulse used is coincided with the observed value which the bats adopt for each range of target distance.

  18. Detecting Moving Targets by Use of Soliton Resonances

    NASA Technical Reports Server (NTRS)

    Zak, Michael; Kulikov, Igor

    2003-01-01

    A proposed method of detecting moving targets in scenes that include cluttered or noisy backgrounds is based on a soliton-resonance mathematical model. The model is derived from asymptotic solutions of the cubic Schroedinger equation for a one-dimensional system excited by a position-and-time-dependent externally applied potential. The cubic Schroedinger equation has general significance for time-dependent dispersive waves. It has been used to approximate several phenomena in classical as well as quantum physics, including modulated beams in nonlinear optics, and superfluids (in particular, Bose-Einstein condensates). In the proposed method, one would take advantage of resonant interactions between (1) a soliton excited by the position-and-time-dependent potential associated with a moving target and (2) eigen-solitons, which represent dispersive waves and are solutions of the cubic Schroedinger equation for a time-independent potential.

  19. Closure Report for Corrective Action Unit 408: Bomblet Target Area Tonopah Test Range (TTR), Nevada, Revision 0

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mark Krauss

    2010-09-01

    This Closure Report (CR) presents information supporting the closure of Corrective Action Unit (CAU) 408: Bomblet Target Area (TTR), Tonopah Test Range, Nevada. This CR complies with the requirements of the Federal Facility Agreement and Consent Order that was agreed to by the State of Nevada; U.S. Department of Energy (DOE), Environmental Management; U.S. Department of Defense; and DOE, Legacy Management. Corrective Action Unit 408 is located at the Tonopah Test Range, Nevada, and consists of Corrective Action Site (CAS) TA-55-002-TAB2, Bomblet Target Areas. This CAS includes the following seven target areas: • Mid Target • Flightline Bomblet Location •more » Strategic Air Command (SAC) Target Location 1 • SAC Target Location 2 • South Antelope Lake • Tomahawk Location 1 • Tomahawk Location 2 The purpose of this CR is to provide documentation supporting the completed corrective actions and data confirming that the closure objectives for the CAS within CAU 408 were met. To achieve this, the following actions were performed: • Review the current site conditions, including the concentration and extent of contamination. • Implement any corrective actions necessary to protect human health and the environment. • Properly dispose of corrective action and investigation wastes. • Document Notice of Completion and closure of CAU 408 issued by the Nevada Division of Environmental Protection. From July 2009 through August 2010, closure activities were performed as set forth in the Streamlined Approach for Environmental Restoration Plan for CAU 408: Bomblet Target Area, Tonopah Test Range (TTR), Nevada. The purposes of the activities as defined during the data quality objectives process were as follows: • Identify and remove munitions of explosive concern (MEC) associated with DOE activities. • Investigate potential disposal pit locations. • Remove depleted uranium-contaminated fragments and soil. • Determine whether contaminants of concern

  20. Universal, colorimetric microRNA detection strategy based on target-catalyzed toehold-mediated strand displacement reaction

    NASA Astrophysics Data System (ADS)

    Park, Yeonkyung; Lee, Chang Yeol; Kang, Shinyoung; Kim, Hansol; Park, Ki Soo; Park, Hyun Gyu

    2018-02-01

    In this work, we developed a novel, label-free, and enzyme-free strategy for the colorimetric detection of microRNA (miRNA), which relies on a target-catalyzed toehold-mediated strand displacement (TMSD) reaction. The system employs a detection probe that specifically binds to the target miRNA and sequentially releases a catalyst strand (CS) intended to trigger the subsequent TMSD reaction. Thus, the presence of target miRNA releases the CS that mediates the formation of an active G-quadruplex DNAzyme which is initially caged and inactivated by a blocker strand. In addition, a fuel strand that is supplemented for the recycling of the CS promotes another TMSD reaction, consequently generating a large number of active G-quadruplex DNAzymes. As a result, a distinct colorimetric signal is produced by the ABTS oxidation promoted by the peroxidase mimicking activity of the released G-quadruplex DNAzymes. Based on this novel strategy, we successfully detected miR-141, a promising biomarker for human prostate cancer, with high selectivity. The diagnostic capability of this system was also demonstrated by reliably determining target miR-141 in human serum, showing its great potential towards real clinical applications. Importantly, the proposed approach is composed of separate target recognition and signal transduction modules. Thus, it could be extended to analyze different target miRNAs by simply redesigning the detection probe while keeping the same signal transduction module as a universal signal amplification unit, which was successfully demonstrated by analyzing another target miRNA, let-7d.

  1. Universal, colorimetric microRNA detection strategy based on target-catalyzed toehold-mediated strand displacement reaction.

    PubMed

    Park, Yeonkyung; Lee, Chang Yeol; Kang, Shinyoung; Kim, Hansol; Park, Ki Soo; Park, Hyun Gyu

    2018-02-23

    In this work, we developed a novel, label-free, and enzyme-free strategy for the colorimetric detection of microRNA (miRNA), which relies on a target-catalyzed toehold-mediated strand displacement (TMSD) reaction. The system employs a detection probe that specifically binds to the target miRNA and sequentially releases a catalyst strand (CS) intended to trigger the subsequent TMSD reaction. Thus, the presence of target miRNA releases the CS that mediates the formation of an active G-quadruplex DNAzyme which is initially caged and inactivated by a blocker strand. In addition, a fuel strand that is supplemented for the recycling of the CS promotes another TMSD reaction, consequently generating a large number of active G-quadruplex DNAzymes. As a result, a distinct colorimetric signal is produced by the ABTS oxidation promoted by the peroxidase mimicking activity of the released G-quadruplex DNAzymes. Based on this novel strategy, we successfully detected miR-141, a promising biomarker for human prostate cancer, with high selectivity. The diagnostic capability of this system was also demonstrated by reliably determining target miR-141 in human serum, showing its great potential towards real clinical applications. Importantly, the proposed approach is composed of separate target recognition and signal transduction modules. Thus, it could be extended to analyze different target miRNAs by simply redesigning the detection probe while keeping the same signal transduction module as a universal signal amplification unit, which was successfully demonstrated by analyzing another target miRNA, let-7d.

  2. Engineered Peptides for Applications in Cancer-Targeted Drug Delivery and Tumor Detection.

    PubMed

    Soudy, R; Byeon, N; Raghuwanshi, Y; Ahmed, S; Lavasanifar, A; Kaur, K

    2017-01-01

    Cancer-targeting peptides as ligands for targeted delivery of anticancer drugs or drug carriers have the potential to significantly enhance the selectivity and the therapeutic benefit of current chemotherapeutic agents. Identification of tumor-specific biomarkers like integrins, aminopeptidase N, and epidermal growth factor receptor as well as the popularity of phage display techniques along with synthetic combinatorial methods used for peptide design and structure optimization have fueled the advancement and application of peptide ligands for targeted drug delivery and tumor detection in cancer treatment, detection and guided therapy. Although considerable preclinical data have shown remarkable success in the use of tumor targeting peptides, peptides generally suffer from poor pharmacokinetics, enzymatic instability, and weak receptor affinity, and they need further structural modification before successful translation to clinics is possible. The current review gives an overview of the different engineering strategies that have been developed for peptide structure optimization to confer selectivity and stability. We also provide an update on the methods used for peptide ligand identification, and peptide- receptor interactions. Additionally, some applications for the use of peptides in targeted delivery of chemotherapeutics and diagnostics over the past 5 years are summarized. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  3. Targeted and non-targeted detection of lemon juice adulteration by LC-MS and chemometrics.

    PubMed

    Wang, Zhengfang; Jablonski, Joseph E

    2016-01-01

    Economically motivated adulteration (EMA) of lemon juice was detected by LC-MS and principal component analysis (PCA). Twenty-two batches of freshly squeezed lemon juice were adulterated by adding an aqueous solution containing 5% citric acid and 6% sucrose to pure lemon juice to obtain 30%, 60% and 100% lemon juice samples. Their total titratable acidities, °Brix and pH values were measured, and then all the lemon juice samples were subject to LC-MS analysis. Concentrations of hesperidin and eriocitrin, major phenolic components of lemon juice, were quantified. The PCA score plots for LC-MS datasets were used to preview the classification of pure and adulterated lemon juice samples. Results showed a large inherent variability in the chemical properties among 22 batches of 100% lemon juice samples. Measurement or quantitation of one or several chemical properties (targeted detection) was not effective in detecting lemon juice adulteration. However, by using the LC-MS datasets, including both chromatographic and mass spectrometric information, 100% lemon juice samples were successfully differentiated from adulterated samples containing 30% lemon juice in the PCA score plot. LC-MS coupled with chemometric analysis can be a complement to existing methods for detecting juice adulteration.

  4. Theoretical detection threshold of the proton-acoustic range verification technique.

    PubMed

    Ahmad, Moiz; Xiang, Liangzhong; Yousefi, Siavash; Xing, Lei

    2015-10-01

    Range verification in proton therapy using the proton-acoustic signal induced in the Bragg peak was investigated for typical clinical scenarios. The signal generation and detection processes were simulated in order to determine the signal-to-noise limits. An analytical model was used to calculate the dose distribution and local pressure rise (per proton) for beams of different energy (100 and 160 MeV) and spot widths (1, 5, and 10 mm) in a water phantom. In this method, the acoustic waves propagating from the Bragg peak were generated by the general 3D pressure wave equation implemented using a finite element method. Various beam pulse widths (0.1-10 μs) were simulated by convolving the acoustic waves with Gaussian kernels. A realistic PZT ultrasound transducer (5 cm diameter) was simulated with a Butterworth bandpass filter with consideration of random noise based on a model of thermal noise in the transducer. The signal-to-noise ratio on a per-proton basis was calculated, determining the minimum number of protons required to generate a detectable pulse. The maximum spatial resolution of the proton-acoustic imaging modality was also estimated from the signal spectrum. The calculated noise in the transducer was 12-28 mPa, depending on the transducer central frequency (70-380 kHz). The minimum number of protons detectable by the technique was on the order of 3-30 × 10(6) per pulse, with 30-800 mGy dose per pulse at the Bragg peak. Wider pulses produced signal with lower acoustic frequencies, with 10 μs pulses producing signals with frequency less than 100 kHz. The proton-acoustic process was simulated using a realistic model and the minimal detection limit was established for proton-acoustic range validation. These limits correspond to a best case scenario with a single large detector with no losses and detector thermal noise as the sensitivity limiting factor. Our study indicated practical proton-acoustic range verification may be feasible with approximately 5

  5. Improved Range Estimation Model for Three-Dimensional (3D) Range Gated Reconstruction

    PubMed Central

    Chua, Sing Yee; Guo, Ningqun; Tan, Ching Seong; Wang, Xin

    2017-01-01

    Accuracy is an important measure of system performance and remains a challenge in 3D range gated reconstruction despite the advancement in laser and sensor technology. The weighted average model that is commonly used for range estimation is heavily influenced by the intensity variation due to various factors. Accuracy improvement in term of range estimation is therefore important to fully optimise the system performance. In this paper, a 3D range gated reconstruction model is derived based on the operating principles of range gated imaging and time slicing reconstruction, fundamental of radiant energy, Laser Detection And Ranging (LADAR), and Bidirectional Reflection Distribution Function (BRDF). Accordingly, a new range estimation model is proposed to alleviate the effects induced by distance, target reflection, and range distortion. From the experimental results, the proposed model outperforms the conventional weighted average model to improve the range estimation for better 3D reconstruction. The outcome demonstrated is of interest to various laser ranging applications and can be a reference for future works. PMID:28872589

  6. Effects of Alzheimer’s Disease on Visual Target Detection: A “Peripheral Bias”

    PubMed Central

    Vallejo, Vanessa; Cazzoli, Dario; Rampa, Luca; Zito, Giuseppe A.; Feuerstein, Flurin; Gruber, Nicole; Müri, René M.; Mosimann, Urs P.; Nef, Tobias

    2016-01-01

    Visual exploration is an omnipresent activity in everyday life, and might represent an important determinant of visual attention deficits in patients with Alzheimer’s Disease (AD). The present study aimed at investigating visual search performance in AD patients, in particular target detection in the far periphery, in daily living scenes. Eighteen AD patients and 20 healthy controls participated in the study. They were asked to freely explore a hemispherical screen, covering ±90°, and to respond to targets presented at 10°, 30°, and 50° eccentricity, while their eye movements were recorded. Compared to healthy controls, AD patients recognized less targets appearing in the center. No difference was found in target detection in the periphery. This pattern was confirmed by the fixation distribution analysis. These results show a neglect for the central part of the visual field for AD patients and provide new insights by mean of a search task involving a larger field of view. PMID:27582704

  7. Design of short-range terahertz wave passive detecting system

    NASA Astrophysics Data System (ADS)

    Zhang, Chao; Lou, Guowei; Zhu, Li; Qian, Songsong; Li, Ting

    2016-09-01

    Based on the study of radiation and transmission characteristics on THz waveband, a short-range passive detecting system is designed. The scheme originated from microwave passive detecting system. A prototype was developed following the design of key components including antennas and a harmonic mixer. The system operated at 0.36 THz. A dual-beam Cassegrain antenna was adopted for receiving signals which radiated by object and background. Local oscillator signal was generated by frequency multiplication. Harmonic mixing is adopted for reducing local oscillator signal frequency required by half. Superheterodyne technology is employed for signal acquisition. The system implemented easily. Tests and measurements were taken, which showed that the scheme was feasible and the performance of the prototype system met the design requirements.

  8. Detection and zoonotic potential of Trichinella spp. from free-range pig farming in Greece.

    PubMed

    Papatsiros, V G; Boutsini, S; Ntousi, D; Stougiou, D; Mintza, D; Bisias, A

    2012-06-01

    Trichinellosis is a serious parasitic zoonosis, which is widely distributed around the world. Pork meat is still the predominant source of outbreaks of human trichinellosis in many countries. The aim of this study is to examine the impact of Trichinella spp. as an important risk factor on the free-range pig farming sector in Greece. In 2009, during routine testing for the detection of Trichinella larvae at slaughterhouses and the National Reference Laboratory for Parasites (NRL), a total of 826,426 pigs were tested with the magnetic stirrer method for Trichinella spp. at slaughterhouses, including 2,892 samples from free-range pigs. Two positive samples were detected: one positive for Trichinella britovi and one positive for Trichinella spp. (unspecified) in the samples from wild farmed free-range pigs. It is alarming that one of these cases was connected with clinical signs of trichinellosis in five persons of the same family in northeastern Greece, who consumed undercooked pork meat from a free-range pig farm. During 2010, a total number of 1,295,034 pigs were tested with same method, including 4,159 samples from free-range pig farms. Five positive samples for Trichinella spp. (unspecified) were detected from 4,159 free-range pigs tested by the Greek NRL. Moreover, 363 serum samples from free-range pigs were serologically tested with enzyme-linked immunosorbent assay (ELISA). Moreover, 363 serum samples from farmed free-range pigs were serologically tested with ELISA, and 15 samples were found positive. Finally, the present study is the first report of detection of T. britovi in Greece. In conclusion, based on the results of the present study, Trichinella spp. is a high-risk factor for the free-range pig farming in Greece.

  9. Mitochondrial DNA Targets Increase Sensitivity of Malaria Detection Using Loop-Mediated Isothermal Amplification ▿

    PubMed Central

    Polley, Spencer D.; Mori, Yasuyoshi; Watson, Julie; Perkins, Mark D.; González, Iveth J.; Notomi, Tsugunori; Chiodini, Peter L.; Sutherland, Colin J.

    2010-01-01

    Loop-mediated isothermal amplification (LAMP) of DNA offers the ability to detect very small quantities of pathogen DNA following minimal tissue sample processing and is thus an attractive methodology for point-of-care diagnostics. Previous attempts to diagnose malaria by the use of blood samples and LAMP have targeted the parasite small-subunit rRNA gene, with a resultant sensitivity for Plasmodium falciparum of around 100 parasites per μl. Here we describe the use of mitochondrial targets for LAMP-based detection of any Plasmodium genus parasite and of P. falciparum specifically. These new targets allow routine amplification from samples containing as few as five parasites per μl of blood. Amplification is complete within 30 to 40 min and is assessed by real-time turbidimetry, thereby offering rapid diagnosis with greater sensitivity than is achieved by the most skilled microscopist or antigen detection using lateral flow immunoassays. PMID:20554824

  10. Moving target detection for frequency agility radar by sparse reconstruction

    NASA Astrophysics Data System (ADS)

    Quan, Yinghui; Li, YaChao; Wu, Yaojun; Ran, Lei; Xing, Mengdao; Liu, Mengqi

    2016-09-01

    Frequency agility radar, with randomly varied carrier frequency from pulse to pulse, exhibits superior performance compared to the conventional fixed carrier frequency pulse-Doppler radar against the electromagnetic interference. A novel moving target detection (MTD) method is proposed for the estimation of the target's velocity of frequency agility radar based on pulses within a coherent processing interval by using sparse reconstruction. Hardware implementation of orthogonal matching pursuit algorithm is executed on Xilinx Virtex-7 Field Programmable Gata Array (FPGA) to perform sparse optimization. Finally, a series of experiments are performed to evaluate the performance of proposed MTD method for frequency agility radar systems.

  11. Moving target detection for frequency agility radar by sparse reconstruction.

    PubMed

    Quan, Yinghui; Li, YaChao; Wu, Yaojun; Ran, Lei; Xing, Mengdao; Liu, Mengqi

    2016-09-01

    Frequency agility radar, with randomly varied carrier frequency from pulse to pulse, exhibits superior performance compared to the conventional fixed carrier frequency pulse-Doppler radar against the electromagnetic interference. A novel moving target detection (MTD) method is proposed for the estimation of the target's velocity of frequency agility radar based on pulses within a coherent processing interval by using sparse reconstruction. Hardware implementation of orthogonal matching pursuit algorithm is executed on Xilinx Virtex-7 Field Programmable Gata Array (FPGA) to perform sparse optimization. Finally, a series of experiments are performed to evaluate the performance of proposed MTD method for frequency agility radar systems.

  12. Change detection in urban and rural driving scenes: Effects of target type and safety relevance on change blindness.

    PubMed

    Beanland, Vanessa; Filtness, Ashleigh J; Jeans, Rhiannon

    2017-03-01

    The ability to detect changes is crucial for safe driving. Previous research has demonstrated that drivers often experience change blindness, which refers to failed or delayed change detection. The current study explored how susceptibility to change blindness varies as a function of the driving environment, type of object changed, and safety relevance of the change. Twenty-six fully-licenced drivers completed a driving-related change detection task. Changes occurred to seven target objects (road signs, cars, motorcycles, traffic lights, pedestrians, animals, or roadside trees) across two environments (urban or rural). The contextual safety relevance of the change was systematically manipulated within each object category, ranging from high safety relevance (i.e., requiring a response by the driver) to low safety relevance (i.e., requiring no response). When viewing rural scenes, compared with urban scenes, participants were significantly faster and more accurate at detecting changes, and were less susceptible to "looked-but-failed-to-see" errors. Interestingly, safety relevance of the change differentially affected performance in urban and rural environments. In urban scenes, participants were more efficient at detecting changes with higher safety relevance, whereas in rural scenes the effect of safety relevance has marginal to no effect on change detection. Finally, even after accounting for safety relevance, change blindness varied significantly between target types. Overall the results suggest that drivers are less susceptible to change blindness for objects that are likely to change or move (e.g., traffic lights vs. road signs), and for moving objects that pose greater danger (e.g., wild animals vs. pedestrians). Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. The feature extraction of "cat-eye" targets based on bi-spectrum

    NASA Astrophysics Data System (ADS)

    Zhang, Tinghua; Fan, Guihua; Sun, Huayan

    2016-10-01

    In order to resolve the difficult problem of detection and identification of optical targets in complex background or in long-distance transmission, this paper mainly study the range profiles of "cat-eye" targets using bi-spectrum. For the problems of laser echo signal attenuation serious and low Signal-Noise Ratio (SNR), the multi-pulse laser signal echo signal detection algorithm which is based on high-order cumulant, filter processing and the accumulation of multi-pulse is proposed. This could improve the detection range effectively. In order to extract the stable characteristics of the one-dimensional range profile coming from the cat-eye targets, a method is proposed which extracts the bi-spectrum feature, and uses the singular value decomposition to simplify the calculation. Then, by extracting data samples of different distance, type and incidence angle, verify the stability of the eigenvector and effectiveness extracted by bi-spectrum.

