Nonstationary EO/IR Clutter Suppression and Dim Object Tracking

NASA Astrophysics Data System (ADS)

Tartakovsky, A.; Brown, A.; Brown, J.

2010-09-01

We develop and evaluate the performance of advanced algorithms which provide significantly improved capabilities for automated detection and tracking of ballistic and flying dim objects in the presence of highly structured intense clutter. Applications include ballistic missile early warning, midcourse tracking, trajectory prediction, and resident space object detection and tracking. The set of algorithms include, in particular, adaptive spatiotemporal clutter estimation-suppression and nonlinear filtering-based multiple-object track-before-detect. These algorithms are suitable for integration into geostationary, highly elliptical, or low earth orbit scanning or staring sensor suites, and are based on data-driven processing that adapts to real-world clutter backgrounds, including celestial, earth limb, or terrestrial clutter. In many scenarios of interest, e.g., for highly elliptic and, especially, low earth orbits, the resulting clutter is highly nonstationary, providing a significant challenge for clutter suppression to or below sensor noise levels, which is essential for dim object detection and tracking. We demonstrate the success of the developed algorithms using semi-synthetic and real data. In particular, our algorithms are shown to be capable of detecting and tracking point objects with signal-to-clutter levels down to 1/1000 and signal-to-noise levels down to 1/4.

Ship Detection in SAR Image Based on the Alpha-stable Distribution

PubMed Central

Wang, Changcheng; Liao, Mingsheng; Li, Xiaofeng

2008-01-01

This paper describes an improved Constant False Alarm Rate (CFAR) ship detection algorithm in spaceborne synthetic aperture radar (SAR) image based on Alpha-stable distribution model. Typically, the CFAR algorithm uses the Gaussian distribution model to describe statistical characteristics of a SAR image background clutter. However, the Gaussian distribution is only valid for multilook SAR images when several radar looks are averaged. As sea clutter in SAR images shows spiky or heavy-tailed characteristics, the Gaussian distribution often fails to describe background sea clutter. In this study, we replace the Gaussian distribution with the Alpha-stable distribution, which is widely used in impulsive or spiky signal processing, to describe the background sea clutter in SAR images. In our proposed algorithm, an initial step for detecting possible ship targets is employed. Then, similar to the typical two-parameter CFAR algorithm, a local process is applied to the pixel identified as possible target. A RADARSAT-1 image is used to validate this Alpha-stable distribution based algorithm. Meanwhile, known ship location data during the time of RADARSAT-1 SAR image acquisition is used to validate ship detection results. Validation results show improvements of the new CFAR algorithm based on the Alpha-stable distribution over the CFAR algorithm based on the Gaussian distribution. PMID:27873794

Modern Approaches to the Computation of the Probability of Target Detection in Cluttered Environments

NASA Astrophysics Data System (ADS)

Meitzler, Thomas J.

The field of computer vision interacts with fields such as psychology, vision research, machine vision, psychophysics, mathematics, physics, and computer science. The focus of this thesis is new algorithms and methods for the computation of the probability of detection (Pd) of a target in a cluttered scene. The scene can be either a natural visual scene such as one sees with the naked eye (visual), or, a scene displayed on a monitor with the help of infrared sensors. The relative clutter and the temperature difference between the target and background (DeltaT) are defined and then used to calculate a relative signal -to-clutter ratio (SCR) from which the Pd is calculated for a target in a cluttered scene. It is shown how this definition can include many previous definitions of clutter and (DeltaT). Next, fuzzy and neural -fuzzy techniques are used to calculate the Pd and it is shown how these methods can give results that have a good correlation with experiment. The experimental design for actually measuring the Pd of a target by observers is described. Finally, wavelets are applied to the calculation of clutter and it is shown how this new definition of clutter based on wavelets can be used to compute the Pd of a target.

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.

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.

Multispectral image fusion for detecting land mines

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

Clark, G.A.; Sengupta, S.K.; Aimonetti, W.D.

1995-04-01

This report details a system which fuses information contained in registered images from multiple sensors to reduce the effects of clutter and improve the ability to detect surface and buried land mines. The sensor suite currently consists of a camera that acquires images in six bands (400nm, 500nm, 600nm, 700nm, 800nm and 900nm). Past research has shown that it is extremely difficult to distinguish land mines from background clutter in images obtained from a single sensor. It is hypothesized, however, that information fused from a suite of various sensors is likely to provide better detection reliability, because the suite ofmore » sensors detects a variety of physical properties that are more separable in feature space. The materials surrounding the mines can include natural materials (soil, rocks, foliage, water, etc.) and some artifacts.« less

Adaptive clutter rejection filters for airborne Doppler weather radar applied to the detection of low altitude windshear

NASA Technical Reports Server (NTRS)

Keel, Byron M.

1989-01-01

An optimum adaptive clutter rejection filter for use with airborne Doppler weather radar is presented. The radar system is being designed to operate at low-altitudes for the detection of windshear in an airport terminal area where ground clutter returns may mask the weather return. The coefficients of the adaptive clutter rejection filter are obtained using a complex form of a square root normalized recursive least squares lattice estimation algorithm which models the clutter return data as an autoregressive process. The normalized lattice structure implementation of the adaptive modeling process for determining the filter coefficients assures that the resulting coefficients will yield a stable filter and offers possible fixed point implementation. A 10th order FIR clutter rejection filter indexed by geographical location is designed through autoregressive modeling of simulated clutter data. Filtered data, containing simulated dry microburst and clutter return, are analyzed using pulse-pair estimation techniques. To measure the ability of the clutter rejection filters to remove the clutter, results are compared to pulse-pair estimates of windspeed within a simulated dry microburst without clutter. In the filter evaluation process, post-filtered pulse-pair width estimates and power levels are also used to measure the effectiveness of the filters. The results support the use of an adaptive clutter rejection filter for reducing the clutter induced bias in pulse-pair estimates of windspeed.

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.

Synthetic aperture radar imagery of airports and surrounding areas: Study of clutter at grazing angles and their polarimetric properties

NASA Technical Reports Server (NTRS)

Onstott, Robert G.; Gineris, Denise J.; Clinthorne, James T.

1991-01-01

The statistical description of ground clutter at an airport and in the surrounding area is addressed. These data are being utilized in a program to detect microbursts. Synthetic aperture radar data were collected at the Denver Stapleton Airport. Mountain terrain data were examined to determine if they may potentially contribute to range ambiguity problems and degrade microburst detection. Results suggest that mountain clutter may not present a special problem source. The examination of clutter at small grazing angles was continued by examining data collected at especially low altitudes. Cultural objects such as buildings produce strong sources of backscatter at angles of about 85 deg, with responses of 30 dB to 60 dB above the background. Otherwise there are a few sources which produce significant scatter. The polarization properties of hydrospheres and clutter were examined with the intent of determining the optimum polarization. This polarization was determined to be dependent upon the ratio of VV and HH polarizations of both rain and ground clutter.

Comparing masked target transform volume (MTTV) clutter metric to human observer evaluation of visual clutter

NASA Astrophysics Data System (ADS)

Camp, H. A.; Moyer, Steven; Moore, Richard K.

2010-04-01

The Night Vision and Electronic Sensors Directorate's current time-limited search (TLS) model, which makes use of the targeting task performance (TTP) metric to describe image quality, does not explicitly account for the effects of visual clutter on observer performance. The TLS model is currently based on empirical fits to describe human performance for a time of day, spectrum and environment. Incorporating a clutter metric into the TLS model may reduce the number of these empirical fits needed. The masked target transform volume (MTTV) clutter metric has been previously presented and compared to other clutter metrics. Using real infrared imagery of rural images with varying levels of clutter, NVESD is currently evaluating the appropriateness of the MTTV metric. NVESD had twenty subject matter experts (SME) rank the amount of clutter in each scene in a series of pair-wise comparisons. MTTV metric values were calculated and then compared to the SME observers rankings. The MTTV metric ranked the clutter in a similar manner to the SME evaluation, suggesting that the MTTV metric may emulate SME response. This paper is a first step in quantifying clutter and measuring the agreement to subjective human evaluation.

Background Characterization Techniques For Pattern Recognition Applications

NASA Astrophysics Data System (ADS)

Noah, Meg A.; Noah, Paul V.; Schroeder, John W.; Kessler, Bernard V.; Chernick, Julian A.

1989-08-01

The Department of Defense has a requirement to investigate technologies for the detection of air and ground vehicles in a clutter environment. The use of autonomous systems using infrared, visible, and millimeter wave detectors has the potential to meet DOD's needs. In general, however, the hard-ware technology (large detector arrays with high sensitivity) has outpaced the development of processing techniques and software. In a complex background scene the "problem" is as much one of clutter rejection as it is target detection. The work described in this paper has investigated a new, and innovative, methodology for background clutter characterization, target detection and target identification. The approach uses multivariate statistical analysis to evaluate a set of image metrics applied to infrared cloud imagery and terrain clutter scenes. The techniques are applied to two distinct problems: the characterization of atmospheric water vapor cloud scenes for the Navy's Infrared Search and Track (IRST) applications to support the Infrared Modeling Measurement and Analysis Program (IRAMMP); and the detection of ground vehicles for the Army's Autonomous Homing Munitions (AHM) problems. This work was sponsored under two separate Small Business Innovative Research (SBIR) programs by the Naval Surface Warfare Center (NSWC), White Oak MD, and the Army Material Systems Analysis Activity at Aberdeen Proving Ground MD. The software described in this paper will be available from the respective contract technical representatives.

Examining the robustness of automated aural classification of active sonar echoes.

PubMed

Murphy, Stefan M; Hines, Paul C

2014-02-01

Active sonar systems are used to detect underwater man-made objects of interest (targets) that are too quiet to be reliably detected with passive sonar. Performance of active sonar can be degraded by false alarms caused by echoes returned from geological seabed structures (clutter) in shallow regions. To reduce false alarms, a method of distinguishing target echoes from clutter echoes is required. Research has demonstrated that perceptual-based signal features similar to those employed in the human auditory system can be used to automatically discriminate between target and clutter echoes, thereby reducing the number of false alarms and improving sonar performance. An active sonar experiment on the Malta Plateau in the Mediterranean Sea was conducted during the Clutter07 sea trial and repeated during the Clutter09 sea trial. The dataset consists of more than 95,000 pulse-compressed echoes returned from two targets and many geological clutter objects. These echoes were processed using an automatic classifier that quantifies the timbre of each echo using a number of perceptual signal features. Using echoes from 2007, the aural classifier was trained to establish a boundary between targets and clutter in the feature space. Temporal robustness was then investigated by testing the classifier on echoes from the 2009 experiment.

Hyperspectral target detection analysis of a cluttered scene from a virtual airborne sensor platform using MuSES

NASA Astrophysics Data System (ADS)

Packard, Corey D.; Viola, Timothy S.; Klein, Mark D.

2017-10-01

The ability to predict spectral electro-optical (EO) signatures for various targets against realistic, cluttered backgrounds is paramount for rigorous signature evaluation. Knowledge of background and target signatures, including plumes, is essential for a variety of scientific and defense-related applications including contrast analysis, camouflage development, automatic target recognition (ATR) algorithm development and scene material classification. The capability to simulate any desired mission scenario with forecast or historical weather is a tremendous asset for defense agencies, serving as a complement to (or substitute for) target and background signature measurement campaigns. In this paper, a systematic process for the physical temperature and visible-through-infrared radiance prediction of several diverse targets in a cluttered natural environment scene is presented. The ability of a virtual airborne sensor platform to detect and differentiate targets from a cluttered background, from a variety of sensor perspectives and across numerous wavelengths in differing atmospheric conditions, is considered. The process described utilizes the thermal and radiance simulation software MuSES and provides a repeatable, accurate approach for analyzing wavelength-dependent background and target (including plume) signatures in multiple band-integrated wavebands (multispectral) or hyperspectrally. The engineering workflow required to combine 3D geometric descriptions, thermal material properties, natural weather boundary conditions, all modes of heat transfer and spectral surface properties is summarized. This procedure includes geometric scene creation, material and optical property attribution, and transient physical temperature prediction. Radiance renderings, based on ray-tracing and the Sandford-Robertson BRDF model, are coupled with MODTRAN for the inclusion of atmospheric effects. This virtual hyperspectral/multispectral radiance prediction methodology has been extensively validated and provides a flexible process for signature evaluation and algorithm development.

An Efficient Adaptive Angle-Doppler Compensation Approach for Non-Sidelooking Airborne Radar STAP

PubMed Central

Shen, Mingwei; Yu, Jia; Wu, Di; Zhu, Daiyin

2015-01-01

In this study, the effects of non-sidelooking airborne radar clutter dispersion on space-time adaptive processing (STAP) is considered, and an efficient adaptive angle-Doppler compensation (EAADC) approach is proposed to improve the clutter suppression performance. In order to reduce the computational complexity, the reduced-dimension sparse reconstruction (RDSR) technique is introduced into the angle-Doppler spectrum estimation to extract the required parameters for compensating the clutter spectral center misalignment. Simulation results to demonstrate the effectiveness of the proposed algorithm are presented. PMID:26053755

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.

The Calculation of Fractal Dimension in the Presence of Non-Fractal Clutter

NASA Technical Reports Server (NTRS)

Herren, Kenneth A.; Gregory, Don A.

1999-01-01

The area of information processing has grown dramatically over the last 50 years. In the areas of image processing and information storage the technology requirements have far outpaced the ability of the community to meet demands. The need for faster recognition algorithms and more efficient storage of large quantities of data has forced the user to accept less than lossless retrieval of that data for analysis. In addition to clutter that is not the object of interest in the data set, often the throughput requirements forces the user to accept "noisy" data and to tolerate the clutter inherent in that data. It has been shown that some of this clutter, both the intentional clutter (clouds, trees, etc) as well as the noise introduced on the data by processing requirements can be modeled as fractal or fractal-like. Traditional methods using Fourier deconvolution on these sources of noise in frequency space leads to loss of signal and can, in many cases, completely eliminate the target of interest. The parameters that characterize fractal-like noise (predominately the fractal dimension) have been investigated and a technique to reduce or eliminate noise from real scenes has been developed. Examples of clutter reduced images are presented.

Modified-hybrid optical neural network filter for multiple object recognition within cluttered scenes

NASA Astrophysics Data System (ADS)

Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.

2009-08-01

Motivated by the non-linear interpolation and generalization abilities of the hybrid optical neural network filter between the reference and non-reference images of the true-class object we designed the modifiedhybrid optical neural network filter. We applied an optical mask to the hybrid optical neural network's filter input. The mask was built with the constant weight connections of a randomly chosen image included in the training set. The resulted design of the modified-hybrid optical neural network filter is optimized for performing best in cluttered scenes of the true-class object. Due to the shift invariance properties inherited by its correlator unit the filter can accommodate multiple objects of the same class to be detected within an input cluttered image. Additionally, the architecture of the neural network unit of the general hybrid optical neural network filter allows the recognition of multiple objects of different classes within the input cluttered image by modifying the output layer of the unit. We test the modified-hybrid optical neural network filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. The filter is shown to exhibit with a single pass over the input data simultaneously out-of-plane rotation, shift invariance and good clutter tolerance. It is able to successfully detect and classify correctly the true-class objects within background clutter for which there has been no previous training.

Neyman Pearson detection of K-distributed random variables

NASA Astrophysics Data System (ADS)

Tucker, J. Derek; Azimi-Sadjadi, Mahmood R.

2010-04-01

In this paper a new detection method for sonar imagery is developed in K-distributed background clutter. The equation for the log-likelihood is derived and compared to the corresponding counterparts derived for the Gaussian and Rayleigh assumptions. Test results of the proposed method on a data set of synthetic underwater sonar images is also presented. This database contains images with targets of different shapes inserted into backgrounds generated using a correlated K-distributed model. Results illustrating the effectiveness of the K-distributed detector are presented in terms of probability of detection, false alarm, and correct classification rates for various bottom clutter scenarios.

Unified sensor management in unknown dynamic clutter

NASA Astrophysics Data System (ADS)

Mahler, Ronald; El-Fallah, Adel

2010-04-01

In recent years the first author has developed a unified, computationally tractable approach to multisensor-multitarget sensor management. This approach consists of closed-loop recursion of a PHD or CPHD filter with maximization of a "natural" sensor management objective function called PENT (posterior expected number of targets). In this paper we extend this approach so that it can be used in unknown, dynamic clutter backgrounds.

Clutter characterization within segmented hyperspectral imagery

NASA Astrophysics Data System (ADS)

Kacenjar, Steve T.; Hoffberg, Michael; North, Patrick

2007-10-01

Use of a Mean Class Propagation Model (MCPM) has been shown to be an effective approach in the expedient propagation of hyperspectral data scenes through the atmosphere. In this approach, real scene data are spatially subdivided into regions of common spectral properties. Each sub-region which we call a class possesses two important attributes (1) the mean spectral radiance and (2) the spectral covariance. The use of this attributes can significantly improve throughput performance of computing systems over conventional pixel-based methods. However, this approach assumes that background clutter can be approximated as having multivariate Gaussian distributions. Under such conditions, covariance propagations can be effectively performed from ground through the atmosphere. This paper explores this basic assumption using real-scene Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data and examines how the partitioning of the scene into smaller and smaller segments influences local clutter characterization. It also presents a clutter characterization metric that helps explain the migration of the magnitude of statistical clutter from parent class to child sub-classes populations. It is shown that such a metric can be directly related to an approximate invariant between the parent class and its child classes.