  14. Improved training for target detection using Fukunaga-Koontz transform and distance classifier correlation filter

    NASA Astrophysics Data System (ADS)

    Elbakary, M. I.; Alam, M. S.; Aslan, M. S.

    2008-03-01

    In a FLIR image sequence, a target may disappear permanently or may reappear after some frames and crucial information such as direction, position and size related to the target are lost. If the target reappears at a later frame, it may not be tracked again because the 3D orientation, size and location of the target might be changed. To obtain information about the target before disappearing and to detect the target after reappearing, distance classifier correlation filter (DCCF) is trained manualy by selecting a number of chips randomly. This paper introduces a novel idea to eliminates the manual intervention in training phase of DCCF. Instead of selecting the training chips manually and selecting the number of the training chips randomly, we adopted the K-means algorithm to cluster the training frames and based on the number of clusters we select the training chips such that a training chip for each cluster. To detect and track the target after reappearing in the field-ofview ,TBF and DCCF are employed. The contduced experiemnts using real FLIR sequences show results similar to the traditional agorithm but eleminating the manual intervention is the advantage of the proposed algorithm.

  15. Study of pseudo noise CW diode laser for ranging applications

    NASA Technical Reports Server (NTRS)

    Lee, Hyo S.; Ramaswami, Ravi

    1992-01-01

    A new Pseudo Random Noise (PN) modulated CW diode laser radar system is being developed for real time ranging of targets at both close and large distances (greater than 10 KM) to satisy a wide range of applications: from robotics to future space applications. Results from computer modeling and statistical analysis, along with some preliminary data obtained from a prototype system, are presented. The received signal is averaged for a short time to recover the target response function. It is found that even with uncooperative targets, based on the design parameters used (200-mW laser and 20-cm receiver), accurate ranging is possible up to about 15 KM, beyond which signal to noise ratio (SNR) becomes too small for real time analog detection.

  16. Extreme soil acidity from biodegradable trap and skeet targets increases severity of pollution at shooting ranges.

    PubMed

    McTee, Michael R; Mummey, Daniel L; Ramsey, Philip W; Hinman, Nancy W

    2016-01-01

    Lead pollution at shooting ranges overshadows the potential for contamination issues from trap and skeet targets. We studied the environmental influence of targets sold as biodegradable by determining the components of the targets and sampling soils at a former sporting clay range. Targets comprised approximately 53% CaCO3, 41% S(0), and 6% modifiers, and on a molar basis, there was 2.3 times more S(0) than CaCO3. We observed a positive correlation between target cover and SO4(2-) (ρ=0.82, P<0.001), which indicated the oxidation of S(0) to H2SO4. Sulfate was negatively correlated with pH (ρ=-0.93, P<0.001) because insufficient CaCO3 existed in the targets to neutralize all the acid produced from S(0) oxidation. Plant cover decreased with decreasing soil pH (ρ=0.62, P=0.006). For sites that had pH values below 3, 24tons of lime per 1000tons of soil would be required to raise soil pH to 6.5. Lime-facilitated pH increases would be transitory because S(0) would continue to oxidize to H2SO4 until the S(0) is depleted. This study demonstrates that biodegradable trap and skeet targets can acidify soil, which has implications for increasing the mobility of Pb from shotgun pellets. Copyright © 2015 Elsevier B.V. All rights reserved.

  17. A lysosome-targetable turn-on fluorescent probe for the detection of thiols in living cells based on a 1,8-naphthalimide derivative

    NASA Astrophysics Data System (ADS)

    Liang, Beibei; Wang, Baiyan; Ma, Qiujuan; Xie, Caixia; Li, Xian; Wang, Suiping

    2018-03-01

    Biological thiols, like cysteine (Cys), homocysteine (Hcy) and glutathione (GSH), play crucial roles in biological systems and in lysosomal processes. Highly selective probes for detecting biological thiols in lysomes of living cells are rare. In this work, a lysosome-targetable turn-on fluorescent probe for the detection of thiols in living cells was designed and synthesized based on a 1,8-naphthalimide derivative. The probe has a 4-(2-aminoethyl)morpholine unit as a lysosome-targetable group and an acrylate group as the thiol recognition unit as well as a fluorescence quencher. In the absence of biothiols, the probe displayed weak fluorescence due to the photoinduced electron transfer (PET) process. Upon the addition of biothiols, the probe exhibited an enhanced fluorescence emission centered at 550 nm due to cleavage of the acrylate moiety. The probe had high selectivity toward biothiols. Moreover, the probe features fast response time, excitation in the visible region and ability of working in a wide pH range. The linear response range covers a concentration range of Cys from 1.5 × 10- 7 to 1.0 × 10- 5 mol·L- 1 and the detection limit is 6.9 × 10- 8 mol·L- 1 for Cys. The probe has been successfully applied to the confocal imaging of biothiols in lysosomes of A549 cells with low cell toxicity. Furthermore, the method was successfully applied to the determination of thiols in a complex multicomponent mixture such as human serum, which suggests our proposed method has great potential for diagnostic purposes. All of such good properties prove it can be used to monitor biothiols in lysosomes of living cells and to be a good fluorescent probe for the selective detection of thiols.

  18. A lysosome-targetable turn-on fluorescent probe for the detection of thiols in living cells based on a 1,8-naphthalimide derivative.

    PubMed

    Liang, Beibei; Wang, Baiyan; Ma, Qiujuan; Xie, Caixia; Li, Xian; Wang, Suiping

    2018-03-05

    Biological thiols, like cysteine (Cys), homocysteine (Hcy) and glutathione (GSH), play crucial roles in biological systems and in lysosomal processes. Highly selective probes for detecting biological thiols in lysomes of living cells are rare. In this work, a lysosome-targetable turn-on fluorescent probe for the detection of thiols in living cells was designed and synthesized based on a 1,8-naphthalimide derivative. The probe has a 4-(2-aminoethyl)morpholine unit as a lysosome-targetable group and an acrylate group as the thiol recognition unit as well as a fluorescence quencher. In the absence of biothiols, the probe displayed weak fluorescence due to the photoinduced electron transfer (PET) process. Upon the addition of biothiols, the probe exhibited an enhanced fluorescence emission centered at 550nm due to cleavage of the acrylate moiety. The probe had high selectivity toward biothiols. Moreover, the probe features fast response time, excitation in the visible region and ability of working in a wide pH range. The linear response range covers a concentration range of Cys from 1.5×10 -7 to 1.0×10 -5 mol·L -1 and the detection limit is 6.9×10 -8 mol·L -1 for Cys. The probe has been successfully applied to the confocal imaging of biothiols in lysosomes of A549 cells with low cell toxicity. Furthermore, the method was successfully applied to the determination of thiols in a complex multicomponent mixture such as human serum, which suggests our proposed method has great potential for diagnostic purposes. All of such good properties prove it can be used to monitor biothiols in lysosomes of living cells and to be a good fluorescent probe for the selective detection of thiols. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. In situ targeted MRI detection of Helicobacter pylori with stable magnetic graphitic nanocapsules

    PubMed Central

    Li, Yunjie; Hu, Xiaoxiao; Ding, Ding; Zou, Yuxiu; Xu, Yiting; Wang, Xuewei; Zhang, Yin; Chen, Long; Chen, Zhuo; Tan, Weihong

    2017-01-01

    Helicobacter pylori infection is implicated in the aetiology of many diseases. Despite numerous studies, a painless, fast and direct method for the in situ detection of H. pylori remains a challenge, mainly due to the strong acidic/enzymatic environment of the gastric mucosa. Herein, we report the use of stable magnetic graphitic nanocapsules (MGNs), for in situ targeted magnetic resonance imaging (MRI) detection of H. pylori. Several layers of graphene as the shell effectively protect the magnetic core from corrosion while retaining the superior contrast effect for MRI in the gastric environment. Boronic-polyethylene glycol molecules were synthesized and modified on the MGN surface for targeted MRI detection. In a mouse model of H. pylori-induced infection, H. pylori was specifically detected through both T2-weighted MR imaging and Raman gastric mucosa imaging using functionalized MGNs. These results indicated that enhancement of MRI using MGNs may be a promising diagnostic and bioimaging platform for very harsh conditions. PMID:28643777

  20. In situ targeted MRI detection of Helicobacter pylori with stable magnetic graphitic nanocapsules

    NASA Astrophysics Data System (ADS)

    Li, Yunjie; Hu, Xiaoxiao; Ding, Ding; Zou, Yuxiu; Xu, Yiting; Wang, Xuewei; Zhang, Yin; Chen, Long; Chen, Zhuo; Tan, Weihong

    2017-06-01

    Helicobacter pylori infection is implicated in the aetiology of many diseases. Despite numerous studies, a painless, fast and direct method for the in situ detection of H. pylori remains a challenge, mainly due to the strong acidic/enzymatic environment of the gastric mucosa. Herein, we report the use of stable magnetic graphitic nanocapsules (MGNs), for in situ targeted magnetic resonance imaging (MRI) detection of H. pylori. Several layers of graphene as the shell effectively protect the magnetic core from corrosion while retaining the superior contrast effect for MRI in the gastric environment. Boronic-polyethylene glycol molecules were synthesized and modified on the MGN surface for targeted MRI detection. In a mouse model of H. pylori-induced infection, H. pylori was specifically detected through both T2-weighted MR imaging and Raman gastric mucosa imaging using functionalized MGNs. These results indicated that enhancement of MRI using MGNs may be a promising diagnostic and bioimaging platform for very harsh conditions.

  1. Target-triggering multiple-cycle signal amplification strategy for ultrasensitive detection of DNA based on QCM and SPR.

    PubMed

    Song, Weiling; Yin, Wenshuo; Sun, Wenbo; Guo, Xiaoyan; He, Peng; Yang, Xiaoyan; Zhang, Xiaoru

    2018-04-24

    Detection of ultralow concentrations of nucleic acid sequences is a central challenge in the early diagnosis of genetic diseases. Herein, we developed a target-triggering cascade multiple cycle amplification for ultrasensitive DNA detection using quartz crystal microbalance (QCM) and surface plasmon resonance (SPR). It was based on the exonuclease Ⅲ (Exo Ⅲ)-assisted signal amplification and the hybridization chain reaction (HCR). The streptavidin-coated Au-NPs (Au-NPs-SA) were assembled on the HCR products as recognition element. Upon sensing of target DNA, the duplex DNA probe triggered the Exo Ⅲ cleavage process, accompanied by generating a new secondary target DNA and releasing target DNA. The released target DNA and the secondary target DNA were recycled. Simultaneously, numerous single strands were liberated and acted as the trigger of HCR to generate further signal amplification, resulting in the immobilization of abundant Au-NPs-SA on the gold substrate. The QCM sensor results were found to be comparable to that achieved using a SPR sensor platform. This method exhibited a high sensitivity toward target DNA with a detection limit of 0.70 fM. The high sensitivity and specificity make this method a great potential for detecting DNA with trace amounts in bioanalysis and clinical biomedicine. Copyright © 2018 Elsevier Inc. All rights reserved.

  2. Multiplex detection of quality indicator molecule targets in urine using programmable hairpin probes based on a simple double-T type microchip electrophoresis platform and isothermal polymerase-catalyzed target recycling.

    PubMed

    Zhou, Lingying; Gan, Ning; Wu, Yongxiang; Hu, Futao; Lin, Jianyuan; Cao, Yuting; Wu, Dazhen

    2018-05-29

    Recently, it has been crucial to be able to detect and quantify small molecular targets simultaneously in biological samples. Herein, a simple and conventional double-T type microchip electrophoresis (MCE) based platform for the multiplex detection of quality indicator molecule targets in urine, using ampicillin (AMPI), adenosine triphosphate (ATP) and estradiol (E2) as models, was developed. Several programmable hairpin probes (PHPs) were designed for detecting different targets and triggering isothermal polymerase-catalyzed target recycling (IPCTR) for signal amplification. Based on the target-responsive aptamer structure of PHP (Domain I), target recognition can induce PHP conformational transition and produce extension duplex DNA (dsDNA), assisted by primers & Bst polymerase. Afterwards, the target can be displaced to react with another PHP and initiate the next cycle. After several rounds of reaction, the dsDNA can be produced in large amounts by IPCTR. Three targets can be simultaneously converted to dsDNA fragments with different lengths, which can be separated and detected using MCE. Thus, a simple double-T type MCE based platform was successfully built for the homogeneous detection of multiplex targets in one channel. Under optimal conditions, the assay exhibited high throughput (48 samples per hour at most, not including reaction time) and sensitivity to three targets in urine with a detection limit of 1 nM (ATP), 0.05 nM (AMPI) and 0.1 nM (E2) respectively. The multiplex assay was successfully employed for the above three targets in several urine samples and combined the advantages of the high specificity of programmable hairpin probes, the excellent signal amplification of IPCTR, and the high through-put of MCE which can be employed for screening in biochemical analysis.

  3. A Search Model for Imperfectly Detected Targets

    NASA Technical Reports Server (NTRS)

    Ahumada, Albert

    2012-01-01

    Under the assumptions that 1) the search region can be divided up into N non-overlapping sub-regions that are searched sequentially, 2) the probability of detection is unity if a sub-region is selected, and 3) no information is available to guide the search, there are two extreme case models. The search can be done perfectly, leading to a uniform distribution over the number of searches required, or the search can be done with no memory, leading to a geometric distribution for the number of searches required with a success probability of 1/N. If the probability of detection P is less than unity, but the search is done otherwise perfectly, the searcher will have to search the N regions repeatedly until detection occurs. The number of searches is thus the sum two random variables. One is N times the number of full searches (a geometric distribution with success probability P) and the other is the uniform distribution over the integers 1 to N. The first three moments of this distribution were computed, giving the mean, standard deviation, and the kurtosis of the distribution as a function of the two parameters. The model was fit to the data presented last year (Ahumada, Billington, & Kaiwi, 2 required to find a single pixel target on a simulated horizon. The model gave a good fit to the three moments for all three observers.

  4. Pulse Shape Correlation for Laser Detection and Ranging (LADAR)

    DTIC Science & Technology

    2010-03-01

    with the incoming measured laser pulse [3]. All of these shapes are symmetric. Siegman and Liu’s findings indicate that the pulse is seldom symmetric...of Engineering, Air Force Institute of Technology (AETC), Wright Pat- terson AFB, OH, March 2007. 10. Siegman , Anthony E. Lasers . University Science...Pulse Shape Correlation for Laser Detection and Ranging (LADAR) THESIS Brian T. Deas, Major, USAF AFIT/GE/ENG/10-07 DEPARTMENT OF THE AIR FORCE AIR

  5. Optoacoustic detection of viral antigens using targeted gold nanorods

    NASA Astrophysics Data System (ADS)

    Maswadi, Saher; Woodward, Lee; Glickman, Randolph D.; Barsalou, Norman

    2009-02-01

    We are detecting antigens (Ag), isolated from infectious organisms, utilizing laser optoacoustic spectroscopy and antibody-coupled gold nanorod (NR) contrast agents specifically targeted to the antigen of interest. We have detected, in clinical ocular samples, both Herpes Simplex Virus Type 1 and 2 (HSV-1 and HSV-2) . A monoclonal antibody (Ab) specific to both HSV-1 and HSV-2 was conjugated to gold nanorods to produce a targeted contrast agent with a strong optoacoustic signal. Elutions obtained from patient corneal swabs were adsorbed in standard plastic micro-wells. An immunoaffinity reaction was then performed with the functionalized gold nanorods, and the results were probed with an OPO laser, emitting wavelengths at the peak absorptions of the nanorods. Positive optoacoustic responses were obtained from samples containing authentic (microbiologically confirmed) HSV-1 and HSV-2. To obtain an estimate of the sensitivity of the technique, serial dilutions from 1 mg/ml to 1 pg/ml of a C. trachomatis surface Ag were prepared, and were probed with a monoclonal Ab, specific to the C. trachomatis surface Ag, conjugated to gold nanorods. An optoacoustic response was obtained, proportional to the concentration of antigen, and with a limit of detection of about 5 pg/ml. The optoacoustic signals generated from micro-wells containing albumin or saline were similar to those from blank wells. The potential benefit of this method is identify viral agents more rapidly than with existing techniques. In addition, the sensitivity of the assay is comparable or superior to existing colorimetric- or fluorometric-linked immunoaffinity assays.

  6. Construction of a standard reference plasmid containing seven target genes for the detection of transgenic cotton.

    PubMed

    Wang, Xujing; Tang, Qiaoling; Dong, Lei; Dong, Yufeng; Su, Yueyan; Jia, Shirong; Wang, Zhixing

    2014-07-01

    Insect resistance and herbicide tolerance are the dominant traits of commercialized transgenic cotton. In this study, we constructed a general standard reference plasmid for transgenic cotton detection. Target genes, including the cowpea trypsin gene cptI, the insect resistance gene cry1Ab/1Ac, the herbicide tolerance gene cp4-epsps, the Agrobacterium tumefaciens nopaline synthase (Nos) terminator that exists in transgenic cotton and part of the endogenous cotton SadI gene were amplified from plasmids pCPT1, pBT, pCP4 and pBI121 and from DNA of the nontransgenic cotton line K312, respectively. The genes cry1Ab/1Ac and cptI, as well as cp4-epsps and the Nos terminator gene, were ligated together to form the fusion genes cptI-Bt and cp4-Nos, respectively, by overlapping PCR. We checked the validity of genes Sad1, cptI-Bt and cp4-Nos by DNA sequencing. Then, positive clones of cptI-Bt, cp4-Nos and Sad1 were digested with the corresponding restriction enzymes and ligated sequentially into vector pCamBIA2300, which contains the CAMV 35S promoter and nptII gene, to form the reference plasmid pMCS. Qualitative detection showed that pMCS is a good positive control for transgenic cotton detection. Real-time PCR detection efficiencies with pMCS as a calibrator ranged from 94.35% to 98.67% for the standard curves of the target genes (R(2)⩾0.998). The relative standard deviation of the mean value for the known sample was 11.95%. These results indicate that the strategy of using the pMCS plasmid as a reference material is feasible and reliable for the detection of transgenic cotton. Therefore, this plasmid can serve as a useful reference tool for qualitative and quantitative detection of single or stacked trait transgenic cotton, thus paving the way for the identification of various products containing components of transgenic cotton. Copyright © 2014 Elsevier Inc. All rights reserved.