Clutter attenuation using the Doppler effect in standoff electromagnetic quantum sensing

NASA Astrophysics Data System (ADS)

Lanzagorta, Marco; Jitrik, Oliverio; Uhlmann, Jeffrey; Venegas, Salvador

2016-05-01

In the context of traditional radar systems, the Doppler effect is crucial to detect and track moving targets in the presence of clutter. In the quantum radar context, however, most theoretical performance analyses to date have assumed static targets. In this paper we consider the Doppler effect at the single photon level. In particular, we describe how the Doppler effect produced by clutter and moving targets modifies the quantum distinguishability and the quantum radar error detection probability equations. Furthermore, we show that Doppler-based delayline cancelers can reduce the effects of clutter in the context of quantum radar, but only in the low-brightness regime. Thus, quantum radar may prove to be an important technology if the electronic battlefield requires stealthy tracking and detection of moving targets in the presence of clutter.

Sparse Representation for Infrared Dim Target Detection via a Discriminative Over-Complete Dictionary Learned Online

PubMed Central

Li, Zheng-Zhou; Chen, Jing; Hou, Qian; Fu, Hong-Xia; Dai, Zhen; Jin, Gang; Li, Ru-Zhang; Liu, Chang-Ju

2014-01-01

It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse representation on a discriminative over-complete dictionary. An adaptive morphological over-complete dictionary is trained and constructed online according to the content of infrared image by K-singular value decomposition (K-SVD) algorithm. Then the adaptive morphological over-complete dictionary is divided automatically into a target over-complete dictionary describing target signals, and a background over-complete dictionary embedding background by the criteria that the atoms in the target over-complete dictionary could be decomposed more sparsely based on a Gaussian over-complete dictionary than the one in the background over-complete dictionary. This discriminative over-complete dictionary can not only capture significant features of background clutter and dim targets better than a structural over-complete dictionary, but also strengthens the sparse feature difference between background and target more efficiently than a discriminative over-complete dictionary learned offline and classified manually. The target and background clutter can be sparsely decomposed over their corresponding over-complete dictionaries, yet couldn't be sparsely decomposed based on their opposite over-complete dictionary, so their residuals after reconstruction by the prescribed number of target and background atoms differ very visibly. Some experiments are included and the results show that this proposed approach could not only improve the sparsity more efficiently, but also enhance the performance of small target detection more effectively. PMID:24871988

Sparse representation for infrared Dim target detection via a discriminative over-complete dictionary learned online.

PubMed

Li, Zheng-Zhou; Chen, Jing; Hou, Qian; Fu, Hong-Xia; Dai, Zhen; Jin, Gang; Li, Ru-Zhang; Liu, Chang-Ju

2014-05-27

It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse representation on a discriminative over-complete dictionary. An adaptive morphological over-complete dictionary is trained and constructed online according to the content of infrared image by K-singular value decomposition (K-SVD) algorithm. Then the adaptive morphological over-complete dictionary is divided automatically into a target over-complete dictionary describing target signals, and a background over-complete dictionary embedding background by the criteria that the atoms in the target over-complete dictionary could be decomposed more sparsely based on a Gaussian over-complete dictionary than the one in the background over-complete dictionary. This discriminative over-complete dictionary can not only capture significant features of background clutter and dim targets better than a structural over-complete dictionary, but also strengthens the sparse feature difference between background and target more efficiently than a discriminative over-complete dictionary learned offline and classified manually. The target and background clutter can be sparsely decomposed over their corresponding over-complete dictionaries, yet couldn't be sparsely decomposed based on their opposite over-complete dictionary, so their residuals after reconstruction by the prescribed number of target and background atoms differ very visibly. Some experiments are included and the results show that this proposed approach could not only improve the sparsity more efficiently, but also enhance the performance of small target detection more effectively.

Subspace Compressive GLRT Detector for MIMO Radar in the Presence of Clutter.

PubMed

Bolisetti, Siva Karteek; Patwary, Mohammad; Ahmed, Khawza; Soliman, Abdel-Hamid; Abdel-Maguid, Mohamed

2015-01-01

The problem of optimising the target detection performance of MIMO radar in the presence of clutter is considered. The increased false alarm rate which is a consequence of the presence of clutter returns is known to seriously degrade the target detection performance of the radar target detector, especially under low SNR conditions. In this paper, a mathematical model is proposed to optimise the target detection performance of a MIMO radar detector in the presence of clutter. The number of samples that are required to be processed by a radar target detector regulates the amount of processing burden while achieving a given detection reliability. While Subspace Compressive GLRT (SSC-GLRT) detector is known to give optimised radar target detection performance with reduced computational complexity, it however suffers a significant deterioration in target detection performance in the presence of clutter. In this paper we provide evidence that the proposed mathematical model for SSC-GLRT detector outperforms the existing detectors in the presence of clutter. The performance analysis of the existing detectors and the proposed SSC-GLRT detector for MIMO radar in the presence of clutter are provided in this paper.

Evaluating a de-cluttering technique for NextGen RNAV and RNP charts

DOT National Transportation Integrated Search

2012-10-14

The authors propose a de-cluttering technique to simplify the depiction of visually complex Area Navigation (RNAV) and Required Navigation Performance (RNP) procedures by reducing the number of paths shown on a single chart page. An experiment was co...

Facial expression, size, and clutter: Inferences from movie structure to emotion judgments and back.

PubMed

Cutting, James E; Armstrong, Kacie L

2016-04-01

The perception of facial expressions and objects at a distance are entrenched psychological research venues, but their intersection is not. We were motivated to study them together because of their joint importance in the physical composition of popular movies-shots that show a larger image of a face typically have shorter durations than those in which the face is smaller. For static images, we explore the time it takes viewers to categorize the valence of different facial expressions as a function of their visual size. In two studies, we find that smaller faces take longer to categorize than those that are larger, and this pattern interacts with local background clutter. More clutter creates crowding and impedes the interpretation of expressions for more distant faces but not proximal ones. Filmmakers at least tacitly know this. In two other studies, we show that contemporary movies lengthen shots that show smaller faces, and even more so with increased clutter.

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.

Automatic Censoring CFAR Detector Based on Ordered Data Difference for Low-Flying Helicopter Safety

PubMed Central

Jiang, Wen; Huang, Yulin; Yang, Jianyu

2016-01-01

Being equipped with a millimeter-wave radar allows a low-flying helicopter to sense the surroundings in real time, which significantly increases its safety. However, nonhomogeneous clutter environments, such as a multiple target situation and a clutter edge environment, can dramatically affect the radar signal detection performance. In order to improve the radar signal detection performance in nonhomogeneous clutter environments, this paper proposes a new automatic censored cell averaging CFAR detector. The proposed CFAR detector does not require any prior information about the background environment and uses the hypothesis test of the first-order difference (FOD) result of ordered data to reject the unwanted samples in the reference window. After censoring the unwanted ranked cells, the remaining samples are combined to form an estimate of the background power level, thus getting better radar signal detection performance. The simulation results show that the FOD-CFAR detector provides low loss CFAR performance in a homogeneous environment and also performs robustly in nonhomogeneous environments. Furthermore, the measured results of a low-flying helicopter validate the basic performance of the proposed method. PMID:27399714

The neurological underpinnings of cluttering: Some initial findings.

PubMed

Ward, David; Connally, Emily L; Pliatsikas, Christos; Bretherton-Furness, Jess; Watkins, Kate E

2015-03-01

Cluttering is a fluency disorder characterised by overly rapid or jerky speech patterns that compromise intelligibility. The neural correlates of cluttering are unknown but theoretical accounts implicate the basal ganglia and medial prefrontal cortex. Dysfunction in these brain areas would be consistent with difficulties in selection and control of speech motor programs that are characteristic of speech disfluencies in cluttering. There is a surprising lack of investigation into this disorder using modern imaging techniques. Here, we used functional MRI to investigate the neural correlates of cluttering. We scanned 17 adults who clutter and 17 normally fluent control speakers matched for age and sex. Brain activity was recorded using sparse-sampling functional MRI while participants viewed scenes and either (i) produced overt speech describing the scene or (ii) read out loud a sentence provided that described the scene. Speech was recorded and analysed off line. Differences in brain activity for each condition compared to a silent resting baseline and between conditions were analysed for each group separately (cluster-forming threshold Z>3.1, extent p<0.05, corrected) and then these differences were further compared between the two groups (voxel threshold p<0.01, extent>30 voxels, uncorrected). In both conditions, the patterns of activation in adults who clutter and control speakers were strikingly similar, particularly at the cortical level. Direct group comparisons revealed greater activity in adults who clutter compared to control speakers in the lateral premotor cortex bilaterally and, as predicted, on the medial surface (pre-supplementary motor area). Subcortically, adults who clutter showed greater activity than control speakers in the basal ganglia. Specifically, the caudate nucleus and putamen were overactive in adults who clutter for the comparison of picture description with sentence reading. In addition, adults who clutter had reduced activity relative to control speakers in the lateral anterior cerebellum bilaterally. Eleven of the 17 adults who clutter also stuttered. This comorbid diagnosis of stuttering was found to contribute to the abnormal overactivity seen in the group of adults who clutter in the right ventral premotor cortex and right anterior cingulate cortex. In the remaining areas of abnormal activity seen in adults who clutter compared to controls, the subgroup who clutter and stutter did not differ from the subgroup who clutter but do not stutter. Our findings were in good agreement with theoretical predictions regarding the neural correlates of cluttering. We found evidence for abnormal function in the basal ganglia and their cortical output target, the medial prefrontal cortex. The findings are discussed in relation to models of cluttering that point to problems with motor control of speech. This paper reports findings on the neural correlates seen in adults who clutter, and offers hypotheses as to how these might map onto the behaviours seen amongst those who clutter. Readers will be able to (a) identify the structures that are implicated in the disorder of cluttering, (b) understand arguments relating these structures to the behavioural expression of the disorder, (c) understand some of the complexities in interpreting data pertaining to recovery from cluttering, (d) understand where future efforts in research into the neurological correlates of cluttering should be focussed. Copyright © 2015. Published by Elsevier Inc.