  7. Added value of second biopsy target in screen-detected widespread suspicious breast calcifications.

    PubMed

    Falkner, Nathalie M; Hince, Dana; Porter, Gareth; Dessauvagie, Ben; Jeganathan, Sanjay; Bulsara, Max; Lo, Glen

    2018-06-01

    There is controversy on the optimal work-up of screen-detected widespread breast calcifications: whether to biopsy a single target or multiple targets. This study evaluates agreement between multiple biopsy targets within the same screen-detected widespread (≥25 mm) breast calcification to determine if the second biopsy adds value. Retrospective observational study of women screened in a statewide general population risk breast cancer mammographic screening program from 2009 to 2016. Screening episodes recalled for widespread calcifications where further views indicated biopsy, and two or more separate target areas were sampled within the same lesion were included. Percentage agreement and Cohen's Kappa were calculated. A total of 293317 women were screened during 761124 separate episodes with recalls for widespread calcifications in 2355 episodes. In 171 women, a second target was biopsied within the same lesion. In 149 (86%) cases, the second target biopsy result agreed with the first biopsy (κ = 0.6768). Agreement increased with increasing mammography score (85%, 86% and 92% for score 3, 4 and 5 lesions). Same day multiple biopsied lesions were three times more likely to yield concordant results compared to post-hoc second target biopsy cases. While a single target biopsy is sufficient to discriminate a benign vs. malignant diagnosis in most cases, in 14% there is added value in performing a second target biopsy. Biopsies performed prospectively are more likely to yield concordant results compared to post-hoc second target biopsy cases, suggesting a single prospective biopsy may be sufficient when results are radiological-pathological concordant; discordance still requires repeat sampling. © 2018 The Royal Australian and New Zealand College of Radiologists.

  8. Infrared dim and small target detecting and tracking method inspired by Human Visual System

    NASA Astrophysics Data System (ADS)

    Dong, Xiabin; Huang, Xinsheng; Zheng, Yongbin; Shen, Lurong; Bai, Shengjian

    2014-01-01

    Detecting and tracking dim and small target in infrared images and videos is one of the most important techniques in many computer vision applications, such as video surveillance and infrared imaging precise guidance. Recently, more and more algorithms based on Human Visual System (HVS) have been proposed to detect and track the infrared dim and small target. In general, HVS concerns at least three mechanisms including contrast mechanism, visual attention and eye movement. However, most of the existing algorithms simulate only a single one of the HVS mechanisms, resulting in many drawbacks of these algorithms. A novel method which combines the three mechanisms of HVS is proposed in this paper. First, a group of Difference of Gaussians (DOG) filters which simulate the contrast mechanism are used to filter the input image. Second, a visual attention, which is simulated by a Gaussian window, is added at a point near the target in order to further enhance the dim small target. This point is named as the attention point. Eventually, the Proportional-Integral-Derivative (PID) algorithm is first introduced to predict the attention point of the next frame of an image which simulates the eye movement of human being. Experimental results of infrared images with different types of backgrounds demonstrate the high efficiency and accuracy of the proposed method to detect and track the dim and small targets.

  9. A retrospective detection algorithm for extraction of weak targets in clutter and interference environments

    NASA Astrophysics Data System (ADS)

    Prengaman, R. J.; Thurber, R. E.; Bath, W. G.

    The usefulness of radar systems depends on the ability to distinguish between signals returned from desired targets and noise. A retrospective processor uses all contacts (or 'plots') from several past radar scans, taking into account all possible target trajectories formed from stored contacts for each input detection. The processor eliminates many false alarms, while retaining those contacts describing resonable trajectories. The employment of a retrospective processor makes it, therefore, possible to obtain large improvements in detection sensitivity in certain important clutter environments. Attention is given to the retrospective processing concept, a theoretical analysis of the multiscan detection process, the experimental evaluation of retrospective data filter, and aspects of retrospective data filter hardware implementation.

  10. Sensitive SERS detection of DNA methyltransferase by target triggering primer generation-based multiple signal amplification strategy.

    PubMed

    Li, Ying; Yu, Chuanfeng; Han, Huixia; Zhao, Caisheng; Zhang, Xiaoru

    2016-07-15

    A novel and sensitive surface-enhanced Raman scattering (SERS) method is proposed for the assay of DNA methyltransferase (MTase) activity and evaluation of inhibitors by developing a target triggering primer generation-based multiple signal amplification strategy. By using of a duplex substrate for Dam MTase, two hairpin templates and a Raman probe, multiple signal amplification mode is achieved. Once recognized by Dam MTase, the duplex substrate can be cleaved by Dpn I endonuclease and two primers are released for triggering the multiple signal amplification reaction. Consequently, a wide dynamic range and remarkably high sensitivity are obtained under isothermal conditions. The detection limit is 2.57×10(-4)UmL(-1). This assay exhibits an excellent selectivity and is successfully applied in the screening of inhibitors for Dam MTase. In addition, this novel sensing system is potentially universal as the recognition element can be conveniently designed for other target analytes by changing the substrate of DNA MTase. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Detection and Tracking of Moving Targets Behind Cluttered Environments Using Compressive Sensing

    NASA Astrophysics Data System (ADS)

    Dang, Vinh Quang

    Detection and tracking of moving targets (target's motion, vibration, etc.) in cluttered environments have been receiving much attention in numerous applications, such as disaster search-and-rescue, law enforcement, urban warfare, etc. One of the popular techniques is the use of stepped frequency continuous wave radar due to its low cost and complexity. However, the stepped frequency radar suffers from long data acquisition time. This dissertation focuses on detection and tracking of moving targets and vibration rates of stationary targets behind cluttered medium such as wall using stepped frequency radar enhanced by compressive sensing. The application of compressive sensing enables the reconstruction of the target space using fewer random frequencies, which decreases the acquisition time. Hardware-accelerated parallelization on GPU is investigated for the Orthogonal Matching Pursuit reconstruction algorithm. For simulation purpose, two hybrid methods have been developed to calculate the scattered fields from the targets through the wall approaching the antenna system, and to convert the incoming fields into voltage signals at terminals of the receive antenna. The first method is developed based on the plane wave spectrum approach for calculating the scattered fields of targets behind the wall. The method uses Fast Multiple Method (FMM) to calculate scattered fields on a particular source plane, decomposes them into plane wave components, and propagates the plane wave spectrum through the wall by integrating wall transmission coefficients before constructing the fields on a desired observation plane. The second method allows one to calculate the complex output voltage at terminals of a receiving antenna which fully takes into account the antenna effects. This method adopts the concept of complex antenna factor in Electromagnetic Compatibility (EMC) community for its calculation.

  12. Model-assisted forest yield estimation with light detection and ranging

    Treesearch

    Jacob L. Strunk; Stephen E. Reutebuch; Hans-Erik Andersen; Peter J. Gould; Robert J. McGaughey

    2012-01-01

    Previous studies have demonstrated that light detection and ranging (LiDAR)-derived variables can be used to model forest yield variables, such as biomass, volume, and number of stems. However, the next step is underrepresented in the literature: estimation of forest yield with appropriate confidence intervals. It is of great importance that the procedures required for...

  13. Accuracy of software-assisted detection of tumour feeders in transcatheter hepatic chemoembolization using three target definition protocols.

    PubMed

    Iwazawa, J; Ohue, S; Hashimoto, N; Mitani, T

    2014-02-01

    To compare the accuracy of computer software analysis using three different target-definition protocols to detect tumour feeder vessels for transarterial chemoembolization of hepatocellular carcinoma. C-arm computed tomography (CT) data were analysed for 81 tumours from 57 patients who had undergone chemoembolization using software-assisted detection of tumour feeders. Small, medium, and large-sized targets were manually defined for each tumour. The tumour feeder was verified when the target tumour was enhanced on selective C-arm CT of the investigated vessel during chemoembolization. The sensitivity, specificity, and accuracy of the three protocols were evaluated and compared. One hundred and eight feeder vessels supplying 81 lesions were detected. The sensitivity of the small, medium, and large target protocols was 79.8%, 91.7%, and 96.3%, respectively; specificity was 95%, 88%, and 50%, respectively; and accuracy was 87.5%, 89.9%, and 74%, respectively. The sensitivity was significantly higher for the medium (p = 0.003) and large (p < 0.001) target protocols than for the small target protocol. The specificity and accuracy were higher for the small (p < 0.001 and p < 0.001, respectively) and medium (p < 0.001 and p < 0.001, respectively) target protocols than for the large target protocol. The overall accuracy of software-assisted automated feeder analysis in transarterial chemoembolization for hepatocellular carcinoma is affected by the target definition size. A large target definition increases sensitivity and decreases specificity in detecting tumour feeders. A target size equivalent to the tumour size most accurately predicts tumour feeders. Copyright © 2013 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

  14. Spatio-temporal hotspots of satellite-tracked arctic foxes reveal a large detection range in a mammalian predator.

    PubMed

    Lai, Sandra; Bêty, Joël; Berteaux, Dominique

    2015-01-01

    The scale at which animals perceive their environment is a strong fitness determinant, yet few empirical estimates of animal detection ranges exist, especially in mammalian predators. Using daily Argos satellite tracking of 26 adult arctic foxes (Vulpes lagopus) during a single winter in the High Canadian Arctic, we investigated the detection range of arctic foxes by detecting hotspots of fox activity on the sea ice. While maintaining territories in the tundra, these solitary foragers occasionally used the sea ice where they sometimes formed spatio-temporal hotspots, likely scavenging on marine mammal carcasses. We detected 35 movements by 13 individuals forming five hotspots. Foxes often traveled more than 10 km, and up to 40 km, to reach hotspots, which lasted one-two weeks and could gather up to 12 individuals. The likelihood of a fox joining a hotspot was neither influenced by its distance from the hotspot nor by the distance of its home range to the coast. Observed traveling distances may indicate a high detection range in arctic foxes, and our results suggest their ability to detect food sources on the sea ice from their terrestrial home range. While revealing a wide knowledge gap regarding resource detection abilities in mammalian predators, our study provides estimates of detection range useful for interpreting and modeling animal movements. It also allows a better understanding of foraging behavior and navigation capacity in terrestrial predators.

  15. Development and validation of quantitative PCR for detection of Terrapene herpesvirus 1 utilizing free-ranging eastern box turtles (Terrapene carolina carolina).

    PubMed

    Kane, Lauren P; Bunick, David; Abd-Eldaim, Mohamed; Dzhaman, Elena; Allender, Matthew C

    2016-06-01

    Diseases that affect the upper respiratory tract (URT) in chelonians have been well described as a significant contributor of morbidity and mortality. Specifically, herpesviruses are common pathogens in captive chelonians worldwide, but their importance on free-ranging populations is less well known. Historical methods for the diagnosis of herpesvirus infections include virus isolation and conventional PCR. Real-time PCR has become an essential tool for detection and quantitation of many pathogens, but has not yet been developed for herpesviruses in box turtles. Two quantitative real-time TaqMan PCR assays, TerHV58 and TerHV64, were developed targeting the DNA polymerase gene of Terrapene herpesvirus 1 (TerHV1). The assay detected a viral DNA segment cloned within a plasmid with 10-fold serial dilutions from 1.04 × 10(7) to 1.04 × 10(1) viral copies per reaction. Even though both primers had acceptable levels of efficiency and variation, TerHV58 was utilized to test clinical samples based on less variation and increased efficiency. This assay detected as few as 10 viral copies per reaction and should be utilized in free-ranging and captive box turtles to aid in the characterization of the epidemiology of this disease. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. Theoretical detection threshold of the proton-acoustic range verification technique

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ahmad, Moiz; Yousefi, Siavash; Xing, Lei, E-mail: lei@stanford.edu

    2015-10-15

    Purpose: Range verification in proton therapy using the proton-acoustic signal induced in the Bragg peak was investigated for typical clinical scenarios. The signal generation and detection processes were simulated in order to determine the signal-to-noise limits. Methods: An analytical model was used to calculate the dose distribution and local pressure rise (per proton) for beams of different energy (100 and 160 MeV) and spot widths (1, 5, and 10 mm) in a water phantom. In this method, the acoustic waves propagating from the Bragg peak were generated by the general 3D pressure wave equation implemented using a finite element method.more » Various beam pulse widths (0.1–10 μs) were simulated by convolving the acoustic waves with Gaussian kernels. A realistic PZT ultrasound transducer (5 cm diameter) was simulated with a Butterworth bandpass filter with consideration of random noise based on a model of thermal noise in the transducer. The signal-to-noise ratio on a per-proton basis was calculated, determining the minimum number of protons required to generate a detectable pulse. The maximum spatial resolution of the proton-acoustic imaging modality was also estimated from the signal spectrum. Results: The calculated noise in the transducer was 12–28 mPa, depending on the transducer central frequency (70–380 kHz). The minimum number of protons detectable by the technique was on the order of 3–30 × 10{sup 6} per pulse, with 30–800 mGy dose per pulse at the Bragg peak. Wider pulses produced signal with lower acoustic frequencies, with 10 μs pulses producing signals with frequency less than 100 kHz. Conclusions: The proton-acoustic process was simulated using a realistic model and the minimal detection limit was established for proton-acoustic range validation. These limits correspond to a best case scenario with a single large detector with no losses and detector thermal noise as the sensitivity limiting factor. Our study indicated practical proton

  17. Theoretical detection threshold of the proton-acoustic range verification technique

    PubMed Central

    Ahmad, Moiz; Xiang, Liangzhong; Yousefi, Siavash; Xing, Lei

    2015-01-01

    Purpose: Range verification in proton therapy using the proton-acoustic signal induced in the Bragg peak was investigated for typical clinical scenarios. The signal generation and detection processes were simulated in order to determine the signal-to-noise limits. Methods: An analytical model was used to calculate the dose distribution and local pressure rise (per proton) for beams of different energy (100 and 160 MeV) and spot widths (1, 5, and 10 mm) in a water phantom. In this method, the acoustic waves propagating from the Bragg peak were generated by the general 3D pressure wave equation implemented using a finite element method. Various beam pulse widths (0.1–10 μs) were simulated by convolving the acoustic waves with Gaussian kernels. A realistic PZT ultrasound transducer (5 cm diameter) was simulated with a Butterworth bandpass filter with consideration of random noise based on a model of thermal noise in the transducer. The signal-to-noise ratio on a per-proton basis was calculated, determining the minimum number of protons required to generate a detectable pulse. The maximum spatial resolution of the proton-acoustic imaging modality was also estimated from the signal spectrum. Results: The calculated noise in the transducer was 12–28 mPa, depending on the transducer central frequency (70–380 kHz). The minimum number of protons detectable by the technique was on the order of 3–30 × 106 per pulse, with 30–800 mGy dose per pulse at the Bragg peak. Wider pulses produced signal with lower acoustic frequencies, with 10 μs pulses producing signals with frequency less than 100 kHz. Conclusions: The proton-acoustic process was simulated using a realistic model and the minimal detection limit was established for proton-acoustic range validation. These limits correspond to a best case scenario with a single large detector with no losses and detector thermal noise as the sensitivity limiting factor. Our study indicated practical proton-acoustic range

  18. An iterative and targeted sampling design informed by habitat suitability models for detecting focal plant species over extensive areas.

    PubMed

    Wang, Ophelia; Zachmann, Luke J; Sesnie, Steven E; Olsson, Aaryn D; Dickson, Brett G

    2014-01-01

    Prioritizing areas for management of non-native invasive plants is critical, as invasive plants can negatively impact plant community structure. Extensive and multi-jurisdictional inventories are essential to prioritize actions aimed at mitigating the impact of invasions and changes in disturbance regimes. However, previous work devoted little effort to devising sampling methods sufficient to assess the scope of multi-jurisdictional invasion over extensive areas. Here we describe a large-scale sampling design that used species occurrence data, habitat suitability models, and iterative and targeted sampling efforts to sample five species and satisfy two key management objectives: 1) detecting non-native invasive plants across previously unsampled gradients, and 2) characterizing the distribution of non-native invasive plants at landscape to regional scales. Habitat suitability models of five species were based on occurrence records and predictor variables derived from topography, precipitation, and remotely sensed data. We stratified and established field sampling locations according to predicted habitat suitability and phenological, substrate, and logistical constraints. Across previously unvisited areas, we detected at least one of our focal species on 77% of plots. In turn, we used detections from 2011 to improve habitat suitability models and sampling efforts in 2012, as well as additional spatial constraints to increase detections. These modifications resulted in a 96% detection rate at plots. The range of habitat suitability values that identified highly and less suitable habitats and their environmental conditions corresponded to field detections with mixed levels of agreement. Our study demonstrated that an iterative and targeted sampling framework can address sampling bias, reduce time costs, and increase detections. Other studies can extend the sampling framework to develop methods in other ecosystems to provide detection data. The sampling methods

  19. An Iterative and Targeted Sampling Design Informed by Habitat Suitability Models for Detecting Focal Plant Species over Extensive Areas

    PubMed Central

    Wang, Ophelia; Zachmann, Luke J.; Sesnie, Steven E.; Olsson, Aaryn D.; Dickson, Brett G.

    2014-01-01

    Prioritizing areas for management of non-native invasive plants is critical, as invasive plants can negatively impact plant community structure. Extensive and multi-jurisdictional inventories are essential to prioritize actions aimed at mitigating the impact of invasions and changes in disturbance regimes. However, previous work devoted little effort to devising sampling methods sufficient to assess the scope of multi-jurisdictional invasion over extensive areas. Here we describe a large-scale sampling design that used species occurrence data, habitat suitability models, and iterative and targeted sampling efforts to sample five species and satisfy two key management objectives: 1) detecting non-native invasive plants across previously unsampled gradients, and 2) characterizing the distribution of non-native invasive plants at landscape to regional scales. Habitat suitability models of five species were based on occurrence records and predictor variables derived from topography, precipitation, and remotely sensed data. We stratified and established field sampling locations according to predicted habitat suitability and phenological, substrate, and logistical constraints. Across previously unvisited areas, we detected at least one of our focal species on 77% of plots. In turn, we used detections from 2011 to improve habitat suitability models and sampling efforts in 2012, as well as additional spatial constraints to increase detections. These modifications resulted in a 96% detection rate at plots. The range of habitat suitability values that identified highly and less suitable habitats and their environmental conditions corresponded to field detections with mixed levels of agreement. Our study demonstrated that an iterative and targeted sampling framework can address sampling bias, reduce time costs, and increase detections. Other studies can extend the sampling framework to develop methods in other ecosystems to provide detection data. The sampling methods

  20. Detection limit of intragenic deletions with targeted array comparative genomic hybridization

    PubMed Central

    2013-01-01

    Background Pathogenic mutations range from single nucleotide changes to deletions or duplications that encompass a single exon to several genes. The use of gene-centric high-density array comparative genomic hybridization (aCGH) has revolutionized the detection of intragenic copy number variations. We implemented an exon-centric design of high-resolution aCGH to detect single- and multi-exon deletions and duplications in a large set of genes using the OGT 60 K and 180 K arrays. Here we describe the molecular characterization and breakpoint mapping of deletions at the smaller end of the detectable range in several genes using aCGH. Results The method initially implemented to detect single to multiple exon deletions, was able to detect deletions much smaller than anticipated. The selected deletions we describe vary in size, ranging from over 2 kb to as small as 12 base pairs. The smallest of these deletions are only detectable after careful manual review during data analysis. Suspected deletions smaller than the detection size for which the method was optimized, were rigorously followed up and confirmed with PCR-based investigations to uncover the true detection size limit of intragenic deletions with this technology. False-positive deletion calls often demonstrated single nucleotide changes or an insertion causing lower hybridization of probes demonstrating the sensitivity of aCGH. Conclusions With optimizing aCGH design and careful review process, aCGH can uncover intragenic deletions as small as dozen bases. These data provide insight that will help optimize probe coverage in array design and illustrate the true assay sensitivity. Mapping of the breakpoints confirms smaller deletions and contributes to the understanding of the mechanism behind these events. Our knowledge of the mutation spectra of several genes can be expected to change as previously unrecognized intragenic deletions are uncovered. PMID:24304607

  1. Evaluation of Targeted Next-Generation Sequencing for Detection of Bovine Pathogens in Clinical Samples.

    PubMed

    Anis, Eman; Hawkins, Ian K; Ilha, Marcia R S; Woldemeskel, Moges W; Saliki, Jeremiah T; Wilkes, Rebecca P

    2018-07-01

    The laboratory diagnosis of infectious diseases, especially those caused by mixed infections, is challenging. Routinely, it requires submission of multiple samples to separate laboratories. Advances in next-generation sequencing (NGS) have provided the opportunity for development of a comprehensive method to identify infectious agents. This study describes the use of target-specific primers for PCR-mediated amplification with the NGS technology in which pathogen genomic regions of interest are enriched and selectively sequenced from clinical samples. In the study, 198 primers were designed to target 43 common bovine and small-ruminant bacterial, fungal, viral, and parasitic pathogens, and a bioinformatics tool was specifically constructed for the detection of targeted pathogens. The primers were confirmed to detect the intended pathogens by testing reference strains and isolates. The method was then validated using 60 clinical samples (including tissues, feces, and milk) that were also tested with other routine diagnostic techniques. The detection limits of the targeted NGS method were evaluated using 10 representative pathogens that were also tested by quantitative PCR (qPCR), and the NGS method was able to detect the organisms from samples with qPCR threshold cycle ( C T ) values in the 30s. The method was successful for the detection of multiple pathogens in the clinical samples, including some additional pathogens missed by the routine techniques because the specific tests needed for the particular organisms were not performed. The results demonstrate the feasibility of the approach and indicate that it is possible to incorporate NGS as a diagnostic tool in a cost-effective manner into a veterinary diagnostic laboratory. Copyright © 2018 Anis et al.

  2. Fractal analysis of seafloor textures for target detection in synthetic aperture sonar imagery

    NASA Astrophysics Data System (ADS)

    Nabelek, T.; Keller, J.; Galusha, A.; Zare, A.

    2018-04-01

    Fractal analysis of an image is a mathematical approach to generate surface related features from an image or image tile that can be applied to image segmentation and to object recognition. In undersea target countermeasures, the targets of interest can appear as anomalies in a variety of contexts, visually different textures on the seafloor. In this paper, we evaluate the use of fractal dimension as a primary feature and related characteristics as secondary features to be extracted from synthetic aperture sonar (SAS) imagery for the purpose of target detection. We develop three separate methods for computing fractal dimension. Tiles with targets are compared to others from the same background textures without targets. The different fractal dimension feature methods are tested with respect to how well they can be used to detect targets vs. false alarms within the same contexts. These features are evaluated for utility using a set of image tiles extracted from a SAS data set generated by the U.S. Navy in conjunction with the Office of Naval Research. We find that all three methods perform well in the classification task, with a fractional Brownian motion model performing the best among the individual methods. We also find that the secondary features are just as useful, if not more so, in classifying false alarms vs. targets. The best classification accuracy overall, in our experimentation, is found when the features from all three methods are combined into a single feature vector.

  3. Vision for action and perception elicit dissociable adherence to Weber's law across a range of 'graspable' target objects.

    PubMed

    Heath, Matthew; Manzone, Joseph; Khan, Michaela; Davarpanah Jazi, Shirin

    2017-10-01

    A number of studies have reported that grasps and manual estimations of differently sized target objects (e.g., 20 through 70 mm) violate and adhere to Weber's law, respectively (e.g., Ganel et al. 2008a, Curr Biol 18:R599-R601)-a result interpreted as evidence that separate visual codes support actions (i.e., absolute) and perceptions (i.e., relative). More recent work employing a broader range of target objects (i.e., 5 through 120 mm) has laid question to this claim and proposed that grasps for 'larger' target objects (i.e., >20 mm) elicit an inverse relationship to Weber's law and that manual estimations for target objects greater than 40 mm violate the law (Bruno et al. 2016, Neuropsychologia 91:327-334). In accounting for this finding, it was proposed that biomechanical limits in aperture shaping preclude the application of Weber's law for larger target objects. It is, however, important to note that the work supporting a biomechanical account may have employed target objects that approached -or were beyond-some participants' maximal aperture separation. The present investigation examined whether grasps and manual estimations differentially adhere to Weber's law across a continuous range of functionally 'graspable' target objects (i.e., 10,…,80% of participant-specific maximal aperture separation). In addition, we employed a method of adjustment task to examine whether manual estimation provides a valid proxy for a traditional measure of perceptual judgment. Manual estimation and method of adjustment tasks demonstrated adherence to Weber's law across the continuous range of target objects used here, whereas grasps violated the law. Thus, results evince that grasps and manual estimations of graspable target objects are, respectively, mediated via absolute and relative visual information.

  4. Silver nanoclusters-assisted ion-exchange reaction with CdTe quantum dots for photoelectrochemical detection of adenosine by target-triggering multiple-cycle amplification strategy.

    PubMed

    Zhao, Yang; Tan, Lu; Gao, Xiaoshan; Jie, Guifen; Huang, Tingyu

    2018-07-01

    Herein, we successfully devised a novel photoelectrochemical (PEC) platform for ultrasensitive detection of adenosine by target-triggering cascade multiple cycle amplification based on the silver nanoparticles-assisted ion-exchange reaction with CdTe quantum dots (QDs). In the presence of target adenosine, DNA s1 is released from the aptamer and then hybridizes with hairpin DNA (HP1), which could initiate the cycling cleavage process under the reaction of nicking endonuclease. Then the product (DNA b) of cycle I could act as the "DNA trigger" of cycle II to further generate a large number of DNA s1, which again go back to cycle I, thus a cascade multiple DNA cycle amplification was carried out to produce abundant DNA c. These DNA c fragments with the cytosine (C)-rich loop were captured by magnetic beads, and numerous silver nanoclusters (Ag NCs) were synthesized by AgNO 3 and sodium borohydride. The dissolved AgNCs released numerous silver ions which could induce ion exchange reaction with the CdTe QDs, thus resulting in greatly amplified change of photocurrent for target detection. The detection linear range for adenosine was 1.0 fM ~10 nM with the detection limit of 0.5 fM. The present PEC strategy combining cascade multiple DNA cycle amplification and AgNCs-induced ion-exchange reaction with QDs provides new insight into rapid, and ultrasensitive PEC detection of different biomolecules, which showed great potential for detecting trace amounts in bioanalysis and clinical biomedicine. Copyright © 2018 Elsevier B.V. All rights reserved.

  5. Evaluation of Novel Broad-Range Real-Time PCR Assay for Rapid Detection of Human Pathogenic Fungi in Various Clinical Specimens▿

    PubMed Central

    Vollmer, Tanja; Störmer, Melanie; Kleesiek, Knut; Dreier, Jens

    2008-01-01

    In the present study, a novel broad-range real-time PCR was developed for the rapid detection of human pathogenic fungi. The assay targets a part of the 28S large-subunit ribosomal RNA (rDNA) gene. We investigated its application for the most important human pathogenic fungal genera, including Aspergillus, Candida, Cryptococcus, Mucor, Penicillium, Pichia, Microsporum, Trichophyton, and Scopulariopsis. Species were identified in PCR-positive reactions by direct DNA sequencing. A noncompetitive internal control was applied to prevent false-negative results due to PCR inhibition. The minimum detection limit for the PCR was determined to be one 28S rDNA copy per PCR, and the 95% detection limit was calculated to 15 copies per PCR. To assess the clinical applicability of the PCR method, intensive-care patients with artificial respiration and patients with infective endocarditis were investigated. For this purpose, 76 tracheal secretion samples and 70 heart valve tissues were analyzed in parallel by real-time PCR and cultivation. No discrepancies in results were observed between PCR analysis and cultivation methods. Furthermore, the application of the PCR method was investigated for other clinical specimens, including cervical swabs, nail and horny skin scrapings, and serum, blood, and urine samples. The combination of a broad-range real-time PCR and direct sequencing facilitates rapid screening for fungal infection in various clinical specimens. PMID:18385440

  6. Evaluation of novel broad-range real-time PCR assay for rapid detection of human pathogenic fungi in various clinical specimens.

    PubMed

    Vollmer, Tanja; Störmer, Melanie; Kleesiek, Knut; Dreier, Jens

    2008-06-01

    In the present study, a novel broad-range real-time PCR was developed for the rapid detection of human pathogenic fungi. The assay targets a part of the 28S large-subunit ribosomal RNA (rDNA) gene. We investigated its application for the most important human pathogenic fungal genera, including Aspergillus, Candida, Cryptococcus, Mucor, Penicillium, Pichia, Microsporum, Trichophyton, and Scopulariopsis. Species were identified in PCR-positive reactions by direct DNA sequencing. A noncompetitive internal control was applied to prevent false-negative results due to PCR inhibition. The minimum detection limit for the PCR was determined to be one 28S rDNA copy per PCR, and the 95% detection limit was calculated to 15 copies per PCR. To assess the clinical applicability of the PCR method, intensive-care patients with artificial respiration and patients with infective endocarditis were investigated. For this purpose, 76 tracheal secretion samples and 70 heart valve tissues were analyzed in parallel by real-time PCR and cultivation. No discrepancies in results were observed between PCR analysis and cultivation methods. Furthermore, the application of the PCR method was investigated for other clinical specimens, including cervical swabs, nail and horny skin scrapings, and serum, blood, and urine samples. The combination of a broad-range real-time PCR and direct sequencing facilitates rapid screening for fungal infection in various clinical specimens.

  7. Risk maps for targeting exotic plant pest detection programs in the United States

    Treesearch

    R.D. Magarey; D.M. Borchert; J.S. Engle; M Garcia-Colunga; Frank H. Koch; et al

    2011-01-01

    In the United States, pest risk maps are used by the Cooperative Agricultural Pest Survey for spatial and temporal targeting of exotic plant pest detection programs. Methods are described to create standardized host distribution, climate and pathway risk maps for the top nationally ranked exotic pest targets. Two examples are provided to illustrate the risk mapping...

  8. Time reversal optical tomography and decomposition methods for detection and localization of targets in highly scattering turbid media

    NASA Astrophysics Data System (ADS)

    Wu, Binlin

    New near-infrared (NIR) diffuse optical tomography (DOT) approaches were developed to detect, locate, and image small targets embedded in highly scattering turbid media. The first approach, referred to as time reversal optical tomography (TROT), is based on time reversal (TR) imaging and multiple signal classification (MUSIC). The second approach uses decomposition methods of non-negative matrix factorization (NMF) and principal component analysis (PCA) commonly used in blind source separation (BSS) problems, and compare the outcomes with that of optical imaging using independent component analysis (OPTICA). The goal is to develop a safe, affordable, noninvasive imaging modality for detection and characterization of breast tumors in early growth stages when those are more amenable to treatment. The efficacy of the approaches was tested using simulated data, and experiments involving model media and absorptive, scattering, and fluorescent targets, as well as, "realistic human breast model" composed of ex vivo breast tissues with embedded tumors. The experimental arrangements realized continuous wave (CW) multi-source probing of samples and multi-detector acquisition of diffusely transmitted signal in rectangular slab geometry. A data matrix was generated using the perturbation in the transmitted light intensity distribution due to the presence of absorptive or scattering targets. For fluorescent targets the data matrix was generated using the diffusely transmitted fluorescence signal distribution from the targets. The data matrix was analyzed using different approaches to detect and characterize the targets. The salient features of the approaches include ability to: (a) detect small targets; (b) provide three-dimensional location of the targets with high accuracy (~within a millimeter or 2); and (c) assess optical strength of the targets. The approaches are less computation intensive and consequently are faster than other inverse image reconstruction methods that

  9. Detection of respiratory viruses and bacteria in children using a twenty-two target reverse-transcription real-time PCR (RT-qPCR) panel.

    PubMed

    Ellis, Chelsey; Misir, Amita; Hui, Charles; Jabbour, Mona; Barrowman, Nicholas; Langill, Jonathan; Bowes, Jennifer; Slinger, Robert

    2016-05-01

    Rapid detection of the wide range of viruses and bacteria that cause respiratory infection in children is important for patient care and antibiotic stewardship. We therefore designed and evaluated a ready-to-use 22 target respiratory infection reverse-transcription real-time polymerase chain reaction (RT-qPCR) panel to determine if this would improve detection of these agents at our pediatric hospital. RT-qPCR assays for twenty-two target organisms were dried-down in individual wells of 96 well plates and saved at room temperature. Targets included 18 respiratory viruses and 4 bacteria. After automated nucleic acid extraction of nasopharyngeal aspirate (NPA) samples, rapid qPCR was performed. RT-qPCR results were compared with those obtained by the testing methods used at our hospital laboratories. One hundred fifty-nine pediatric NPA samples were tested with the RT-qPCR panel. One or more respiratory pathogens were detected in 132/159 (83%) samples. This was significantly higher than the detection rate of standard methods (94/159, 59%) (P<0.001). This difference was mainly due to improved RT-qPCR detection of rhinoviruses, parainfluenza viruses, bocavirus, and coronaviruses. The panel internal control assay performance remained stable at room temperature storage over a two-month testing period. The RT-qPCR panel was able to identify pathogens in a high proportion of respiratory samples. The panel detected more positive specimens than the methods in use at our hospital. The pre-made panel format was easy to use and rapid, with results available in approximately 90 minutes. We now plan to determine if use of this panel improves patient care and antibiotic stewardship.

  10. Detection of Accelerating Targets in Clutter Using a De-Chirping Technique

    DTIC Science & Technology

    2014-06-01

    Academy, also in Canberra, working on the the- ory and simulation of spatial optical solitons and light-induced optical switching in nonlinear...signal gain in the receiver. UNCLASSIFIED 1 DSTO–RR–0399 UNCLASSIFIED target along the velocity vector , or equivalently by radar platform. The change of...the tracker uses range rate in its track initiation logic. (2) Lateral acceleration perpendicular to the velocity vector - the target is turning and

  11. Target-responsive DNAzyme cross-linked hydrogel for visual quantitative detection of lead.

    PubMed

    Huang, Yishun; Ma, Yanli; Chen, Yahong; Wu, Xuemeng; Fang, Luting; Zhu, Zhi; Yang, Chaoyong James

    2014-11-18

    Because of the severe health risks associated with lead pollution, rapid, sensitive, and portable detection of low levels of Pb(2+) in biological and environmental samples is of great importance. In this work, a Pb(2+)-responsive hydrogel was prepared using a DNAzyme and its substrate as cross-linker for rapid, sensitive, portable, and quantitative detection of Pb(2+). Gold nanoparticles (AuNPs) were first encapsulated in the hydrogel as an indicator for colorimetric analysis. In the absence of lead, the DNAzyme is inactive, and the substrate cross-linker maintains the hydrogel in the gel form. In contrast, the presence of lead activates the DNAzyme to cleave the substrate, decreasing the cross-linking density of the hydrogel and resulting in dissolution of the hydrogel and release of AuNPs for visual detection. As low as 10 nM Pb(2+) can be detected by the naked eye. Furthermore, to realize quantitative visual detection, a volumetric bar-chart chip (V-chip) was used for quantitative readout of the hydrogel system by replacing AuNPs with gold-platinum core-shell nanoparticles (Au@PtNPs). The Au@PtNPs released from the hydrogel upon target activation can efficiently catalyze the decomposition of H2O2 to generate a large volume of O2. The gas pressure moves an ink bar in the V-chip for portable visual quantitative detection of lead with a detection limit less than 5 nM. The device was able to detect lead in digested blood with excellent accuracy. The method developed can be used for portable lead quantitation in many applications. Furthermore, the method can be further extended to portable visual quantitative detection of a variety of targets by replacing the lead-responsive DNAzyme with other DNAzymes.

  12. Towards Enhanced Underwater Lidar Detection via Source Separation

    NASA Astrophysics Data System (ADS)

    Illig, David W.

    Interest in underwater optical sensors has grown as technologies enabling autonomous underwater vehicles have been developed. Propagation of light through water is complicated by the dual challenges of absorption and scattering. While absorption can be reduced by operating in the blue-green region of the visible spectrum, reducing scattering is a more significant challenge. Collection of scattered light negatively impacts underwater optical ranging, imaging, and communications applications. This thesis concentrates on the ranging application, where scattering reduces operating range as well as range accuracy. The focus of this thesis is on the problem of backscatter, which can create a "clutter" return that may obscure submerged target(s) of interest. The main contributions of this thesis are explorations of signal processing approaches to increase the separation between the target and backscatter returns. Increasing this separation allows detection of weak targets in the presence of strong scatter, increasing both operating range and range accuracy. Simulation and experimental results will be presented for a variety of approaches as functions of water clarity and target position. This work provides several novel contributions to the underwater lidar field: 1. Quantification of temporal separation approaches: While temporal separation has been studied extensively, this work provides a quantitative assessment of the extent to which both high frequency modulation and spatial filter approaches improve the separation between target and backscatter. 2. Development and assessment of frequency separation: This work includes the first frequency-based separation approach for underwater lidar, in which the channel frequency response is measured with a wideband waveform. Transforming to the time-domain gives a channel impulse response, in which target and backscatter returns may appear in unique range bins and thus be separated. 3. Development and assessment of statistical

  13. Receiver design, performance analysis, and evaluation for space-borne laser altimeters and space-to-space laser ranging systems

    NASA Technical Reports Server (NTRS)

    Davidson, Frederic M.; Sun, Xiaoli; Field, Christopher T.

    1995-01-01

    Laser altimeters measure the time of flight of the laser pulses to determine the range of the target. The simplest altimeter receiver consists of a photodetector followed by a leading edge detector. A time interval unit (TIU) measures the time from the transmitted laser pulse to the leading edge of the received pulse as it crosses a preset threshold. However, the ranging error of this simple detection scheme depends on the received, pulse amplitude, pulse shape, and the threshold. In practice, the pulse shape and the amplitude are determined by the target target characteristics which has to be assumed unknown prior to the measurement. The ranging error can be improved if one also measures the pulse width and use the average of the leading and trailing edges (half pulse width) as the pulse arrival time. The ranging error becomes independent of the received pulse amplitude and the pulse width as long as the pulse shape is symmetric. The pulse width also gives the slope of the target. The ultimate detection scheme is to digitize the received waveform and calculate the centroid as the pulse arrival time. The centroid detection always gives unbiased measurement even for asymmetric pulses. In this report, we analyze the laser altimeter ranging errors for these three detection schemes using the Mars Orbital Laser Altimeter (MOLA) as an example.