The Complexity of Background Clutter Affects Nectar Bat Use of Flower Odor and Shape Cues.

PubMed

Muchhala, Nathan; Serrano, Diana

2015-01-01

Given their small size and high metabolism, nectar bats need to be able to quickly locate flowers during foraging bouts. Chiropterophilous plants depend on these bats for their reproduction, thus they also benefit if their flowers can be easily located, and we would expect that floral traits such as odor and shape have evolved to maximize detection by bats. However, relatively little is known about the importance of different floral cues during foraging bouts. In the present study, we undertook a set of flight cage experiments with two species of nectar bats (Anoura caudifer and A. geoffroyi) and artificial flowers to compare the importance of shape and scent cues in locating flowers. In a training phase, a bat was presented an artificial flower with a given shape and scent, whose position was constantly shifted to prevent reliance on spatial memory. In the experimental phase, two flowers were presented, one with the training-flower scent and one with the training-flower shape. For each experimental repetition, we recorded which flower was located first, and then shifted flower positions. Additionally, experiments were repeated in a simple environment, without background clutter, or a complex environment, with a background of leaves and branches. Results demonstrate that bats visit either flower indiscriminately with simple backgrounds, with no significant difference in terms of whether they visit the training-flower odor or training-flower shape first. However, in a complex background olfaction was the most important cue; scented flowers were consistently located first. This suggests that for well-exposed flowers, without obstruction from clutter, vision and/or echolocation are sufficient in locating them. In more complex backgrounds, nectar bats depend more heavily on olfaction during foraging bouts.

The Complexity of Background Clutter Affects Nectar Bat Use of Flower Odor and Shape Cues

PubMed Central

Muchhala, Nathan; Serrano, Diana

2015-01-01

Given their small size and high metabolism, nectar bats need to be able to quickly locate flowers during foraging bouts. Chiropterophilous plants depend on these bats for their reproduction, thus they also benefit if their flowers can be easily located, and we would expect that floral traits such as odor and shape have evolved to maximize detection by bats. However, relatively little is known about the importance of different floral cues during foraging bouts. In the present study, we undertook a set of flight cage experiments with two species of nectar bats (Anoura caudifer and A. geoffroyi) and artificial flowers to compare the importance of shape and scent cues in locating flowers. In a training phase, a bat was presented an artificial flower with a given shape and scent, whose position was constantly shifted to prevent reliance on spatial memory. In the experimental phase, two flowers were presented, one with the training-flower scent and one with the training-flower shape. For each experimental repetition, we recorded which flower was located first, and then shifted flower positions. Additionally, experiments were repeated in a simple environment, without background clutter, or a complex environment, with a background of leaves and branches. Results demonstrate that bats visit either flower indiscriminately with simple backgrounds, with no significant difference in terms of whether they visit the training-flower odor or training-flower shape first. However, in a complex background olfaction was the most important cue; scented flowers were consistently located first. This suggests that for well-exposed flowers, without obstruction from clutter, vision and/or echolocation are sufficient in locating them. In more complex backgrounds, nectar bats depend more heavily on olfaction during foraging bouts. PMID:26445216

Signs of depth-luminance covariance in 3-D cluttered scenes.

PubMed

Scaccia, Milena; Langer, Michael S

2018-03-01

In three-dimensional (3-D) cluttered scenes such as foliage, deeper surfaces often are more shadowed and hence darker, and so depth and luminance often have negative covariance. We examined whether the sign of depth-luminance covariance plays a role in depth perception in 3-D clutter. We compared scenes rendered with negative and positive depth-luminance covariance where positive covariance means that deeper surfaces are brighter and negative covariance means deeper surfaces are darker. For each scene, the sign of the depth-luminance covariance was given by occlusion cues. We tested whether subjects could use this sign information to judge the depth order of two target surfaces embedded in 3-D clutter. The clutter consisted of distractor surfaces that were randomly distributed in a 3-D volume. We tested three independent variables: the sign of the depth-luminance covariance, the colors of the targets and distractors, and the background luminance. An analysis of variance showed two main effects: Subjects performed better when the deeper surfaces were darker and when the color of the target surfaces was the same as the color of the distractors. There was also a strong interaction: Subjects performed better under a negative depth-luminance covariance condition when targets and distractors had different colors than when they had the same color. Our results are consistent with a "dark means deep" rule, but the use of this rule depends on the similarity between the color of the targets and color of the 3-D clutter.

Infrared maritime target detection using a probabilistic single Gaussian model of sea clutter in Fourier domain

NASA Astrophysics Data System (ADS)

Zhou, Anran; Xie, Weixin; Pei, Jihong; Chen, Yapei

2018-02-01

For ship targets detection in cluttered infrared image sequences, a robust detection method, based on the probabilistic single Gaussian model of sea background in Fourier domain, is put forward. The amplitude spectrum sequences at each frequency point of the pure seawater images in Fourier domain, being more stable than the gray value sequences of each background pixel in the spatial domain, are regarded as a Gaussian model. Next, a probability weighted matrix is built based on the stability of the pure seawater's total energy spectrum in the row direction, to make the Gaussian model more accurate. Then, the foreground frequency points are separated from the background frequency points by the model. Finally, the false-alarm points are removed utilizing ships' shape features. The performance of the proposed method is tested by visual and quantitative comparisons with others.

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.

Methods And System Suppressing Clutter In A Gain-Block, Radar-Responsive Tag System

DOEpatents

Ormesher, Richard C.; Axline, Robert M.

2006-04-18

Methods and systems reduce clutter interference in a radar-responsive tag system. A radar transmits a series of linear-frequency-modulated pulses and receives echo pulses from nearby terrain and from radar-responsive tags that may be in the imaged scene. Tags in the vicinity of the radar are activated by the radar's pulses. The tags receive and remodulate the radar pulses. Tag processing reverses the direction, in time, of the received waveform's linear frequency modulation. The tag retransmits the remodulated pulses. The radar uses a reversed-chirp de-ramp pulse to process the tag's echo. The invention applies to radar systems compatible with coherent gain-block tags. The invention provides a marked reduction in the strength of residual clutter echoes on each and every echo pulse received by the radar. SAR receiver processing effectively whitens passive-clutter signatures across the range dimension. Clutter suppression of approximately 14 dB is achievable for a typical radar system.

Experimental Evaluation of Camouflage Effectiveness in the Thermal Infrared (Experimentele Evaluatie van de Effectiviteit van Camouflage in het Thermische Infrarood)

DTIC Science & Technology

1993-03-01

shape distortion. For recognitio , , however, camouflage rnr’f.ure" have to adjiist the tLugek signoawuie in more detail to the background clutter...ous trees, 4m height at ±100m range 4 ag.. _!tural field (seasonal plant growing) 5 ba~e soil (ploughed rough surface) 1) concrete -, face 7 Water...surlace (small pond, Im depth) 8 Up- and down hill slopes (bare seil and grass covered). North and South facing At regular intervals, the physical

Influence of temperature fluctuations on infrared limb radiance: a new simulation code

NASA Astrophysics Data System (ADS)

Rialland, Valérie; Chervet, Patrick

2006-08-01

Airborne infrared limb-viewing detectors may be used as surveillance sensors in order to detect dim military targets. These systems' performances are limited by the inhomogeneous background in the sensor field of view which impacts strongly on target detection probability. This background clutter, which results from small-scale fluctuations of temperature, density or pressure must therefore be analyzed and modeled. Few existing codes are able to model atmospheric structures and their impact on limb-observed radiance. SAMM-2 (SHARC-4 and MODTRAN4 Merged), the Air Force Research Laboratory (AFRL) background radiance code can be used to in order to predict the radiance fluctuation as a result of a normalized temperature fluctuation, as a function of the line-of-sight. Various realizations of cluttered backgrounds can then be computed, based on these transfer functions and on a stochastic temperature field. The existing SIG (SHARC Image Generator) code was designed to compute the cluttered background which would be observed from a space-based sensor. Unfortunately, this code was not able to compute accurate scenes as seen by an airborne sensor especially for lines-of-sight close to the horizon. Recently, we developed a new code called BRUTE3D and adapted to our configuration. This approach is based on a method originally developed in the SIG model. This BRUTE3D code makes use of a three-dimensional grid of temperature fluctuations and of the SAMM-2 transfer functions to synthesize an image of radiance fluctuations according to sensor characteristics. This paper details the working principles of the code and presents some output results. The effects of the small-scale temperature fluctuations on infrared limb radiance as seen by an airborne sensor are highlighted.