  14. A New Strategy to Reduce Influenza Escape: Detecting Therapeutic Targets Constituted of Invariance Groups

    PubMed Central

    Lao, Julie; Vanet, Anne

    2017-01-01

    The pathogenicity of the different flu species is a real public health problem worldwide. To combat this scourge, we established a method to detect drug targets, reducing the possibility of escape. Besides being able to attach a drug candidate, these targets should have the main characteristic of being part of an essential viral function. The invariance groups that are sets of residues bearing an essential function can be detected genetically. They consist of invariant and synthetic lethal residues (interdependent residues not varying or slightly varying when together). We analyzed an alignment of more than 10,000 hemagglutinin sequences of influenza to detect six invariance groups, close in space, and on the protein surface. In parallel we identified five potential pockets on the surface of hemagglutinin. By combining these results, three potential binding sites were determined that are composed of invariance groups located respectively in the vestigial esterase domain, in the bottom of the stem and in the fusion area. The latter target is constituted of residues involved in the spring-loaded mechanism, an essential step in the fusion process. We propose a model describing how this potential target could block the reorganization of the hemagglutinin HA2 secondary structure and prevent viral entry into the host cell. PMID:28257108

  15. The effect of targeted wide age range SIAs in reducing measles incidence in the African Region.

    PubMed

    Masresha, Balcha; Luce, Richard; Katsande, Regis; Fall, Amadou; Eshetu, Meseret; Mihigo, Richard

    2017-01-01

    Periodic measles supplemental immunisation activities (SIAs) increase population immunity and thereby reduce the pool of accumulated susceptible children. They are typically conducted every 2 - 4 years, and most often target children up to five years of age. Between 2012 and 2015, after surveillance data indicated a shift in the epidemiological profile of measles towards older age groups, 11 countries were supported to conduct wide age range SIAs based on their local epidemiological patterns. Six other countries conducted SIAs with measles-rubella vaccines targeting ages 9 months to 14 years as an initial step of introducing rubella vaccine into the immunization program. In subsequent years, the incidence of confirmed measles dropped significantly in 13 of the 17 countries reviewed. The findings emphasize the importance of well-functioning surveillance systems, and the benefits of using of surveillance data to determine the specific target age-range for periodic SIAs to accelerate progress towards measles elimination.

  16. The effect of targeted wide age range SIAs in reducing measles incidence in the African Region

    PubMed Central

    Masresha, Balcha; Luce, Richard; Katsande, Regis; Fall, Amadou; Eshetu, Meseret; Mihigo, Richard

    2017-01-01

    Periodic measles supplemental immunisation activities (SIAs) increase population immunity and thereby reduce the pool of accumulated susceptible children. They are typically conducted every 2 – 4 years, and most often target children up to five years of age. Between 2012 and 2015, after surveillance data indicated a shift in the epidemiological profile of measles towards older age groups, 11 countries were supported to conduct wide age range SIAs based on their local epidemiological patterns. Six other countries conducted SIAs with measles-rubella vaccines targeting ages 9 months to 14 years as an initial step of introducing rubella vaccine into the immunization program. In subsequent years, the incidence of confirmed measles dropped significantly in 13 of the 17 countries reviewed. The findings emphasize the importance of well-functioning surveillance systems, and the benefits of using of surveillance data to determine the specific target age-range for periodic SIAs to accelerate progress towards measles elimination. PMID:29296148

  17. Searching the optimal PTH target range in children undergoing peritoneal dialysis: new insights from international cohort studies.

    PubMed

    Haffner, Dieter; Schaefer, Franz

    2013-04-01

    The treatment of the mineral and bone disorder associated with chronic kidney disease (CKD-MBD) remains a major challenge in pediatric patients. The principal aims of therapeutic measures are not only to prevent the debilitating skeletal complications and to achieve normal growth but also to preserve long-term cardiovascular health. Serum parathyroid hormone (PTH) levels are used as a surrogate parameter of bone turnover. Whereas it is generally accepted that serum calcium and phosphate levels should be kept within the range for age, current pediatric consensus guidelines differ markedly with respect to the optimal PTH target range and operate on a limited evidence base. Recently, the International Pediatric Dialysis Network (IPPN) established a global registry collecting detailed clinical and biochemical information, including data relevant to CKD-MBD in children on chronic peritoneal dialysis (PD). This review highlights the current evidence basis regarding the optimal PTH target range in pediatric CKD patients, and re-assesses the current guidelines in view of the outcome data collected by the IPPN registry. Based on a comprehensive evaluation of CKD-MBD outcome measures in this global patient cohort, a PTH target range of 1.7-3 times the upper limit of normal (i.e. 100-200 pg/ml) appears reasonable in children undergoing chronic PD.

  18. Thermoacoustic molecular tomography with magnetic nanoparticle contrast agents for targeted tumor detection.

    PubMed

    Nie, Liming; Ou, Zhongmin; Yang, Sihua; Xing, Da

    2010-08-01

    The primary feasibility steps of demonstrating the ability of microwave-induced thermoacoustic (TA) in phantoms have been previously reported. However, none were shown to target a diseased site in living subjects in thermoacoustic tomography (TAT) field so far. To determine the expressions of oncogenic surface molecules, it is quite necessary to image tumor lesions and acquire pathogenic status on them via TAT. Compared to biological tissues, iron oxide nanoparticles have a much higher microwave absorbance. Fe3O4/polyaniline (PANI) nanoparticles were prepared via polymerization of aniline in the Fe304 superparamagnetic fluids. Then Fe3O4/PANI was conjugated to folic acid (FA), which can bind specifically to the surface of the folate receptor used as a tumor marker. FA-Fe3O4/PANI targeted tumor was irradiated by pulsed microwave at 6 GHz for thermoacoustic detection and imaging. The effect of the Fe3O4/PANI superparamagnetic nanoparticles for enhancing TAT images was successfully investigated in ex vivo human blood and in vivo mouse tail. Intravenous administration of the targeted nanoparticles to mice bearing tumors showed fivefold greater thermoacoustic signal and much longer elimination time than that of mice injected with nontargeted nanoparticles in the tumor. The specific targeting ability of FA-Fe3O4/PANI to tumor was also verified on fluorescence microscopy. Fabricated iron oxide nanoparticles conjugated with tumor ligands for targeted TAT tumor detection at the molecular level was reported for the first time. The results indicate that thermoacoustic molecular imaging with functionalized iron oxide nanoparticles may contribute to targeted and functional early cancer imaging. Also, the modified iron oxide nanoparticles combined with suitable tumor markers may also be used as novel nanomaterials for targeted and guided cancer thermal therapy.

  19. Dependency of human target detection performance on clutter and quality of supporting image analysis algorithms in a video surveillance task

    NASA Astrophysics Data System (ADS)

    Huber, Samuel; Dunau, Patrick; Wellig, Peter; Stein, Karin

    2017-10-01

    Background: In target detection, the success rates depend strongly on human observer performances. Two prior studies tested the contributions of target detection algorithms and prior training sessions. The aim of this Swiss-German cooperation study was to evaluate the dependency of human observer performance on the quality of supporting image analysis algorithms. Methods: The participants were presented 15 different video sequences. Their task was to detect all targets in the shortest possible time. Each video sequence showed a heavily cluttered simulated public area from a different viewing angle. In each video sequence, the number of avatars in the area was altered to 100, 150 and 200 subjects. The number of targets appearing was kept at 10%. The number of marked targets varied from 0, 5, 10, 20 up to 40 marked subjects while keeping the positive predictive value of the detection algorithm at 20%. During the task, workload level was assessed by applying an acoustic secondary task. Detection rates and detection times for the targets were analyzed using inferential statistics. Results: The study found Target Detection Time to increase and Target Detection Rates to decrease with increasing numbers of avatars. The same is true for the Secondary Task Reaction Time while there was no effect on Secondary Task Hit Rate. Furthermore, we found a trend for a u-shaped correlation between the numbers of markings and RTST indicating increased workload. Conclusion: The trial results may indicate useful criteria for the design of training and support of observers in observational tasks.

  20. A target detection multi-layer matched filter for color and hyperspectral cameras

    NASA Astrophysics Data System (ADS)

    Miyanishi, Tomoya; Preece, Bradley L.; Reynolds, Joseph P.

    2018-05-01

    In this article, a method for applying matched filters to a 3-dimentional hyperspectral data cube is discussed. In many applications, color visible cameras or hyperspectral cameras are used for target detection where the color or spectral optical properties of the imaged materials are partially known in advance. Therefore, the use of matched filtering with spectral data along with shape data is an effective method for detecting certain targets. Since many methods for 2D image filtering have been researched, we propose a multi-layer filter where ordinary spatially matched filters are used before the spectral filters. We discuss a way to layer the spectral filters for a 3D hyperspectral data cube, accompanied by a detectability metric for calculating the SNR of the filter. This method is appropriate for visible color cameras and hyperspectral cameras. We also demonstrate an analysis using the Night Vision Integrated Performance Model (NV-IPM) and a Monte Carlo simulation in order to confirm the effectiveness of the filtering in providing a higher output SNR and a lower false alarm rate.

  1. Multispectral image fusion for target detection

    NASA Astrophysics Data System (ADS)

    Leviner, Marom; Maltz, Masha

    2009-09-01

    Various different methods to perform multi-spectral image fusion have been suggested, mostly on the pixel level. However, the jury is still out on the benefits of a fused image compared to its source images. We present here a new multi-spectral image fusion method, multi-spectral segmentation fusion (MSSF), which uses a feature level processing paradigm. To test our method, we compared human observer performance in an experiment using MSSF against two established methods: Averaging and Principle Components Analysis (PCA), and against its two source bands, visible and infrared. The task that we studied was: target detection in the cluttered environment. MSSF proved superior to the other fusion methods. Based on these findings, current speculation about the circumstances in which multi-spectral image fusion in general and specific fusion methods in particular would be superior to using the original image sources can be further addressed.

  2. 10-fold detection range increase in quadrant-photodiode position sensing for photonic force microscope

    NASA Astrophysics Data System (ADS)

    Perrone, Sandro; Volpe, Giovanni; Petrov, Dmitri

    2008-10-01

    We propose a technique that permits one to increase by one order of magnitude the detection range of position sensing for the photonic force microscope with quadrant photodetectors (QPDs). This technique takes advantage of the unavoidable cross-talk between output signals of the QPD and does not assume that the output signals are linear in the probe displacement. We demonstrate the increase in the detection range from 150 to 1400 nm for a trapped polystyrene sphere with radius of 300 nm as probe.

  3. 10-fold detection range increase in quadrant-photodiode position sensing for photonic force microscope

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Perrone, Sandro; Volpe, Giovanni; Petrov, Dmitri

    2008-10-15

    We propose a technique that permits one to increase by one order of magnitude the detection range of position sensing for the photonic force microscope with quadrant photodetectors (QPDs). This technique takes advantage of the unavoidable cross-talk between output signals of the QPD and does not assume that the output signals are linear in the probe displacement. We demonstrate the increase in the detection range from 150 to 1400 nm for a trapped polystyrene sphere with radius of 300 nm as probe.

  4. 10-fold detection range increase in quadrant-photodiode position sensing for photonic force microscope.

    PubMed

    Perrone, Sandro; Volpe, Giovanni; Petrov, Dmitri

    2008-10-01

    We propose a technique that permits one to increase by one order of magnitude the detection range of position sensing for the photonic force microscope with quadrant photodetectors (QPDs). This technique takes advantage of the unavoidable cross-talk between output signals of the QPD and does not assume that the output signals are linear in the probe displacement. We demonstrate the increase in the detection range from 150 to 1400 nm for a trapped polystyrene sphere with radius of 300 nm as probe.

  5. Detecting Topological Defect Dark Matter Using Coherent Laser Ranging System

    PubMed Central

    Yang, Wanpeng; Leng, Jianxiao; Zhang, Shuangyou; Zhao, Jianye

    2016-01-01

    In the last few decades, optical frequency combs with high intensity, broad optical bandwidth, and directly traceable discrete wavelengths have triggered rapid developments in distance metrology. However, optical frequency combs to date have been limited to determine the absolute distance to an object (such as satellite missions). We propose a scheme for the detection of topological defect dark matter using a coherent laser ranging system composed of dual-combs and an optical clock via nongravitational signatures. The dark matter field, which comprises a defect, may interact with standard model particles, including quarks and photons, resulting in the alteration of their masses. Thus, a topological defect may function as a dielectric material with a distinctive frequency-depend index of refraction, which would cause the time delay of a periodic extraterrestrial or terrestrial light. When a topological defect passes through the Earth, the optical path of long-distance vacuum path is altered, this change in optical path can be detected through the coherent laser ranging system. Compared to continuous wavelength(cw) laser interferometry methods, dual-comb interferometry in our scheme excludes systematic misjudgement by measuring the absolute optical path length. PMID:27389642

  6. Single photon detection and timing in the Lunar Laser Ranging Experiment.

    NASA Technical Reports Server (NTRS)

    Poultney, S. K.

    1972-01-01

    The goals of the Lunar Laser Ranging Experiment lead to the need for the measurement of a 2.5 sec time interval to an accuracy of a nanosecond or better. The systems analysis which included practical retroreflector arrays, available laser systems, and large telescopes led to the necessity of single photon detection. Operation under all background illumination conditions required auxiliary range gates and extremely narrow spectral and spatial filters in addition to the effective gate provided by the time resolution. Nanosecond timing precision at relatively high detection efficiency was obtained using the RCA C31000F photomultiplier and Ortec 270 constant fraction of pulse-height timing discriminator. The timing accuracy over the 2.5 sec interval was obtained using a digital interval with analog vernier ends. Both precision and accuracy are currently checked internally using a triggerable, nanosecond light pulser. Future measurements using sub-nanosecond laser pulses will be limited by the time resolution of single photon detectors.

  7. Multiplexed target detection using DNA-binding dye chemistry in droplet digital PCR.

    PubMed

    McDermott, Geoffrey P; Do, Duc; Litterst, Claudia M; Maar, Dianna; Hindson, Christopher M; Steenblock, Erin R; Legler, Tina C; Jouvenot, Yann; Marrs, Samuel H; Bemis, Adam; Shah, Pallavi; Wong, Josephine; Wang, Shenglong; Sally, David; Javier, Leanne; Dinio, Theresa; Han, Chunxiao; Brackbill, Timothy P; Hodges, Shawn P; Ling, Yunfeng; Klitgord, Niels; Carman, George J; Berman, Jennifer R; Koehler, Ryan T; Hiddessen, Amy L; Walse, Pramod; Bousse, Luc; Tzonev, Svilen; Hefner, Eli; Hindson, Benjamin J; Cauly, Thomas H; Hamby, Keith; Patel, Viresh P; Regan, John F; Wyatt, Paul W; Karlin-Neumann, George A; Stumbo, David P; Lowe, Adam J

    2013-12-03

    Two years ago, we described the first droplet digital PCR (ddPCR) system aimed at empowering all researchers with a tool that removes the substantial uncertainties associated with using the analogue standard, quantitative real-time PCR (qPCR). This system enabled TaqMan hydrolysis probe-based assays for the absolute quantification of nucleic acids. Due to significant advancements in droplet chemistry and buoyed by the multiple benefits associated with dye-based target detection, we have created a "second generation" ddPCR system compatible with both TaqMan-probe and DNA-binding dye detection chemistries. Herein, we describe the operating characteristics of DNA-binding dye based ddPCR and offer a side-by-side comparison to TaqMan probe detection. By partitioning each sample prior to thermal cycling, we demonstrate that it is now possible to use a DNA-binding dye for the quantification of multiple target species from a single reaction. The increased resolution associated with partitioning also made it possible to visualize and account for signals arising from nonspecific amplification products. We expect that the ability to combine the precision of ddPCR with both DNA-binding dye and TaqMan probe detection chemistries will further enable the research community to answer complex and diverse genetic questions.

  8. 33 CFR 334.200 - Chesapeake Bay, Point Lookout to Cedar Point; aerial and surface firing range and target area, U...

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... Cedar Point; aerial and surface firing range and target area, U.S. Naval Air Station, Patuxent River... Chesapeake Bay, Point Lookout to Cedar Point; aerial and surface firing range and target area, U.S. Naval Air Station, Patuxent River, Maryland, danger zones. (a) Aerial firing range—(1) The danger zone. The waters...

  9. 33 CFR 334.200 - Chesapeake Bay, Point Lookout to Cedar Point; aerial and surface firing range and target area, U...

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... Cedar Point; aerial and surface firing range and target area, U.S. Naval Air Station, Patuxent River... Chesapeake Bay, Point Lookout to Cedar Point; aerial and surface firing range and target area, U.S. Naval Air Station, Patuxent River, Maryland, danger zones. (a) Aerial firing range—(1) The danger zone. The waters...

  10. 33 CFR 334.200 - Chesapeake Bay, Point Lookout to Cedar Point; aerial and surface firing range and target area, U...

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... Cedar Point; aerial and surface firing range and target area, U.S. Naval Air Station, Patuxent River... Chesapeake Bay, Point Lookout to Cedar Point; aerial and surface firing range and target area, U.S. Naval Air Station, Patuxent River, Maryland, danger zones. (a) Aerial firing range—(1) The danger zone. The waters...

  11. Study on a novel laser target detection system based on software radio technique

    NASA Astrophysics Data System (ADS)

    Song, Song; Deng, Jia-hao; Wang, Xue-tian; Gao, Zhen; Sun, Ji; Sun, Zhi-hui

    2008-12-01

    This paper presents that software radio technique is applied to laser target detection system with the pseudo-random code modulation. Based on the theory of software radio, the basic framework of the system, hardware platform, and the implementation of the software system are detailed. Also, the block diagram of the system, DSP circuit, block diagram of the pseudo-random code generator, and soft flow diagram of signal processing are designed. Experimental results have shown that the application of software radio technique provides a novel method to realize the modularization, miniaturization and intelligence of the laser target detection system, and the upgrade and improvement of the system will become simpler, more convenient, and cheaper.

  12. Surveillance theory applied to virus detection: a case for targeted discovery

    USGS Publications Warehouse

    Bogich, Tiffany L.; Anthony, Simon J.; Nichols, James D.

    2013-01-01

    Virus detection and mathematical modeling have gone through rapid developments in the past decade. Both offer new insights into the epidemiology of infectious disease and characterization of future risk; however, modeling has not yet been applied to designing the best surveillance strategies for viral and pathogen discovery. We review recent developments and propose methods to integrate viral and pathogen discovery and mathematical modeling through optimal surveillance theory, arguing for a more targeted approach to novel virus detection guided by the principles of adaptive management and structured decision-making.

  13. An insertion approach electrochemical aptasensor for mucin 1 detection based on exonuclease-assisted target recycling.

    PubMed

    Wen, Wei; Hu, Rong; Bao, Ting; Zhang, Xiuhua; Wang, Shengfu

    2015-09-15

    In this work, a sensitive exonuclease-assisted amplification electrochemical aptasensor through insertion approach was developed for the detection of mucin 1 (MUC 1). In order to construct the aptasensor, 6-Mercapto-1-hexanol (MCH) was used to block partial sites of gold electrode (GE), followed by thiolated capture probe self-assembled on GE. Methylene blue (MB) labeled aptamer hybridized with capture probe at both ends to form double-strand DNA. For the MB labeled termini was close to GE, the electrochemical response was remarkable. The presence of MUC 1 caused the dissociation of the double-strand DNA owing to the specific recognition of aptamer to MUC 1. Then exonuclease I (Exo I) selectively digested the aptamer which bound with MUC 1, the released MUC 1 participated new binding with the rest aptamer. Insertion approach improved the reproducibility and Exo I-catalyzed target recycling improved the sensitivity of the aptasensor significantly. Under optimal experimental conditions, the proposed aptasensor had a good linear correlation ranged from 10 pM to 1 μM with a detection limit of 4 pM (Signal to Noise ratio, S/N=3). The strategy had great potential for the simple and sensitive detection of other cancer markers. Copyright © 2015 Elsevier B.V. All rights reserved.

  14. Constant-Envelope Waveform Design for Optimal Target-Detection and Autocorrelation Performances

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Sen, Satyabrata

    2013-01-01

    We propose an algorithm to directly synthesize in time-domain a constant-envelope transmit waveform that achieves the optimal performance in detecting an extended target in the presence of signal-dependent interference. This approach is in contrast to the traditional indirect methods that synthesize the transmit signal following the computation of the optimal energy spectral density. Additionally, we aim to maintain a good autocorrelation property of the designed signal. Therefore, our waveform design technique solves a bi-objective optimization problem in order to simultaneously improve the detection and autocorrelation performances, which are in general conflicting in nature. We demonstrate this compromising characteristics of themore » detection and autocorrelation performances with numerical examples. Furthermore, in the absence of the autocorrelation criterion, our designed signal is shown to achieve a near-optimum detection performance.« less

  15. Testing & Evaluation of Close-Range SAR for Monitoring & Automatically Detecting Pavement Conditions

    DOT National Transportation Integrated Search

    2012-01-01

    This report summarizes activities in support of the DOT contract on Testing & Evaluating Close-Range SAR for Monitoring & Automatically Detecting Pavement Conditions & Improve Visual Inspection Procedures. The work of this project was performed by Dr...

  16. Controlling range expansion in habitat networks by adaptively targeting source populations.

    PubMed

    Hock, Karlo; Wolff, Nicholas H; Beeden, Roger; Hoey, Jessica; Condie, Scott A; Anthony, Kenneth R N; Possingham, Hugh P; Mumby, Peter J

    2016-08-01

    Controlling the spread of invasive species, pests, and pathogens is often logistically limited to interventions that target specific locations at specific periods. However, in complex, highly connected systems, such as marine environments connected by ocean currents, populations spread dynamically in both space and time via transient connectivity links. This results in nondeterministic future distributions of species in which local populations emerge dynamically and concurrently over a large area. The challenge, therefore, is to choose intervention locations that will maximize the effectiveness of the control efforts. We propose a novel method to manage dynamic species invasions and outbreaks that identifies the intervention locations most likely to curtail population expansion by selectively targeting local populations most likely to expand their future range. Critically, at any point during the development of the invasion or outbreak, the method identifies the local intervention that maximizes the long-term benefit across the ecosystem by restricting species' potential to spread. In so doing, the method adaptively selects the intervention targets under dynamically changing circumstances. To illustrate the effectiveness of the method we applied it to controlling the spread of crown-of-thorns starfish (Acanthaster sp.) outbreaks across Australia's Great Barrier Reef. Application of our method resulted in an 18-fold relative improvement in management outcomes compared with a random targeting of reefs in putative starfish control scenarios. Although we focused on applying the method to reducing the spread of an unwanted species, it can also be used to facilitate the spread of desirable species through connectivity networks. For example, the method could be used to select those fragments of habitat most likely to rebuild a population if they were sufficiently well protected. © 2016 Society for Conservation Biology.

  17. Selective tuning of the right inferior frontal gyrus during target detection

    PubMed Central

    Hampshire, Adam; Thompson, Russell; Duncan, John; Owen, Adrian M.

    2010-01-01

    In the human brain, a network of frontal and parietal regions is commonly recruited during tasks that demand the deliberate, focused control of thought and action. Previously, using a simple target detection task, we reported striking differences in the selectivity of the BOLD response in anatomically distinct subregions of this network. In particular, it was observed that the right inferior frontal gyrus (IFG) followed a tightly tuned function, selectively responding only to the current target object. Here, we examine this functional specialization further, using adapted versions of our original task. Our results demonstrate that the response of the right IFG to targets is a strong and replicable phenomenon. It occurs under increased attentional load, when targets and distractors are equally frequent, and when controlling for inhibitory processes. These findings support the hypothesis that the right IFG responds selectively to those items that are of the most relevance to the currently intended task schema. PMID:19246331

  18. Imaging of targeted lipid microbubbles to detect cancer cells using third harmonic generation microscopy

    PubMed Central

    Harpel, Kaitlin; Baker, Robert Dawson; Amirsolaimani, Babak; Mehravar, Soroush; Vagner, Josef; Matsunaga, Terry O.; Banerjee, Bhaskar; Kieu, Khanh

    2016-01-01

    The use of receptor-targeted lipid microbubbles imaged by ultrasound is an innovative method of detecting and localizing disease. However, since ultrasound requires a medium between the transducer and the object being imaged, it is impractical to apply to an exposed surface in a surgical setting where sterile fields need be maintained and ultrasound gel may cause the bubbles to collapse. Multiphoton microscopy (MPM) is an emerging tool for accurate, label-free imaging of tissues and cells with high resolution and contrast. We have recently determined a novel application of MPM to be used for detecting targeted microbubble adherence to the upregulated plectin-receptor on pancreatic tumor cells. Specifically, the third-harmonic generation response can be used to detect bound microbubbles to various cell types presenting MPM as an alternative and useful imaging method. This is an interesting technique that can potentially be translated as a diagnostic tool for the early detection of cancer and inflammatory disorders. PMID:27446711

  19. Deep Long-period Seismicity Beneath the Executive Committee Range, Marie Byrd Land, Antarctica, Studied Using Subspace Detection

    NASA Astrophysics Data System (ADS)

    Aster, R. C.; McMahon, N. D.; Myers, E. K.; Lough, A. C.

    2015-12-01

    Lough et al. (2014) first detected deep sub-icecap magmatic events beneath the Executive Committee Range volcanoes of Marie Byrd Land. Here, we extend the identification and analysis of these events in space and time utilizing subspace detection. Subspace detectors provide a highly effective methodology for studying events within seismic swarms that have similar moment tensor and Green's function characteristics and are particularly effective for identifying low signal-to-noise events. Marie Byrd Land (MBL) is an extremely remote continental region that is nearly completely covered by the West Antarctic Ice Sheet (WAIS). The southern extent of Marie Byrd Land lies within the West Antarctic Rift System (WARS), which includes the volcanic Executive Committee Range (ECR). The ECR shows north-to-south progression of volcanism across the WARS during the Holocene. In 2013, the POLENET/ANET seismic data identified two swarms of seismic activity in 2010 and 2011. These events have been interpreted as deep, long-period (DLP) earthquakes based on depth (25-40 km) and low frequency content. The DLP events in MBL lie beneath an inferred sub-WAIS volcanic edifice imaged with ice penetrating radar and have been interpreted as a present location of magmatic intrusion. The magmatic swarm activity in MBL provides a promising target for advanced subspace detection and temporal, spatial, and event size analysis of an extensive deep long period earthquake swarm using a remote seismographic network. We utilized a catalog of 1,370 traditionally identified DLP events to construct subspace detectors for the six nearest stations and analyzed two years of data spanning 2010-2011. Association of these detections into events resulted in an approximate ten-fold increase in number of locatable earthquakes. In addition to the two previously identified swarms during early 2010 and early 2011, we find sustained activity throughout the two years of study that includes several previously

  20. Optimal Detection Range of RFID Tag for RFID-based Positioning System Using the k-NN Algorithm.

    PubMed

    Han, Soohee; Kim, Junghwan; Park, Choung-Hwan; Yoon, Hee-Cheon; Heo, Joon

    2009-01-01

    Positioning technology to track a moving object is an important and essential component of ubiquitous computing environments and applications. An RFID-based positioning system using the k-nearest neighbor (k-NN) algorithm can determine the position of a moving reader from observed reference data. In this study, the optimal detection range of an RFID-based positioning system was determined on the principle that tag spacing can be derived from the detection range. It was assumed that reference tags without signal strength information are regularly distributed in 1-, 2- and 3-dimensional spaces. The optimal detection range was determined, through analytical and numerical approaches, to be 125% of the tag-spacing distance in 1-dimensional space. Through numerical approaches, the range was 134% in 2-dimensional space, 143% in 3-dimensional space.

  1. Using personal glucose meters and functional DNA sensors to quantify a variety of analytical targets

    PubMed Central

    Xiang, Yu; Lu, Yi

    2012-01-01

    Portable, low-cost and quantitative detection of a broad range of targets at home and in the field has the potential to revolutionize medical diagnostics and environmental monitoring. Despite many years of research, very few such devices are commercially available. Taking advantage of the wide availability and low cost of the pocket-sized personal glucose meter—used worldwide by diabetes sufferers—we demonstrate a method to use such meters to quantify non-glucose targets, ranging from a recreational drug (cocaine, 3.4 μM detection limit) to an important biological cofactor (adenosine, 18 μM detection limit), to a disease marker (interferon-gamma of tuberculosis, 2.6 nM detection limit) and a toxic metal ion (uranium, 9.1 nM detection limit). The method is based on the target-induced release of invertase from a functional-DNA–invertase conjugate. The released invertase converts sucrose into glucose, which is detectable using the meter. The approach should be easily applicable to the detection of many other targets through the use of suitable functional-DNA partners (aptamers DNAzymes or aptazymes). PMID:21860458

  2. Using personal glucose meters and functional DNA sensors to quantify a variety of analytical targets

    NASA Astrophysics Data System (ADS)

    Xiang, Yu; Lu, Yi

    2011-09-01

    Portable, low-cost and quantitative detection of a broad range of targets at home and in the field has the potential to revolutionize medical diagnostics and environmental monitoring. Despite many years of research, very few such devices are commercially available. Taking advantage of the wide availability and low cost of the pocket-sized personal glucose meter—used worldwide by diabetes sufferers—we demonstrate a method to use such meters to quantify non-glucose targets, ranging from a recreational drug (cocaine, 3.4 µM detection limit) to an important biological cofactor (adenosine, 18 µM detection limit), to a disease marker (interferon-gamma of tuberculosis, 2.6 nM detection limit) and a toxic metal ion (uranium, 9.1 nM detection limit). The method is based on the target-induced release of invertase from a functional-DNA-invertase conjugate. The released invertase converts sucrose into glucose, which is detectable using the meter. The approach should be easily applicable to the detection of many other targets through the use of suitable functional-DNA partners (aptamers, DNAzymes or aptazymes).

  3. Discriminating between camouflaged targets by their time of detection by a human-based observer assessment method

    NASA Astrophysics Data System (ADS)

    Selj, G. K.; Søderblom, M.

    2015-10-01

    Detection of a camouflaged object in natural sceneries requires the target to be distinguishable from its local background. The development of any new camouflage pattern therefore has to rely on a well-founded test methodology - which has to be correlated with the final purpose of the pattern - as well as an evaluation procedure, containing the optimal criteria for i) discriminating between the targets and then eventually ii) for a final rank of the targets. In this study we present results from a recent camouflage assessment trial where human observers were used in a search by photo methodology to assess generic test camouflage patterns. We conducted a study to investigate possible improvements in camouflage patterns for battle dress uniforms. The aim was to do a comparative study of potential, and generic patterns intended for use in arid areas (sparsely vegetated, semi desert). We developed a test methodology that was intended to be simple, reliable and realistic with respect to the operational benefit of camouflage. Therefore we chose to conduct a human based observer trial founded on imagery of realistic targets in natural backgrounds. Inspired by a recent and similar trial in the UK, we developed new and purpose-based software to be able to conduct the observer trial. Our preferred assessment methodology - the observer trial - was based on target recordings in 12 different, but operational relevant scenes, collected in a dry and sparsely vegetated area (Rhodes). The scenes were chosen with the intention to span as broadly as possible. The targets were human-shaped mannequins and were situated identically in each of the scenes to allow for a relative comparison of camouflage effectiveness in each scene. Test of significance, among the targets' performance, was carried out by non-parametric tests as the corresponding time of detection distributions in overall were found to be difficult to parameterize. From the trial, containing 12 different scenes from

  4. Effects of extraneous odors on canine detection

    NASA Astrophysics Data System (ADS)

    Waggoner, L. Paul; Jones, Meredith H.; Williams, Marc; Johnston, J. M.; Edge, Cindy C.; Petrousky, James A.

    1998-12-01

    Dogs are often required to detect target substances under challenging conditions. One of these challenges is to detect contraband in the presence of extraneous odors, whether they are part of the ambient environment or placed there for the purpose of evading detection. This paper presents the results of two studies evaluating the ability of dogs to detect target substances in the presence of varying concentrations of extraneous odors. The studies were conducted under behavioral laboratory conditions, providing good control over vapor sources and a clear basis for evaluation of detection responses. Dogs were trained to sample an air stream consisting of the extraneous odor only or the extraneous odor plus the target odor and then press the appropriate lever to earn food. The results are described in terns of the ability of dogs to detect target odors in the presence of a wide range of concentrations of the extraneous odors.

  5. Targeted detection of murine colonic dysplasia in vivo with flexible multispectral scanning fiber endoscopy

    NASA Astrophysics Data System (ADS)

    Joshi, Bishnu P.; Miller, Sharon J.; Lee, Cameron; Gustad, Adam; Seibel, Eric J.; Wang, Thomas D.

    2012-02-01

    We demonstrate a multi-spectral scanning fiber endoscope (SFE) that collects fluorescence images in vivo from three target peptides that bind specifically to murine colonic adenomas. This ultrathin endoscope was demonstrated in a genetically engineered mouse model of spontaneous colorectal adenomas based on somatic Apc (adenomatous polyposis coli) gene inactivation. The SFE delivers excitation at 440, 532, 635 nm with <2 mW per channel. The target 7-mer peptides were conjugated to visible organic dyes, including 7-Diethylaminocoumarin-3-carboxylic acid (DEAC) (λex=432 nm, λem=472 nm), 5-Carboxytetramethylrhodamine (5-TAMRA) (λex=535 nm, λem=568 nm), and CF-633 (λex=633 nm, λem=650 nm). Target peptides were first validated using techniques of pfu counting, flow cytometry and previously established methods of fluorescence endoscopy. Peptides were applied individually or in combination and detected with fluorescence imaging. The ability to image multiple channels of fluorescence concurrently was successful for all three channels in vitro, while two channels were resolved simultaneously in vivo. Selective binding of the peptide was evident to adenomas and not to adjacent normal-appearing mucosa. Multispectral wide-field fluorescence detection using the SFE is achievable, and this technology has potential to advance early cancer detection and image-guided therapy in human patients by simultaneously visualizing multiple over expressed molecular targets unique to dysplasia.

  6. A new comprehensive method for detection of livestock-related pathogenic viruses using a target enrichment system.

    PubMed

    Oba, Mami; Tsuchiaka, Shinobu; Omatsu, Tsutomu; Katayama, Yukie; Otomaru, Konosuke; Hirata, Teppei; Aoki, Hiroshi; Murata, Yoshiteru; Makino, Shinji; Nagai, Makoto; Mizutani, Tetsuya

    2018-01-08

    We tested usefulness of a target enrichment system SureSelect, a comprehensive viral nucleic acid detection method, for rapid identification of viral pathogens in feces samples of cattle, pigs and goats. This system enriches nucleic acids of target viruses in clinical/field samples by using a library of biotinylated RNAs with sequences complementary to the target viruses. The enriched nucleic acids are amplified by PCR and subjected to next generation sequencing to identify the target viruses. In many samples, SureSelect target enrichment method increased efficiencies for detection of the viruses listed in the biotinylated RNA library. Furthermore, this method enabled us to determine nearly full-length genome sequence of porcine parainfluenza virus 1 and greatly increased Breadth, a value indicating the ratio of the mapping consensus length in the reference genome, in pig samples. Our data showed usefulness of SureSelect target enrichment system for comprehensive analysis of genomic information of various viruses in field samples. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. Multitarget detection algorithm for automotive FMCW radar

    NASA Astrophysics Data System (ADS)

    Hyun, Eugin; Oh, Woo-Jin; Lee, Jong-Hun

    2012-06-01

    Today, 77 GHz FMCW (Frequency Modulation Continuous Wave) radar has strong advantages of range and velocity detection for automotive applications. However, FMCW radar brings out ghost targets and missed targets in multi-target situations. In this paper, in order to resolve these limitations, we propose an effective pairing algorithm, which consists of two steps. In the proposed method, a waveform with different slopes in two periods is used. In the 1st pairing processing, all combinations of range and velocity are obtained in each of two wave periods. In the 2nd pairing step, using the results of the 1st pairing processing, fine range and velocity are detected. In that case, we propose the range-velocity windowing technique in order to compensate for the non-ideal beat-frequency characteristic that arises due to the non-linearity of the RF module. Based on experimental results, the performance of the proposed algorithm is improved compared with that of the typical method.

  8. A false-alarm aware methodology to develop robust and efficient multi-scale infrared small target detection algorithm

    NASA Astrophysics Data System (ADS)

    Moradi, Saed; Moallem, Payman; Sabahi, Mohamad Farzan

    2018-03-01

    False alarm rate and detection rate are still two contradictory metrics for infrared small target detection in an infrared search and track system (IRST), despite the development of new detection algorithms. In certain circumstances, not detecting true targets is more tolerable than detecting false items as true targets. Hence, considering background clutter and detector noise as the sources of the false alarm in an IRST system, in this paper, a false alarm aware methodology is presented to reduce false alarm rate while the detection rate remains undegraded. To this end, advantages and disadvantages of each detection algorithm are investigated and the sources of the false alarms are determined. Two target detection algorithms having independent false alarm sources are chosen in a way that the disadvantages of the one algorithm can be compensated by the advantages of the other one. In this work, multi-scale average absolute gray difference (AAGD) and Laplacian of point spread function (LoPSF) are utilized as the cornerstones of the desired algorithm of the proposed methodology. After presenting a conceptual model for the desired algorithm, it is implemented through the most straightforward mechanism. The desired algorithm effectively suppresses background clutter and eliminates detector noise. Also, since the input images are processed through just four different scales, the desired algorithm has good capability for real-time implementation. Simulation results in term of signal to clutter ratio and background suppression factor on real and simulated images prove the effectiveness and the performance of the proposed methodology. Since the desired algorithm was developed based on independent false alarm sources, our proposed methodology is expandable to any pair of detection algorithms which have different false alarm sources.

  9. Simulation of sea surface wave influence on small target detection with airborne laser depth sounding.

    PubMed

    Tulldahl, H Michael; Steinvall, K Ove

    2004-04-20

    A theoretical model for simulation of airborne depth-sounding lidar is presented with the purpose of analyzing the influence from water surface waves on the ability to detect 1-m3 targets placed on the sea bottom. Although water clarity is the main limitation, sea surface waves can significantly affect the detectability. The detection probability for a target at a 9-m depth can be above 90% at 1-m/s wind and below 80% at 6-m/s wind for the same water clarity. The simulation model contains both numerical and analytical components. Simulated data are compared with measured data and give realistic results for bottom depths between 3 and 10 m.