Effet de l'encombrement visuel de l'ecran primaire de vol sur la performance du pilote, la charge de travail et le parcours visuel

NASA Astrophysics Data System (ADS)

Doyon-Poulin, Philippe

Flight deck of 21st century commercial aircrafts does not look like the one the Wright brothers used for their first flight. The rapid growth of civilian aviation resulted in an increase in the number of flight deck instruments and of their complexity, in order to complete a safe and ontime flight. However, presenting an abundance of visual information using visually cluttered flight instruments might reduce the pilot's flight performance. Visual clutter has received an increased interest by the aerospace community to understand the effects of visual density and information overload on pilots' performance. Aerospace regulations demand to minimize visual clutter of flight deck displays. Past studies found a mixed effect of visual clutter of the primary flight display on pilots' technical flight performance. More research is needed to better understand this subject. In this thesis, we did an experimental study in a flight simulator to test the effects of visual clutter of the primary flight display on the pilot's technical flight performance, mental workload and gaze pattern. First, we identified a gap in existing definitions of visual clutter and we proposed a new definition relevant to the aerospace community that takes into account the context of use of the display. Then, we showed that past research on the effects of visual clutter of the primary flight display on pilots' performance did not manipulate the variable of visual clutter in a similar manner. Past research changed visual clutter at the same time than the flight guidance function. Using a different flight guidance function between displays might have masked the effect of visual clutter on pilots' performance. To solve this issue, we proposed three requirements that all tested displays must satisfy to assure that only the variable of visual clutter is changed during study while leaving other variables unaffected. Then, we designed three primary flight displays with a different visual clutter level (low, medium, high) but with the same flight guidance function, by respecting the previous requirements. Twelve pilots, with a mean experience of over 4000 total flight hours, completed an instrument landing in a flight simulator using all three displays for a total of nine repetitions. Our results showed that pilots reported lower workload level and had better lateral precision during the approach using the medium-clutter display compared to the low- and high-clutter displays. Also, pilots reported that the medium-clutter display was the most useful for the flight task compared to the two other displays. Eye tracker results showed that pilots' gaze pattern was less efficient for the high-clutter display compared to the low- and medium-clutter displays. Overall, these new experimental results emphasize the importance of optimizing visual clutter of flight displays as it affects both objective and subjective performance of experienced pilots in their flying task. This thesis ends with practical recommendations to help designers optimize visual clutter of displays used for man-machine interface.

Low-Cost 3-D Flow Estimation of Blood With Clutter.

PubMed

Wei, Siyuan; Yang, Ming; Zhou, Jian; Sampson, Richard; Kripfgans, Oliver D; Fowlkes, J Brian; Wenisch, Thomas F; Chakrabarti, Chaitali

2017-05-01

Volumetric flow rate estimation is an important ultrasound medical imaging modality that is used for diagnosing cardiovascular diseases. Flow rates are obtained by integrating velocity estimates over a cross-sectional plane. Speckle tracking is a promising approach that overcomes the angle dependency of traditional Doppler methods, but suffers from poor lateral resolution. Recent work improves lateral velocity estimation accuracy by reconstructing a synthetic lateral phase (SLP) signal. However, the estimation accuracy of such approaches is compromised by the presence of clutter. Eigen-based clutter filtering has been shown to be effective in removing the clutter signal; but it is computationally expensive, precluding its use at high volume rates. In this paper, we propose low-complexity schemes for both velocity estimation and clutter filtering. We use a two-tiered motion estimation scheme to combine the low complexity sum-of-absolute-difference and SLP methods to achieve subpixel lateral accuracy. We reduce the complexity of eigen-based clutter filtering by processing in subgroups and replacing singular value decomposition with less compute-intensive power iteration and subspace iteration methods. Finally, to improve flow rate estimation accuracy, we use kernel power weighting when integrating the velocity estimates. We evaluate our method for fast- and slow-moving clutter for beam-to-flow angles of 90° and 60° using Field II simulations, demonstrating high estimation accuracy across scenarios. For instance, for a beam-to-flow angle of 90° and fast-moving clutter, our estimation method provides a bias of -8.8% and standard deviation of 3.1% relative to the actual flow rate.

Background suppression of infrared small target image based on inter-frame registration

NASA Astrophysics Data System (ADS)

Ye, Xiubo; Xue, Bindang

2018-04-01

We propose a multi-frame background suppression method for remote infrared small target detection. Inter-frame information is necessary when the heavy background clutters make it difficult to distinguish real targets and false alarms. A registration procedure based on points matching in image patches is used to compensate the local deformation of background. Then the target can be separated by background subtraction. Experiments show our method serves as an effective preliminary of target detection.

VNIR hyperspectral background characterization methods in adverse weather conditions

NASA Astrophysics Data System (ADS)

Romano, João M.; Rosario, Dalton; Roth, Luz

2009-05-01

Hyperspectral technology is currently being used by the military to detect regions of interest where potential targets may be located. Weather variability, however, may affect the ability for an algorithm to discriminate possible targets from background clutter. Nonetheless, different background characterization approaches may facilitate the ability for an algorithm to discriminate potential targets over a variety of weather conditions. In a previous paper, we introduced a new autonomous target size invariant background characterization process, the Autonomous Background Characterization (ABC) or also known as the Parallel Random Sampling (PRS) method, features a random sampling stage, a parallel process to mitigate the inclusion by chance of target samples into clutter background classes during random sampling; and a fusion of results at the end. In this paper, we will demonstrate how different background characterization approaches are able to improve performance of algorithms over a variety of challenging weather conditions. By using the Mahalanobis distance as the standard algorithm for this study, we compare the performance of different characterization methods such as: the global information, 2 stage global information, and our proposed method, ABC, using data that was collected under a variety of adverse weather conditions. For this study, we used ARDEC's Hyperspectral VNIR Adverse Weather data collection comprised of heavy, light, and transitional fog, light and heavy rain, and low light conditions.

Automated vehicle detection in forward-looking infrared imagery.

PubMed

Der, Sandor; Chan, Alex; Nasrabadi, Nasser; Kwon, Heesung

2004-01-10

We describe an algorithm for the detection and clutter rejection of military vehicles in forward-looking infrared (FLIR) imagery. The detection algorithm is designed to be a prescreener that selects regions for further analysis and uses a spatial anomaly approach that looks for target-sized regions of the image that differ in texture, brightness, edge strength, or other spatial characteristics. The features are linearly combined to form a confidence image that is thresholded to find likely target locations. The clutter rejection portion uses target-specific information extracted from training samples to reduce the false alarms of the detector. The outputs of the clutter rejecter and detector are combined by a higher-level evidence integrator to improve performance over simple concatenation of the detector and clutter rejecter. The algorithm has been applied to a large number of FLIR imagery sets, and some of these results are presented here.

Target-Oriented High-Resolution SAR Image Formation via Semantic Information Guided Regularizations

NASA Astrophysics Data System (ADS)

Hou, Biao; Wen, Zaidao; Jiao, Licheng; Wu, Qian

2018-04-01

Sparsity-regularized synthetic aperture radar (SAR) imaging framework has shown its remarkable performance to generate a feature enhanced high resolution image, in which a sparsity-inducing regularizer is involved by exploiting the sparsity priors of some visual features in the underlying image. However, since the simple prior of low level features are insufficient to describe different semantic contents in the image, this type of regularizer will be incapable of distinguishing between the target of interest and unconcerned background clutters. As a consequence, the features belonging to the target and clutters are simultaneously affected in the generated image without concerning their underlying semantic labels. To address this problem, we propose a novel semantic information guided framework for target oriented SAR image formation, which aims at enhancing the interested target scatters while suppressing the background clutters. Firstly, we develop a new semantics-specific regularizer for image formation by exploiting the statistical properties of different semantic categories in a target scene SAR image. In order to infer the semantic label for each pixel in an unsupervised way, we moreover induce a novel high-level prior-driven regularizer and some semantic causal rules from the prior knowledge. Finally, our regularized framework for image formation is further derived as a simple iteratively reweighted $\\ell_1$ minimization problem which can be conveniently solved by many off-the-shelf solvers. Experimental results demonstrate the effectiveness and superiority of our framework for SAR image formation in terms of target enhancement and clutters suppression, compared with the state of the arts. Additionally, the proposed framework opens a new direction of devoting some machine learning strategies to image formation, which can benefit the subsequent decision making tasks.

Learning-Based Object Identification and Segmentation Using Dual-Energy CT Images for Security.