  10. Shilling Attacks Detection in Recommender Systems Based on Target Item Analysis

    PubMed Central

    Zhou, Wei; Wen, Junhao; Koh, Yun Sing; Xiong, Qingyu; Gao, Min; Dobbie, Gillian; Alam, Shafiq

    2015-01-01

    Recommender systems are highly vulnerable to shilling attacks, both by individuals and groups. Attackers who introduce biased ratings in order to affect recommendations, have been shown to negatively affect collaborative filtering (CF) algorithms. Previous research focuses only on the differences between genuine profiles and attack profiles, ignoring the group characteristics in attack profiles. In this paper, we study the use of statistical metrics to detect rating patterns of attackers and group characteristics in attack profiles. Another question is that most existing detecting methods are model specific. Two metrics, Rating Deviation from Mean Agreement (RDMA) and Degree of Similarity with Top Neighbors (DegSim), are used for analyzing rating patterns between malicious profiles and genuine profiles in attack models. Building upon this, we also propose and evaluate a detection structure called RD-TIA for detecting shilling attacks in recommender systems using a statistical approach. In order to detect more complicated attack models, we propose a novel metric called DegSim’ based on DegSim. The experimental results show that our detection model based on target item analysis is an effective approach for detecting shilling attacks. PMID:26222882

  11. Modification of YAPE keypoint detection algorithm for wide local contrast range images

    NASA Astrophysics Data System (ADS)

    Lukoyanov, A.; Nikolaev, D.; Konovalenko, I.

    2018-04-01

    Keypoint detection is an important tool of image analysis, and among many contemporary keypoint detection algorithms YAPE is known for its computational performance, allowing its use in mobile and embedded systems. One of its shortcomings is high sensitivity to local contrast which leads to high detection density in high-contrast areas while missing detections in low-contrast ones. In this work we study the contrast sensitivity of YAPE and propose a modification which compensates for this property on images with wide local contrast range (Yet Another Contrast-Invariant Point Extractor, YACIPE). As a model example, we considered the traffic sign recognition problem, where some signs are well-lighted, whereas others are in shadows and thus have low contrast. We show that the number of traffic signs on the image of which has not been detected any keypoints is 40% less for the proposed modification compared to the original algorithm.

  12. Dual signal amplification for highly sensitive electrochemical detection of uropathogens via enzyme-based catalytic target recycling.

    PubMed

    Su, Jiao; Zhang, Haijie; Jiang, Bingying; Zheng, Huzhi; Chai, Yaqin; Yuan, Ruo; Xiang, Yun

    2011-11-15

    We report an ultrasensitive electrochemical approach for the detection of uropathogen sequence-specific DNA target. The sensing strategy involves a dual signal amplification process, which combines the signal enhancement by the enzymatic target recycling technique with the sensitivity improvement by the quantum dot (QD) layer-by-layer (LBL) assembled labels. The enzyme-based catalytic target DNA recycling process results in the use of each target DNA sequence for multiple times and leads to direct amplification of the analytical signal. Moreover, the LBL assembled QD labels can further enhance the sensitivity of the sensing system. The coupling of these two effective signal amplification strategies thus leads to low femtomolar (5fM) detection of the target DNA sequences. The proposed strategy also shows excellent discrimination between the target DNA and the single-base mismatch sequences. The advantageous intrinsic sequence-independent property of exonuclease III over other sequence-dependent enzymes makes our new dual signal amplification system a general sensing platform for monitoring ultralow level of various types of target DNA sequences. Copyright © 2011 Elsevier B.V. All rights reserved.

  13. A novel polydopamine-based chemiluminescence resonance energy transfer method for microRNA detection coupling duplex-specific nuclease-aided target recycling strategy.

    PubMed

    Wang, Qian; Yin, Bin-Cheng; Ye, Bang-Ce

    2016-06-15

    MicroRNAs (miRNAs), functioning as oncogenes or tumor suppressors, play significant regulatory roles in regulating gene expression and become as biomarkers for disease diagnostics and therapeutics. In this work, we have coupled a polydopamine (PDA) nanosphere-assisted chemiluminescence resonance energy transfer (CRET) platform and a duplex-specific nuclease (DSN)-assisted signal amplification strategy to develop a novel method for specific miRNA detection. With the assistance of hemin, luminol, and H2O2, the horseradish peroxidase (HRP)-mimicking G-rich sequence in the sensing probe produces chemiluminescence, which is quickly quenched by the CRET effect between PDA as energy acceptor and excited luminol as energy donor. The target miRNA triggers DSN to partially degrade the sensing probe in the DNA-miRNA heteroduplex to repeatedly release G-quadruplex formed by G-rich sequence from PDA for the production of chemiluminescence. The method allows quantitative detection of target miRNA in the range of 80 pM-50 nM with a detection limit of 49.6 pM. The method also shows excellent specificity to discriminate single-base differences, and can accurately quantify miRNA in biological samples, with good agreement with the result from a commercial miRNA detection kit. The procedure requires no organic dyes or labels, and is a simple and cost-effective method for miRNA detection for early clinical diagnosis. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. Diagnostic Accuracy of Multiparametric Magnetic Resonance Imaging and Fusion Guided Targeted Biopsy Evaluated by Transperineal Template Saturation Prostate Biopsy for the Detection and Characterization of Prostate Cancer.

    PubMed

    Mortezavi, Ashkan; Märzendorfer, Olivia; Donati, Olivio F; Rizzi, Gianluca; Rupp, Niels J; Wettstein, Marian S; Gross, Oliver; Sulser, Tullio; Hermanns, Thomas; Eberli, Daniel

    2018-02-21

    We evaluated the diagnostic accuracy of multiparametric magnetic resonance imaging and multiparametric magnetic resonance imaging/transrectal ultrasound fusion guided targeted biopsy against that of transperineal template saturation prostate biopsy to detect prostate cancer. We retrospectively analyzed the records of 415 men who consecutively presented for prostate biopsy between November 2014 and September 2016 at our tertiary care center. Multiparametric magnetic resonance imaging was performed using a 3 Tesla device without an endorectal coil, followed by transperineal template saturation prostate biopsy with the BiopSee® fusion system. Additional fusion guided targeted biopsy was done in men with a suspicious lesion on multiparametric magnetic resonance imaging, defined as Likert score 3 to 5. Any Gleason pattern 4 or greater was defined as clinically significant prostate cancer. The detection rates of multiparametric magnetic resonance imaging and fusion guided targeted biopsy were compared with the detection rate of transperineal template saturation prostate biopsy using the McNemar test. We obtained a median of 40 (range 30 to 55) and 3 (range 2 to 4) transperineal template saturation prostate biopsy and fusion guided targeted biopsy cores, respectively. Of the 124 patients (29.9%) without a suspicious lesion on multiparametric magnetic resonance imaging 32 (25.8%) were found to have clinically significant prostate cancer on transperineal template saturation prostate biopsy. Of the 291 patients (70.1%) with a Likert score of 3 to 5 clinically significant prostate cancer was detected in 129 (44.3%) by multiparametric magnetic resonance imaging fusion guided targeted biopsy, in 176 (60.5%) by transperineal template saturation prostate biopsy and in 187 (64.3%) by the combined approach. Overall 58 cases (19.9%) of clinically significant prostate cancer would have been missed if fusion guided targeted biopsy had been performed exclusively. The sensitivity of

  15. EzyAmp signal amplification cascade enables isothermal detection of nucleic acid and protein targets.

    PubMed

    Linardy, Evelyn M; Erskine, Simon M; Lima, Nicole E; Lonergan, Tina; Mokany, Elisa; Todd, Alison V

    2016-01-15

    Advancements in molecular biology have improved the ability to characterize disease-related nucleic acids and proteins. Recently, there has been an increasing desire for tests that can be performed outside of centralised laboratories. This study describes a novel isothermal signal amplification cascade called EzyAmp (enzymatic signal amplification) that is being developed for detection of targets at the point of care. EzyAmp exploits the ability of some restriction endonucleases to cleave substrates containing nicks within their recognition sites. EzyAmp uses two oligonucleotide duplexes (partial complexes 1 and 2) which are initially cleavage-resistant as they lack a complete recognition site. The recognition site of partial complex 1 can be completed by hybridization of a triggering oligonucleotide (Driver Fragment 1) that is generated by a target-specific initiation event. Binding of Driver Fragment 1 generates a completed complex 1, which upon cleavage, releases Driver Fragment 2. In turn, binding of Driver Fragment 2 to partial complex 2 creates completed complex 2 which when cleaved releases additional Driver Fragment 1. Each cleavage event separates fluorophore quencher pairs resulting in an increase in fluorescence. At this stage a cascade of signal production becomes independent of further target-specific initiation events. This study demonstrated that the EzyAmp cascade can facilitate detection and quantification of nucleic acid targets with sensitivity down to aM concentration. Further, the same cascade detected VEGF protein with a sensitivity of 20nM showing that this universal method for amplifying signal may be linked to the detection of different types of analytes in an isothermal format. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

  16. Complex background suppression using global-local registration strategy for the detection of small-moving target on moving platform

    NASA Astrophysics Data System (ADS)

    Zou, Tianhao; Zuo, Zhengrong

    2018-02-01

    Target detection is a very important and basic problem of computer vision and image processing. The most often case we meet in real world is a detection task for a moving-small target on moving platform. The commonly used methods, such as Registration-based suppression, can hardly achieve a desired result. To crack this hard nut, we introduce a Global-local registration based suppression method. Differ from the traditional ones, the proposed Global-local Registration Strategy consider both the global consistency and the local diversity of the background, obtain a better performance than normal background suppression methods. In this paper, we first discussed the features about the small-moving target detection on unstable platform. Then we introduced a new strategy and conducted an experiment to confirm its noisy stability. In the end, we confirmed the background suppression method based on global-local registration strategy has a better perform in moving target detection on moving platform.

  17. Optofluidic laser for dual-mode sensitive biomolecular detection with a large dynamic range

    NASA Astrophysics Data System (ADS)

    Wu, Xiang; Oo, Maung Kyaw Khaing; Reddy, Karthik; Chen, Qiushu; Sun, Yuze; Fan, Xudong

    2014-04-01

    Enzyme-linked immunosorbent assay (ELISA) is a powerful method for biomolecular analysis. The traditional ELISA employing light intensity as the sensing signal often encounters large background arising from non-specific bindings, material autofluorescence and leakage of excitation light, which deteriorates its detection limit and dynamic range. Here we develop the optofluidic laser-based ELISA, where ELISA occurs inside a laser cavity. The laser onset time is used as the sensing signal, which is inversely proportional to the enzyme concentration and hence the analyte concentration inside the cavity. We first elucidate the principle of the optofluidic laser-based ELISA, and then characterize the optofluidic laser performance. Finally, we present the dual-mode detection of interleukin-6 using commercial ELISA kits, where the sensing signals are simultaneously obtained by the traditional and the optofluidic laser-based ELISA, showing a detection limit of 1 fg ml-1 (38 aM) and a dynamic range of 6 orders of magnitude.

  18. Canine detection of free-ranging brown treesnakes on Guam

    USGS Publications Warehouse

    Savidge, J.A.; Stanford, J.W.; Reed, R.N.; Haddock, G.R.; Adams, A.A.Y.

    2011-01-01

    We investigated canine teams (dogs and their handlers) on Guam as a potential tool for finding invasive brown treesnakes (Boiga irregularis) in the wild. Canine teams searched a 40 ?? 40 m forested area for a snake that had consumed a dead mouse containing a radio-transmitter. To avoid tainting the target or target area with human scent, no snake was handled or closely approached prior to searches. Trials were conducted during the morning when these nocturnal snakes were usually hidden in refugia. A radiotracker knew the snake's location, but dog handlers and search navigators did not. Of 85 trials conducted over four months, the two canine teams had an average success rate of 35% of correctly defining an area ??? 5 ?? 5 m that contained the transmittered snake; the team with more experience prior to the trials had a success rate of 44% compared with 26% for the less experienced team. Canine teams also found 11 shed skins from wild snakes. Although dogs alerted outside the vicinity of transmittered snakes, only one wild, non-transmittered snake was found during the trials, possibly reflecting the difficulty humans have in locating non-transmittered brown treesnakes in refugia. We evaluated success at finding snakes as a function of canine team, number of prior trials (i.e. experience gained during the trials), recent canine success at finding a target snake, various environmental conditions, snake perch height, and snake characteristics (snout-vent length and sex). Success rate increased over the course of the trials. Canine team success also increased with increasing average humidity and decreased with increasing average wind speed. Our results suggest dogs could be useful at detecting brown treesnakes in refugia, particularly when compared to daytime visual searches by humans, but techniques are needed to help humans find and extract snakes once a dog has alerted. ?? New Zealand Ecological Society.

  19. Study on multispectral imaging detection and recognition

    NASA Astrophysics Data System (ADS)

    Jun, Wang; Na, Ding; Gao, Jiaobo; Yu, Hu; Jun, Wu; Li, Junna; Zheng, Yawei; Fei, Gao; Sun, Kefeng

    2009-07-01

    Multispectral imaging detecting technology use target radiation character in spectral spatial distribution and relation between spectral and image to detect target and remote sensing measure. Its speciality is multi channel, narrow bandwidth, large amount of information, high accuracy. The ability of detecting target in environment of clutter, camouflage, concealment and beguilement is improved. At present, spectral imaging technology in the range of multispectral and hyperspectral develop greatly. The multispectral imaging equipment of unmanned aerial vehicle can be used in mine detection, information, surveillance and reconnaissance. Spectral imaging spectrometer operating in MWIR and LWIR has already been applied in the field of remote sensing and military in the advanced country. The paper presents the technology of multispectral imaging. It can enhance the reflectance, scatter and radiation character of the artificial targets among nature background. The targets among complex background and camouflage/stealth targets can be effectively identified. The experiment results and the data of spectral imaging is obtained.

  20. Detection of ferromagnetic target based on mobile magnetic gradient tensor system

    NASA Astrophysics Data System (ADS)

    Gang, Y. I. N.; Yingtang, Zhang; Zhining, Li; Hongbo, Fan; Guoquan, Ren

    2016-03-01

    Attitude change of mobile magnetic gradient tensor system critically affects the precision of gradient measurements, thereby increasing ambiguity in target detection. This paper presents a rotational invariant-based method for locating and identifying ferromagnetic targets. Firstly, unit magnetic moment vector was derived based on the geometrical invariant, such that the intermediate eigenvector of the magnetic gradient tensor is perpendicular to the magnetic moment vector and the source-sensor displacement vector. Secondly, unit source-sensor displacement vector was derived based on the characteristic that the angle between magnetic moment vector and source-sensor displacement is a rotational invariant. By introducing a displacement vector between two measurement points, the magnetic moment vector and the source-sensor displacement vector were theoretically derived. To resolve the problem of measurement noises existing in the realistic detection applications, linear equations were formulated using invariants corresponding to several distinct measurement points and least square solution of magnetic moment vector and source-sensor displacement vector were obtained. Results of simulation and principal verification experiment showed the correctness of the analytical method, along with the practicability of the least square method.

  1. Ultra-high dynamic range electro-optic sampling for detecting millimeter and sub-millimeter radiation

    PubMed Central

    Ibrahim, Akram; Férachou, Denis; Sharma, Gargi; Singh, Kanwarpal; Kirouac-Turmel, Marie; Ozaki, Tsuneyuki

    2016-01-01

    Time-domain spectroscopy using coherent millimeter and sub-millimeter radiation (also known as terahertz radiation) is rapidly expanding its application, owing greatly to the remarkable advances in generating and detecting such radiation. However, many current techniques for coherent terahertz detection have limited dynamic range, thus making it difficult to perform some basic experiments that need to directly compare strong and weak terahertz signals. Here, we propose and demonstrate a novel technique based on cross-polarized spectral-domain interferometry to achieve ultra-high dynamic range electro-optic sampling measurement of coherent millimeter and sub-millimeter radiation. In our scheme, we exploit the birefringence in a single-mode polarization maintaining fiber in order to measure the phase change induced by the electric field of terahertz radiation in the detection crystal. With our new technique, we have achieved a dynamic range of 7 × 106, which is 4 orders of magnitude higher than conventional electro-optic sampling techniques, while maintaining comparable signal-to-noise ratio. The present technique is foreseen to have great impact on experiments such as linear terahertz spectroscopy of optically thick materials (such as aqueous samples) and nonlinear terahertz spectroscopy, where the higher dynamic range is crucial for proper interpretation of experimentally obtained results. PMID:26976363

  2. Ultra-high dynamic range electro-optic sampling for detecting millimeter and sub-millimeter radiation.

    PubMed

    Ibrahim, Akram; Férachou, Denis; Sharma, Gargi; Singh, Kanwarpal; Kirouac-Turmel, Marie; Ozaki, Tsuneyuki

    2016-03-15

    Time-domain spectroscopy using coherent millimeter and sub-millimeter radiation (also known as terahertz radiation) is rapidly expanding its application, owing greatly to the remarkable advances in generating and detecting such radiation. However, many current techniques for coherent terahertz detection have limited dynamic range, thus making it difficult to perform some basic experiments that need to directly compare strong and weak terahertz signals. Here, we propose and demonstrate a novel technique based on cross-polarized spectral-domain interferometry to achieve ultra-high dynamic range electro-optic sampling measurement of coherent millimeter and sub-millimeter radiation. In our scheme, we exploit the birefringence in a single-mode polarization maintaining fiber in order to measure the phase change induced by the electric field of terahertz radiation in the detection crystal. With our new technique, we have achieved a dynamic range of 7 × 10(6), which is 4 orders of magnitude higher than conventional electro-optic sampling techniques, while maintaining comparable signal-to-noise ratio. The present technique is foreseen to have great impact on experiments such as linear terahertz spectroscopy of optically thick materials (such as aqueous samples) and nonlinear terahertz spectroscopy, where the higher dynamic range is crucial for proper interpretation of experimentally obtained results.

  3. Truncated feature representation for automatic target detection using transformed data-based decomposition

    NASA Astrophysics Data System (ADS)

    Riasati, Vahid R.

    2016-05-01

    In this work, the data covariance matrix is diagonalized to provide an orthogonal bases set using the eigen vectors of the data. The eigen-vector decomposition of the data is transformed and filtered in the transform domain to truncate the data for robust features related to a specified set of targets. These truncated eigen features are then combined and reconstructed to utilize in a composite filter and consequently utilized for the automatic target detection of the same class of targets. The results associated with the testing of the current technique are evaluated using the peak-correlation and peak-correlation energy metrics and are presented in this work. The inverse transformed eigen-bases of the current technique may be thought of as an injected sparsity to minimize data in representing the skeletal data structure information associated with the set of targets under consideration.

  4. Target-specific NMR detection of protein-ligand interactions with antibody-relayed 15N-group selective STD.

    PubMed

    Hetényi, Anasztázia; Hegedűs, Zsófia; Fajka-Boja, Roberta; Monostori, Éva; Kövér, Katalin E; Martinek, Tamás A

    2016-12-01

    Fragment-based drug design has been successfully applied to challenging targets where the detection of the weak protein-ligand interactions is a key element. 1 H saturation transfer difference (STD) NMR spectroscopy is a powerful technique for this work but it requires pure homogeneous proteins as targets. Monoclonal antibody (mAb)-relayed 15 N-GS STD spectroscopy has been developed to resolve the problem of protein mixtures and impure proteins. A 15 N-labelled target-specific mAb is selectively irradiated and the saturation is relayed through the target to the ligand. Tests on the anti-Gal-1 mAb/Gal-1/lactose system showed that the approach is experimentally feasible in a reasonable time frame. This method allows detection and identification of binding molecules directly from a protein mixture in a multicomponent system.