PubMed

Martin, Limor; Tuysuzoglu, Ahmet; Karl, W Clem; Ishwar, Prakash

2015-11-01

In recent years, baggage screening at airports has included the use of dual-energy X-ray computed tomography (DECT), an advanced technology for nondestructive evaluation. The main challenge remains to reliably find and identify threat objects in the bag from DECT data. This task is particularly hard due to the wide variety of objects, the high clutter, and the presence of metal, which causes streaks and shading in the scanner images. Image noise and artifacts are generally much more severe than in medical CT and can lead to splitting of objects and inaccurate object labeling. The conventional approach performs object segmentation and material identification in two decoupled processes. Dual-energy information is typically not used for the segmentation, and object localization is not explicitly used to stabilize the material parameter estimates. We propose a novel learning-based framework for joint segmentation and identification of objects directly from volumetric DECT images, which is robust to streaks, noise and variability due to clutter. We focus on segmenting and identifying a small set of objects of interest with characteristics that are learned from training images, and consider everything else as background. We include data weighting to mitigate metal artifacts and incorporate an object boundary field to reduce object splitting. The overall formulation is posed as a multilabel discrete optimization problem and solved using an efficient graph-cut algorithm. We test the method on real data and show its potential for producing accurate labels of the objects of interest without splits in the presence of metal and clutter.

Clutter Mitigation in Echocardiography Using Sparse Signal Separation

PubMed Central

Yavneh, Irad

2015-01-01

In ultrasound imaging, clutter artifacts degrade images and may cause inaccurate diagnosis. In this paper, we apply a method called Morphological Component Analysis (MCA) for sparse signal separation with the objective of reducing such clutter artifacts. The MCA approach assumes that the two signals in the additive mix have each a sparse representation under some dictionary of atoms (a matrix), and separation is achieved by finding these sparse representations. In our work, an adaptive approach is used for learning the dictionary from the echo data. MCA is compared to Singular Value Filtering (SVF), a Principal Component Analysis- (PCA-) based filtering technique, and to a high-pass Finite Impulse Response (FIR) filter. Each filter is applied to a simulated hypoechoic lesion sequence, as well as experimental cardiac ultrasound data. MCA is demonstrated in both cases to outperform the FIR filter and obtain results comparable to the SVF method in terms of contrast-to-noise ratio (CNR). Furthermore, MCA shows a lower impact on tissue sections while removing the clutter artifacts. In experimental heart data, MCA obtains in our experiments clutter mitigation with an average CNR improvement of 1.33 dB. PMID:26199622

A comparison of robust principal component analysis techniques for buried object detection in downward looking GPR sensor data

NASA Astrophysics Data System (ADS)

Pinar, Anthony; Havens, Timothy C.; Rice, Joseph; Masarik, Matthew; Burns, Joseph; Thelen, Brian

2016-05-01

Explosive hazards are a deadly threat in modern conflicts; hence, detecting them before they cause injury or death is of paramount importance. One method of buried explosive hazard discovery relies on data collected from ground penetrating radar (GPR) sensors. Threat detection with downward looking GPR is challenging due to large returns from non-target objects and clutter. This leads to a large number of false alarms (FAs), and since the responses of clutter and targets can form very similar signatures, classifier design is not trivial. One approach to combat these issues uses robust principal component analysis (RPCA) to enhance target signatures while suppressing clutter and background responses, though there are many versions of RPCA. This work applies some of these RPCA techniques to GPR sensor data and evaluates their merit using the peak signal-to-clutter ratio (SCR) of the RPCA-processed B-scans. Experimental results on government furnished data show that while some of the RPCA methods yield similar results, there are indeed some methods that outperform others. Furthermore, we show that the computation time required by the different RPCA methods varies widely, and the selection of tuning parameters in the RPCA algorithms has a major effect on the peak SCR.

SAR image classification based on CNN in real and simulation datasets

NASA Astrophysics Data System (ADS)

Peng, Lijiang; Liu, Ming; Liu, Xiaohua; Dong, Liquan; Hui, Mei; Zhao, Yuejin

2018-04-01

Convolution neural network (CNN) has made great success in image classification tasks. Even in the field of synthetic aperture radar automatic target recognition (SAR-ATR), state-of-art results has been obtained by learning deep representation of features on the MSTAR benchmark. However, the raw data of MSTAR have shortcomings in training a SAR-ATR model because of high similarity in background among the SAR images of each kind. This indicates that the CNN would learn the hierarchies of features of backgrounds as well as the targets. To validate the influence of the background, some other SAR images datasets have been made which contains the simulation SAR images of 10 manufactured targets such as tank and fighter aircraft, and the backgrounds of simulation SAR images are sampled from the whole original MSTAR data. The simulation datasets contain the dataset that the backgrounds of each kind images correspond to the one kind of backgrounds of MSTAR targets or clutters and the dataset that each image shares the random background of whole MSTAR targets or clutters. In addition, mixed datasets of MSTAR and simulation datasets had been made to use in the experiments. The CNN architecture proposed in this paper are trained on all datasets mentioned above. The experimental results shows that the architecture can get high performances on all datasets even the backgrounds of the images are miscellaneous, which indicates the architecture can learn a good representation of the targets even though the drastic changes on background.

Ship Detection from Ocean SAR Image Based on Local Contrast Variance Weighted Information Entropy

PubMed Central

Huang, Yulin; Pei, Jifang; Zhang, Qian; Gu, Qin; Yang, Jianyu

2018-01-01

Ship detection from synthetic aperture radar (SAR) images is one of the crucial issues in maritime surveillance. However, due to the varying ocean waves and the strong echo of the sea surface, it is very difficult to detect ships from heterogeneous and strong clutter backgrounds. In this paper, an innovative ship detection method is proposed to effectively distinguish the vessels from complex backgrounds from a SAR image. First, the input SAR image is pre-screened by the maximally-stable extremal region (MSER) method, which can obtain the ship candidate regions with low computational complexity. Then, the proposed local contrast variance weighted information entropy (LCVWIE) is adopted to evaluate the complexity of those candidate regions and the dissimilarity between the candidate regions with their neighborhoods. Finally, the LCVWIE values of the candidate regions are compared with an adaptive threshold to obtain the final detection result. Experimental results based on measured ocean SAR images have shown that the proposed method can obtain stable detection performance both in strong clutter and heterogeneous backgrounds. Meanwhile, it has a low computational complexity compared with some existing detection methods. PMID:29652863

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.

Global Infrasound Association Based on Probabilistic Clutter Categorization

NASA Astrophysics Data System (ADS)

Arora, Nimar; Mialle, Pierrick

2016-04-01

The IDC advances its methods and continuously improves its automatic system for the infrasound technology. The IDC focuses on enhancing the automatic system for the identification of valid signals and the optimization of the network detection threshold by identifying ways to refine signal characterization methodology and association criteria. An objective of this study is to reduce the number of associated infrasound arrivals that are rejected from the automatic bulletins when generating the reviewed event bulletins. Indeed, a considerable number of signal detections are due to local clutter sources such as microbaroms, waterfalls, dams, gas flares, surf (ocean breaking waves) etc. These sources are either too diffuse or too local to form events. Worse still, the repetitive nature of this clutter leads to a large number of false event hypotheses due to the random matching of clutter at multiple stations. Previous studies, for example [1], have worked on categorization of clutter using long term trends on detection azimuth, frequency, and amplitude at each station. In this work we continue the same line of reasoning to build a probabilistic model of clutter that is used as part of NETVISA [2], a Bayesian approach to network processing. The resulting model is a fusion of seismic, hydroacoustic and infrasound processing built on a unified probabilistic framework. References: [1] Infrasound categorization Towards a statistics based approach. J. Vergoz, P. Gaillard, A. Le Pichon, N. Brachet, and L. Ceranna. ITW 2011 [2] NETVISA: Network Processing Vertically Integrated Seismic Analysis. N. S. Arora, S. Russell, and E. Sudderth. BSSA 2013

Circular SAR GMTI

NASA Astrophysics Data System (ADS)

Page, Douglas; Owirka, Gregory; Nichols, Howard; Scarborough, Steven

2014-06-01

We describe techniques for improving ground moving target indication (GMTI) performance in multi-channel synthetic aperture radar (SAR) systems. Our approach employs a combination of moving reference processing (MRP) to compensate for defocus of moving target SAR responses and space-time adaptive processing (STAP) to mitigate the effects of strong clutter interference. Using simulated moving target and clutter returns, we demonstrate focusing of the target return using MRP, and discuss the effect of MRP on the clutter response. We also describe formation of adaptive degrees of freedom (DOFs) for STAP filtering of MRP processed data. For the simulated moving target in clutter example, we demonstrate improvement in the signal to interference plus noise (SINR) loss compared to more standard algorithm configurations. In addition to MRP and STAP, the use of tracker feedback, false alarm mitigation, and parameter estimation techniques are also described. A change detection approach for reducing false alarms from clutter discretes is outlined, and processing of a measured data coherent processing interval (CPI) from a continuously orbiting platform is described. The results demonstrate detection and geolocation of a high-value target under track. The endoclutter target is not clearly visible in single-channel SAR chips centered on the GMTI track prediction. Detections are compared to truth data before and after geolocation using measured angle of arrival (AOA).