  5. A targeted change-detection procedure by combining change vector analysis and post-classification approach

    NASA Astrophysics Data System (ADS)

    Ye, Su; Chen, Dongmei; Yu, Jie

    2016-04-01

    In remote sensing, conventional supervised change-detection methods usually require effective training data for multiple change types. This paper introduces a more flexible and efficient procedure that seeks to identify only the changes that users are interested in, here after referred to as "targeted change detection". Based on a one-class classifier "Support Vector Domain Description (SVDD)", a novel algorithm named "Three-layer SVDD Fusion (TLSF)" is developed specially for targeted change detection. The proposed algorithm combines one-class classification generated from change vector maps, as well as before- and after-change images in order to get a more reliable detecting result. In addition, this paper introduces a detailed workflow for implementing this algorithm. This workflow has been applied to two case studies with different practical monitoring objectives: urban expansion and forest fire assessment. The experiment results of these two case studies show that the overall accuracy of our proposed algorithm is superior (Kappa statistics are 86.3% and 87.8% for Case 1 and 2, respectively), compared to applying SVDD to change vector analysis and post-classification comparison.

  6. Quality control for normal liquid-based cytology: Rescreening, high-risk HPV targeted reviewing and/or high-risk HPV detection?

    PubMed Central

    Depuydt, Christophe E; Arbyn, Marc; Benoy, Ina H; Vandepitte, Johan; Vereecken, Annie J; Bogers, Johannes J

    2009-01-01

    The objective of this prospective study was to compare the number of CIN2+cases detected in negative cytology by different quality control (QC) methods. Full rescreening, high-risk (HR) human papillomavirus (HPV)-targeted reviewing and HR HPV detection were compared. Randomly selected negative cytology detected by BD FocalPoint™ (NFR), by guided screening of the prescreened which needed further review (GS) and by manual screening (MS) was used. A 3-year follow-up period was available. Full rescreening of cytology only detected 23.5% of CIN2+ cases, whereas the cytological rescreening of oncogenic positive slides (high-risk HPV-targeted reviewing) detected 7 of 17 CIN2+ cases (41.2%). Quantitative real-time PCR for 15 oncogenic HPV types detected all CIN2+ cases. Relative sensitivity to detect histological CIN2+ was 0.24 for full rescreening, 0.41 for HR-targeted reviewing and 1.00 for HR HPV detection. In more than half of the reviewed negative cytological preparations associated with histological CIN2+cases no morphologically abnormal cells were detected despite a positive HPV test. The visual cut-off for the detection of abnormal cytology was established at 6.5 HR HPV copies/cell. High-risk HPV detection has a higher yield for detection of CIN2+ cases as compared to manual screening followed by 5% full review, or compared to targeted reviewing of smears positive for oncogenic HPV types, and show diagnostic properties that support its use as a QC procedure in cytologic laboratories. PMID:18544049

  7. A Targeted Swallow Screen for the Detection of Postoperative Dysphagia.

    PubMed

    Gee, Erica; Lancaster, Elizabeth; Meltzer, Jospeh; Mendelsohn, Abie H; Benharash, Peyman

    2015-10-01

    Postoperative dysphagia leads to aspiration pneumonia, prolonged hospital stay, and is associated with increased mortality. A simple and sensitive screening test to identify patients requiring objective dysphagia evaluation is presently lacking. In this study, we evaluated the efficacy of a novel targeted swallow screen evaluation. This was a prospective trial involving all adult patients who underwent elective cardiac surgery with cardiopulmonary bypass at our institution over an 8-week period. Within 24 hours of extubation and before the initiation of oral intake, all postsurgical patients were evaluated using the targeted swallow screen. A fiberoptic endoscopic evaluation of swallowing was requested for failed screenings. During the study, 50 postcardiac surgery patients were screened. Fifteen (30%) failed the targeted swallow screen, and ten of the fifteen (66%) failed the subsequent fiberoptic endoscopic evaluation of swallowing exam and were confirmed to have dysphagia. The screening test had 100 per cent sensitivity for detecting dysphagia in our patient population, and a specificity of 87.5 per cent. The overall incidence of dysphagia was 20 per cent. We have shown that a targeted swallow evaluation can efficiently screen patients during the postcardiac surgery period. Furthermore, we have shown that the true incidence of dysphagia after cardiac surgery is significantly higher than previously recognized in literature.

  8. STARR: shortwave-targeted agile Raman robot for the detection and identification of emplaced explosives

    NASA Astrophysics Data System (ADS)

    Gomer, Nathaniel R.; Gardner, Charles W.

    2014-05-01

    In order to combat the threat of emplaced explosives (land mines, etc.), ChemImage Sensor Systems (CISS) has developed a multi-sensor, robot mounted sensor capable of identification and confirmation of potential threats. The system, known as STARR (Shortwave-infrared Targeted Agile Raman Robot), utilizes shortwave infrared spectroscopy for the identification of potential threats, combined with a visible short-range standoff Raman hyperspectral imaging (HSI) system for material confirmation. The entire system is mounted onto a Talon UGV (Unmanned Ground Vehicle), giving the sensor an increased area search rate and reducing the risk of injury to the operator. The Raman HSI system utilizes a fiber array spectral translator (FAST) for the acquisition of high quality Raman chemical images, allowing for increased sensitivity and improved specificity. An overview of the design and operation of the system will be presented, along with initial detection results of the fusion sensor.

  9. Target detection in GPR data using joint low-rank and sparsity constraints

    NASA Astrophysics Data System (ADS)

    Bouzerdoum, Abdesselam; Tivive, Fok Hing Chi; Abeynayake, Canicious

    2016-05-01

    In ground penetrating radars, background clutter, which comprises the signals backscattered from the rough, uneven ground surface and the background noise, impairs the visualization of buried objects and subsurface inspections. In this paper, a clutter mitigation method is proposed for target detection. The removal of background clutter is formulated as a constrained optimization problem to obtain a low-rank matrix and a sparse matrix. The low-rank matrix captures the ground surface reflections and the background noise, whereas the sparse matrix contains the target reflections. An optimization method based on split-Bregman algorithm is developed to estimate these two matrices from the input GPR data. Evaluated on real radar data, the proposed method achieves promising results in removing the background clutter and enhancing the target signature.

  10. Improving Target Detection in Visual Search Through the Augmenting Multi-Sensory Cues

    DTIC Science & Technology

    2013-01-01

    target detection, visual search James Merlo, Joseph E. Mercado , Jan B.F. Van Erp, Peter A. Hancock University of Central Florida 12201 Research Parkway...were controlled by a purpose-created, LabView- based software computer program that synchronised the respective displays and recorded response times and

  11. Rapid detection of proteins in transgenic crops without protein reference standards by targeted proteomic mass spectrometry.

    PubMed

    Schacherer, Lindsey J; Xie, Weiping; Owens, Michaela A; Alarcon, Clara; Hu, Tiger X

    2016-09-01

    Liquid chromatography coupled with tandem mass spectrometry is increasingly used for protein detection for transgenic crops research. Currently this is achieved with protein reference standards which may take a significant time or efforts to obtain and there is a need for rapid protein detection without protein reference standards. A sensitive and specific method was developed to detect target proteins in transgenic maize leaf crude extract at concentrations as low as ∼30 ng mg(-1) dry leaf without the need of reference standards or any sample enrichment. A hybrid Q-TRAP mass spectrometer was used to monitor all potential tryptic peptides of the target proteins in both transgenic and non-transgenic samples. The multiple reaction monitoring-initiated detection and sequencing (MIDAS) approach was used for initial peptide/protein identification via Mascot database search. Further confirmation was achieved by direct comparison between transgenic and non-transgenic samples. Definitive confirmation was provided by running the same experiments of synthetic peptides or protein standards, if available. A targeted proteomic mass spectrometry method using MIDAS approach is an ideal methodology for detection of new proteins in early stages of transgenic crop research and development when neither protein reference standards nor antibodies are available. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  12. A mathematical analysis of the Janus combat simulation weather effects models and sensitivity analysis of sky-to-ground brightness ratio on target detection

    NASA Astrophysics Data System (ADS)

    Shorts, Vincient F.

    1994-09-01

    The Janus combat simulation offers the user a wide variety of weather effects options to employ during the execution of any simulation run, which can directly influence detection of opposing forces. Realistic weather effects are required if the simulation is to accurately reproduce 'real world' results. This thesis examines the mathematics of the Janus weather effects models. A weather effect option in Janus is the sky-to-ground brightness ratio (SGR). SGR affects an optical sensor's ability to detect targets. It is a measure of the sun angle in relation to the horizon. A review of the derivation of SGR is performed and an analysis of SGR's affect on the number of optical detections and detection ranges is performed using an unmanned aerial vehicle (UAV) search scenario. For comparison, the UAV's are equipped with a combination of optical and thermal sensors.

  13. Identification of new antibacterial targets in RNA polymerase of Mycobacterium tuberculosis by detecting positive selection sites.

    PubMed

    Wang, QingBiao; Xu, Yiqin; Gu, Zhuoya; Liu, Nian; Jin, Ke; Li, Yao; Crabbe, M James C; Zhong, Yang

    2018-04-01

    Bacterial RNA polymerase (RNAP) is an effective target for antibacterial treatment. In order to search new potential targets in RNAP of Mycobacterium, we detected adaptive selections of RNAP related genes in 13 strains of Mycobacterium by phylogenetic analysis. We first collected sequences of 17 genes including rpoA, rpoB, rpoC, rpoZ, and sigma factor A-M. Then maximum likelihood trees were constructed, followed by positive selection detection. We found that sigG shows positive selection along the clade (M. tuberculosis, M. bovis), suggesting its important evolutionary role and its potential to be a new antibacterial target. Moreover, the regions near 933Cys and 935His on the rpoB subunit of M. tuberculosis showed significant positive selection, which could also be a new attractive target for anti-tuberculosis drugs. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Single molecule molecular inversion probes for targeted, high-accuracy detection of low-frequency variation.

    PubMed

    Hiatt, Joseph B; Pritchard, Colin C; Salipante, Stephen J; O'Roak, Brian J; Shendure, Jay

    2013-05-01

    The detection and quantification of genetic heterogeneity in populations of cells is fundamentally important to diverse fields, ranging from microbial evolution to human cancer genetics. However, despite the cost and throughput advances associated with massively parallel sequencing, it remains challenging to reliably detect mutations that are present at a low relative abundance in a given DNA sample. Here we describe smMIP, an assay that combines single molecule tagging with multiplex targeted capture to enable practical and highly sensitive detection of low-frequency or subclonal variation. To demonstrate the potential of the method, we simultaneously resequenced 33 clinically informative cancer genes in eight cell line and 45 clinical cancer samples. Single molecule tagging facilitated extremely accurate consensus calling, with an estimated per-base error rate of 8.4 × 10(-6) in cell lines and 2.6 × 10(-5) in clinical specimens. False-positive mutations in the single molecule consensus base-calls exhibited patterns predominantly consistent with DNA damage, including 8-oxo-guanine and spontaneous deamination of cytosine. Based on mixing experiments with cell line samples, sensitivity for mutations above 1% frequency was 83% with no false positives. At clinically informative sites, we identified seven low-frequency point mutations (0.2%-4.7%), including BRAF p.V600E (melanoma, 0.2% alternate allele frequency), KRAS p.G12V (lung, 0.6%), JAK2 p.V617F (melanoma, colon, two lung, 0.3%-1.4%), and NRAS p.Q61R (colon, 4.7%). We anticipate that smMIP will be broadly adoptable as a practical and effective method for accurately detecting low-frequency mutations in both research and clinical settings.

  15. Cognitive Slowing and Learning of Target Detection Skills in Pre-Demented Subjects

    ERIC Educational Resources Information Center

    Amieva, Helene; Rouch-Leroyer, Isabelle; Letenneur, Luc; Dartigues, Jean Francois; Fabrigoule, Collette

    2004-01-01

    Alzheimer's disease produces a generalized slowing of cognitive processing increasing with the progression of dementia. However little is known about this phenomenon in the pre-demented stages. Our purpose was to investigate cognitive slowing in pre-demented subjects and their ability to develop target detection skills while performing a…

  16. Performance Evaluation of Target Detection with a Near-Space Vehicle-Borne Radar in Blackout Condition.

    PubMed

    Li, Yanpeng; Li, Xiang; Wang, Hongqiang; Deng, Bin; Qin, Yuliang

    2016-01-06

    Radar is a very important sensor in surveillance applications. Near-space vehicle-borne radar (NSVBR) is a novel installation of a radar system, which offers many benefits, like being highly suited to the remote sensing of extremely large areas, having a rapidly deployable capability and having low vulnerability to electronic countermeasures. Unfortunately, a target detection challenge arises because of complicated scenarios, such as nuclear blackout, rain attenuation, etc. In these cases, extra care is needed to evaluate the detection performance in blackout situations, since this a classical problem along with the application of an NSVBR. However, the existing evaluation measures are the probability of detection and the receiver operating curve (ROC), which cannot offer detailed information in such a complicated application. This work focuses on such requirements. We first investigate the effect of blackout on an electromagnetic wave. Performance evaluation indexes are then built: three evaluation indexes on the detection capability and two evaluation indexes on the robustness of the detection process. Simulation results show that the proposed measure will offer information on the detailed performance of detection. These measures are therefore very useful in detecting the target of interest in a remote sensing system and are helpful for both the NSVBR designers and users.

  17. Performance Evaluation of Target Detection with a Near-Space Vehicle-Borne Radar in Blackout Condition

    PubMed Central

    Li, Yanpeng; Li, Xiang; Wang, Hongqiang; Deng, Bin; Qin, Yuliang

    2016-01-01

    Radar is a very important sensor in surveillance applications. Near-space vehicle-borne radar (NSVBR) is a novel installation of a radar system, which offers many benefits, like being highly suited to the remote sensing of extremely large areas, having a rapidly deployable capability and having low vulnerability to electronic countermeasures. Unfortunately, a target detection challenge arises because of complicated scenarios, such as nuclear blackout, rain attenuation, etc. In these cases, extra care is needed to evaluate the detection performance in blackout situations, since this a classical problem along with the application of an NSVBR. However, the existing evaluation measures are the probability of detection and the receiver operating curve (ROC), which cannot offer detailed information in such a complicated application. This work focuses on such requirements. We first investigate the effect of blackout on an electromagnetic wave. Performance evaluation indexes are then built: three evaluation indexes on the detection capability and two evaluation indexes on the robustness of the detection process. Simulation results show that the proposed measure will offer information on the detailed performance of detection. These measures are therefore very useful in detecting the target of interest in a remote sensing system and are helpful for both the NSVBR designers and users. PMID:26751445

  18. Novel label-free and high-throughput microchip electrophoresis platform for multiplex antibiotic residues detection based on aptamer probes and target catalyzed hairpin assembly for signal amplification.

    PubMed

    Wang, Ye; Gan, Ning; Zhou, You; Li, Tianhua; Hu, Futao; Cao, Yuting; Chen, Yinji

    2017-11-15

    Novel label-free and multiplex aptasensors have been developed for simultaneous detection of several antibiotics based on a microchip electrophoresis (MCE) platform and target catalyzed hairpin assembly (CHA) for signal amplification. Kanamycin (Kana) and oxytetracycline (OTC) were employed as models for testing the system. These aptasensors contained six DNA strands termed as Kana aptamer-catalysis strand (Kana apt-C), Kana inhibit strand (Kana inh), OTC aptamer-catalysis strand (OTC apt-C), OTC inhibit strand (OTC inh), hairpin structures H1 and H2 which were partially complementary. Upon the addition of Kana or OTC, the binding event of aptamer and target triggered the self-assembly between H1 and H2, resulting in the formation of many H1-H2 complexes. They could show strong signals which represented the concentration of Kana or OTC respectively in the MCE system. With the help of the well-designed and high-quality CHA amplification, the assay could yield 300-fold amplified signal comparing that from non-amplified system. Under optimal conditions, this assay exhibited a linear correlation in the ranges from 0.001ngmL -1 to 10ngmL -1 , with the detection limits of 0.7pgmL -1 and 0.9pgmL -1 (S/N=3) toward Kana and OTC, respectively. The platform has the following advantages: firstly, the aptamer probes can be fabricated easily without labeling signal tags for MCE detection; Secondly, the targets can just react with probes and produce the amplified signal in one-pot. Finally, the targets can be simultaneously detected within 10min in different channels, thus high-throughput measurement can be achieved. Based on this work, it is estimated that this detection platform will be universally served as a simple, sensitive and portable platform for antibiotic contaminants detection in biological and environmental samples. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Combined effects of expectations and visual uncertainty upon detection and identification of a target in the fog.

    PubMed

    Quétard, Boris; Quinton, Jean-Charles; Colomb, Michèle; Pezzulo, Giovanni; Barca, Laura; Izaute, Marie; Appadoo, Owen Kevin; Mermillod, Martial

    2015-09-01

    Detecting a pedestrian while driving in the fog is one situation where the prior expectation about the target presence is integrated with the noisy visual input. We focus on how these sources of information influence the oculomotor behavior and are integrated within an underlying decision-making process. The participants had to judge whether high-/low-density fog scenes displayed on a computer screen contained a pedestrian or a deer by executing a mouse movement toward the response button (mouse-tracking). A variable road sign was added on the scene to manipulate expectations about target identity. We then analyzed the timing and amplitude of the deviation of mouse trajectories toward the incorrect response and, using an eye tracker, the detection time (before fixating the target) and the identification time (fixations on the target). Results revealed that expectation of the correct target results in earlier decisions with less deviation toward the alternative response, this effect being partially explained by the facilitation of target identification.

  20. Target-catalyzed hairpin assembly and metal-organic frameworks mediated nonenzymatic co-reaction for multiple signal amplification detection of miR-122 in human serum.

    PubMed

    Li, Yuliang; Yu, Chao; Yang, Bo; Liu, Zhirui; Xia, Peiyuan; Wang, Qian

    2018-04-15

    Herein, a new type of multifunctional iron based metal-organic frameworks (PdNPs@Fe-MOFs) has been synthesized by assembly palladium nanoparticles on the surface of Fe-MIL-88NH 2 MOFs microcrystals, and first applied in electrochemical biosensor for ultrasensitive detection of microRNA-122 (miR-122, a biomarker of drug-induced liver injury). The nanohybrids have not only been utilized as ideal nanocarriers for immobilization of signal probes, but also used as redox probes and electrocatalysts. In this biosensor, two hairpin probes were designed as capture probes and signal probes, respectively. The nanohybrids conjugated with streptavidin and biotinylated signal probes were used as the tracer labels, target miR-122 was sandwiched between the tracer labels and thiol-terminated capture probes inserted in MCH monolayer on the gold nanoparticles-functionalized nitrogen-doped graphene sheets (AuNPs@N-G) modified electrode. Based on target-catalyzed hairpin assembly, target miR-122 could trigger the hybridization of capture probes and signal probes to further be released to initiate the next reaction process resulted in numerous tracer indicators anchored onto the sensing interfaces. Thus, the detection signal could be dramatically enhanced towards the electrocatalytic oxidation of 3,3',5,5'-tetramethylbenzidine in the presence of H 2 O 2 owing to the intrinsic and intriguing peroxidase-like activity of the nanohybrids. With the assist of target-catalyzed hairpin assembly and PdNPs@Fe-MOFs mimetic co-reaction for signal amplification, a wide detection range from 0.01fM to 10pM was achieved with a low detection limit of 0.003fM (S/N =3). Furthermore, the proposed biosensor exhibited excellent specificity and recovery in spiked serum samples, and was successfully used for detecting miR-122 in real biological samples, which provided a rapid and efficient method for detecting drug-induced liver injury at an early stage. Copyright © 2017. Published by Elsevier B.V.