Fukunaga-Koontz transform based dimensionality reduction for hyperspectral imagery

NASA Astrophysics Data System (ADS)

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

2006-05-01

Fukunaga-Koontz Transform based technique offers some attractive properties for desired class oriented dimensionality reduction in hyperspectral imagery. In FKT, feature selection is performed by transforming into a new space where feature classes have complimentary eigenvectors. Dimensionality reduction technique based on these complimentary eigenvector analysis can be described under two classes, desired class and background clutter, such that each basis function best represent one class while carrying the least amount of information from the second class. By selecting a few eigenvectors which are most relevant to desired class, one can reduce the dimension of hyperspectral cube. Since the FKT based technique reduces data size, it provides significant advantages for near real time detection applications in hyperspectral imagery. Furthermore, the eigenvector selection approach significantly reduces computation burden via the dimensionality reduction processes. The performance of the proposed dimensionality reduction algorithm has been tested using real-world hyperspectral dataset.

Public attitudes toward-and identification of-cluttering and stuttering in Norway and Puerto Rico.

PubMed

St Louis, Kenneth O; Sønsterud, Hilda; Carlo, Edna J; Heitmann, Ragnhild R; Kvenseth, Helene

2014-12-01

The study sought to compare public attitudes toward cluttering versus stuttering in Norway and Puerto Rico and to compare respondents' identification of persons known with these fluency disorders. After reading lay definitions of cluttering and stuttering, three samples of adults from Norway and three from Puerto Rico rated their attitudes toward cluttering and/or stuttering on modified versions of the POSHA-Cl (for cluttering) and POSHA-S (for stuttering). They also identified children and adults whom they knew who either or both manifested cluttering or stuttering. Attitudes toward cluttering were essentially unaffected by rating either cluttering only or combined cluttering and stuttering on the same questionnaire in both countries. The same was also true of stuttering. Attitudes were very similar toward both disorders although slightly less positive for cluttering. Norwegian attitudes toward both disorders were generally more positive than Puerto Rican attitudes. The average respondent identified slightly more than one fluency disorder, a higher percentage for stuttering than cluttering and higher for adults than children. Cluttering-stuttering was rarely identified. Given a lay definition, this study confirmed that adults from diverse cultures hold attitudes toward cluttering that are similar to-but somewhat less positive than-their attitudes toward stuttering. It also confirmed that adults can identify cluttering among people they know, although less commonly than stuttering. Design controls in this study assured that consideration of stuttering did not affect either the attitudes or identification results for cluttering. The reader will be able to: (a) describe the effects-or lack thereof-of considerations of stuttering on attitudes toward cluttering; (b) describe differences in public identification of children and adults who either clutter or stutter; (c) describe differences between attitudes toward cluttering and stuttering in Norway and Puerto Rico. Copyright © 2014 Elsevier Inc. All rights reserved.

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.

Improved Resolution and Reduced Clutter in Ultra-Wideband Microwave Imaging Using Cross-Correlated Back Projection: Experimental and Numerical Results

PubMed Central

Jacobsen, S.; Birkelund, Y.

2010-01-01

Microwave breast cancer detection is based on the dielectric contrast between healthy and malignant tissue. This radar-based imaging method involves illumination of the breast with an ultra-wideband pulse. Detection of tumors within the breast is achieved by some selected focusing technique. Image formation algorithms are tailored to enhance tumor responses and reduce early-time and late-time clutter associated with skin reflections and heterogeneity of breast tissue. In this contribution, we evaluate the performance of the so-called cross-correlated back projection imaging scheme by using a scanning system in phantom experiments. Supplementary numerical modeling based on commercial software is also presented. The phantom is synthetically scanned with a broadband elliptical antenna in a mono-static configuration. The respective signals are pre-processed by a data-adaptive RLS algorithm in order to remove artifacts caused by antenna reverberations and signal clutter. Successful detection of a 7 mm diameter cylindrical tumor immersed in a low permittivity medium was achieved in all cases. Selecting the widely used delay-and-sum (DAS) beamforming algorithm as a benchmark, we show that correlation based imaging methods improve the signal-to-clutter ratio by at least 10 dB and improves spatial resolution through a reduction of the imaged peak full-width half maximum (FWHM) of about 40–50%. PMID:21331362

Improved resolution and reduced clutter in ultra-wideband microwave imaging using cross-correlated back projection: experimental and numerical results.

PubMed

Jacobsen, S; Birkelund, Y

2010-01-01

Microwave breast cancer detection is based on the dielectric contrast between healthy and malignant tissue. This radar-based imaging method involves illumination of the breast with an ultra-wideband pulse. Detection of tumors within the breast is achieved by some selected focusing technique. Image formation algorithms are tailored to enhance tumor responses and reduce early-time and late-time clutter associated with skin reflections and heterogeneity of breast tissue. In this contribution, we evaluate the performance of the so-called cross-correlated back projection imaging scheme by using a scanning system in phantom experiments. Supplementary numerical modeling based on commercial software is also presented. The phantom is synthetically scanned with a broadband elliptical antenna in a mono-static configuration. The respective signals are pre-processed by a data-adaptive RLS algorithm in order to remove artifacts caused by antenna reverberations and signal clutter. Successful detection of a 7 mm diameter cylindrical tumor immersed in a low permittivity medium was achieved in all cases. Selecting the widely used delay-and-sum (DAS) beamforming algorithm as a benchmark, we show that correlation based imaging methods improve the signal-to-clutter ratio by at least 10 dB and improves spatial resolution through a reduction of the imaged peak full-width half maximum (FWHM) of about 40-50%.

Multiwaveband simulation-based signature analysis of camouflaged human dismounts in cluttered environments with TAIThermIR and MuSES

NASA Astrophysics Data System (ADS)

Packard, Corey D.; Klein, Mark D.; Viola, Timothy S.; Hepokoski, Mark A.

2016-10-01

The ability to predict electro-optical (EO) signatures of diverse targets against cluttered backgrounds is paramount for signature evaluation and/or management. Knowledge of target and background signatures is essential for a variety of defense-related applications. While there is no substitute for measured target and background signatures to determine contrast and detection probability, the capability to simulate any mission scenario with desired environmental conditions is a tremendous asset for defense agencies. In this paper, a systematic process for the thermal and visible-through-infrared simulation of camouflaged human dismounts in cluttered outdoor environments is presented. This process, utilizing the thermal and EO/IR radiance simulation tool TAIThermIR (and MuSES), provides a repeatable and accurate approach for analyzing contrast, signature and detectability of humans in multiple wavebands. The engineering workflow required to combine natural weather boundary conditions and the human thermoregulatory module developed by ThermoAnalytics is summarized. The procedure includes human geometry creation, human segmental physiology description and transient physical temperature prediction using environmental boundary conditions and active thermoregulation. Radiance renderings, which use Sandford-Robertson BRDF optical surface property descriptions and are coupled with MODTRAN for the calculation of atmospheric effects, are demonstrated. Sensor effects such as optical blurring and photon noise can be optionally included, increasing the accuracy of detection probability outputs that accompany each rendering. This virtual evaluation procedure has been extensively validated and provides a flexible evaluation process that minimizes the difficulties inherent in human-subject field testing. Defense applications such as detection probability assessment, camouflage pattern evaluation, conspicuity tests and automatic target recognition are discussed.

Doppler characteristics of sea clutter.

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

Raynal, Ann Marie; Doerry, Armin Walter

2010-06-01

Doppler radars can distinguish targets from clutter if the target's velocity along the radar line of sight is beyond that of the clutter. Some targets of interest may have a Doppler shift similar to that of clutter. The nature of sea clutter is different in the clutter and exo-clutter regions. This behavior requires special consideration regarding where a radar can expect to find sea-clutter returns in Doppler space and what detection algorithms are most appropriate to help mitigate false alarms and increase probability of detection of a target. This paper studies the existing state-of-the-art in the understanding of Doppler characteristicsmore » of sea clutter and scattering from the ocean to better understand the design and performance choices of a radar in differentiating targets from clutter under prevailing sea conditions.« less

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.

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.

An examination of along-track interferometry for detecting ground moving targets

NASA Technical Reports Server (NTRS)

Chen, Curtis W.; Chapin, Elaine; Muellerschoen, Ron; Hensley, Scott

2005-01-01

Along-track interferometry (ATI) is an interferometric synthetic aperture radar technique primarily used to measure Earth-surface velocities. We present results from an airborne experiment demonstrating phenomenology specific to the context of observing discrete ground targets moving admidst a stationary clutter background.

Morphological filtering and multiresolution fusion for mammographic microcalcification detection

NASA Astrophysics Data System (ADS)

Chen, Lulin; Chen, Chang W.; Parker, Kevin J.

1997-04-01

Mammographic images are often of relatively low contrast and poor sharpness with non-stationary background or clutter and are usually corrupted by noise. In this paper, we propose a new method for microcalcification detection using gray scale morphological filtering followed by multiresolution fusion and present a unified general filtering form called the local operating transformation for whitening filtering and adaptive thresholding. The gray scale morphological filters are used to remove all large areas that are considered as non-stationary background or clutter variations, i.e., to prewhiten images. The multiresolution fusion decision is based on matched filter theory. In addition to the normal matched filter, the Laplacian matched filter which is directly related through the wavelet transforms to multiresolution analysis is exploited for microcalcification feature detection. At the multiresolution fusion stage, the region growing techniques are used in each resolution level. The parent-child relations between resolution levels are adopted to make final detection decision. FROC is computed from test on the Nijmegen database.

LWIR hyperspectral micro-imager for detection of trace explosive particles

NASA Astrophysics Data System (ADS)

Bingham, Adam L.; Lucey, Paul G.; Akagi, Jason T.; Hinrichs, John L.; Knobbe, Edward T.

2014-05-01

Chemical micro-imaging is a powerful tool for the detection and identification of analytes of interest against a cluttered background (i.e. trace explosive particles left behind in a fingerprint). While a variety of groups have demonstrated the efficacy of Raman instruments for these applications, point by point or line by line acquisition of a targeted field of view (FOV) is a time consuming process if it is to be accomplished with useful spatial resolutions. Spectrum Photonics has developed and demonstrated a prototype system utilizing long wave infrared hyperspectral microscopy, which enables the simultaneous collection of LWIR reflectance spectra from 8-14 μm in a 30 x 7 mm FOV with 30 μm spatial resolution in 30 s. An overview of the uncooled Sagnac-based LWIR HSM system will be given, emphasizing the benefits of this approach. Laboratory Hyperspectral data collected from custom mixtures and fingerprint residues is shown, focusing on the ability of the LWIR chemical micro-imager to detect chemicals of interest out of a cluttered background.

Dual-energy approach to contrast-enhanced mammography using the balanced filter method: spectral optimization and preliminary phantom measurement.

PubMed

Saito, Masatoshi

2007-11-01

Dual-energy contrast agent-enhanced mammography is a technique of demonstrating breast cancers obscured by a cluttered background resulting from the contrast between soft tissues in the breast. The technique has usually been implemented by exploiting two exposures to different x-ray tube voltages. In this article, another dual-energy approach using the balanced filter method without switching the tube voltages is described. For the spectral optimization of dual-energy mammography using the balanced filters, we applied a theoretical framework reported by Lemacks et al. [Med. Phys. 29, 1739-1751 (2002)] to calculate the signal-to-noise ratio (SNR) in an iodinated contrast agent subtraction image. This permits the selection of beam parameters such as tube voltage and balanced filter material, and the optimization of the latter's thickness with respect to some critical quantity-in this case, mean glandular dose. For an imaging system with a 0.1 mm thick CsI:T1 scintillator, we predict that the optimal tube voltage would be 45 kVp for a tungsten anode using zirconium, iodine, and neodymium balanced filters. A mean glandular dose of 1.0 mGy is required to obtain an SNR of 5 in order to detect 1.0 mg/cm2 iodine in the resulting clutter-free image of a 5 cm thick breast composed of 50% adipose and 50% glandular tissue. In addition to spectral optimization, we carried out phantom measurements to demonstrate the present dual-energy approach for obtaining a clutter-free image, which preferentially shows iodine, of a breast phantom comprising three major components-acrylic spheres, olive oil, and an iodinated contrast agent. The detection of iodine details on the cluttered background originating from the contrast between acrylic spheres and olive oil is analogous to the task of distinguishing contrast agents in a mixture of glandular and adipose tissues.

Maximum Likelihood Detection of Electro-Optic Moving Targets

DTIC Science & Technology

1992-01-16

indicates intensity. The Infrared Measurements Sensor (IRMS) is a scanning sensor that collects both long wave- length infrared ( LWIR , 8 to 12 fim...moving clutter. Nonstationary spatial statistics correspond to the nonuniform intensity of the background scene. An equivalent viewpoint is to...Figure 6 compares theory and experiment for 10 frames of the Longjump LWIR data obtained from the IRMS scanning sensor, which is looking at a background

Ambient Background Particulate Compositiion Outdoor Natural Background: Interferents/Clutter

DTIC Science & Technology

2011-08-01

FIGURES 1. Map of UK Sampling Locations, Lizard, Pershore, Birmingham, Lichfield 10 2. Mean UK Airborne Pollen , Fungi, and Bacteria and/or their Sum...routinely other than for health effects. Allergy caused by pollen (>15 urn) and mold is monitored for health effects by National Allergy 9...occurrence. To achieve this, measurement of pollens , bacteria, and fungal spores and dust particulates were undertaken for weekly periods at four

Mixture-Tuned, Clutter Matched Filter for Remote Detection of Subpixel Spectral Signals

NASA Technical Reports Server (NTRS)

Thompson, David R.; Mandrake, Lukas; Green, Robert O.

2013-01-01

Mapping localized spectral features in large images demands sensitive and robust detection algorithms. Two aspects of large images that can harm matched-filter detection performance are addressed simultaneously. First, multimodal backgrounds may thwart the typical Gaussian model. Second, outlier features can trigger false detections from large projections onto the target vector. Two state-of-the-art approaches are combined that independently address outlier false positives and multimodal backgrounds. The background clustering models multimodal backgrounds, and the mixture tuned matched filter (MT-MF) addresses outliers. Combining the two methods captures significant additional performance benefits. The resulting mixture tuned clutter matched filter (MT-CMF) shows effective performance on simulated and airborne datasets. The classical MNF transform was applied, followed by k-means clustering. Then, each cluster s mean, covariance, and the corresponding eigenvalues were estimated. This yields a cluster-specific matched filter estimate as well as a cluster- specific feasibility score to flag outlier false positives. The technology described is a proof of concept that may be employed in future target detection and mapping applications for remote imaging spectrometers. It is of most direct relevance to JPL proposals for airborne and orbital hyperspectral instruments. Applications include subpixel target detection in hyperspectral scenes for military surveillance. Earth science applications include mineralogical mapping, species discrimination for ecosystem health monitoring, and land use classification.

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.

Detection, recognition, identification, and tracking of military vehicles using biomimetic intelligence

NASA Astrophysics Data System (ADS)

Pace, Paul W.; Sutherland, John

2001-10-01

This project is aimed at analyzing EO/IR images to provide automatic target detection/recognition/identification (ATR/D/I) of militarily relevant land targets. An increase in performance was accomplished using a biomimetic intelligence system functioning on low-cost, commercially available processing chips. Biomimetic intelligence has demonstrated advanced capabilities in the areas of hand- printed character recognition, real-time detection/identification of multiple faces in full 3D perspectives in cluttered environments, advanced capabilities in classification of ground-based military vehicles from SAR, and real-time ATR/D/I of ground-based military vehicles from EO/IR/HRR data in cluttered environments. The investigation applied these tools to real data sets and examined the parameters such as the minimum resolution for target recognition, the effect of target size, rotation, line-of-sight changes, contrast, partial obscuring, background clutter etc. The results demonstrated a real-time ATR/D/I capability against a subset of militarily relevant land targets operating in a realistic scenario. Typical results on the initial EO/IR data indicate probabilities of correct classification of resolved targets to be greater than 95 percent.

Non-negative infrared patch-image model: Robust target-background separation via partial sum minimization of singular values

NASA Astrophysics Data System (ADS)

Dai, Yimian; Wu, Yiquan; Song, Yu; Guo, Jun

2017-03-01

To further enhance the small targets and suppress the heavy clutters simultaneously, a robust non-negative infrared patch-image model via partial sum minimization of singular values is proposed. First, the intrinsic reason behind the undesirable performance of the state-of-the-art infrared patch-image (IPI) model when facing extremely complex backgrounds is analyzed. We point out that it lies in the mismatching of IPI model's implicit assumption of a large number of observations with the reality of deficient observations of strong edges. To fix this problem, instead of the nuclear norm, we adopt the partial sum of singular values to constrain the low-rank background patch-image, which could provide a more accurate background estimation and almost eliminate all the salient residuals in the decomposed target image. In addition, considering the fact that the infrared small target is always brighter than its adjacent background, we propose an additional non-negative constraint to the sparse target patch-image, which could not only wipe off more undesirable components ulteriorly but also accelerate the convergence rate. Finally, an algorithm based on inexact augmented Lagrange multiplier method is developed to solve the proposed model. A large number of experiments are conducted demonstrating that the proposed model has a significant improvement over the other nine competitive methods in terms of both clutter suppressing performance and convergence rate.

Experts' saliency ratings of speech-language dimensions associated with cluttering.

PubMed

Myers, Florence L; Bakker, Klaas

2014-12-01

The study aimed to investigate how cluttering specialists rated degree of prominence or saliency of various communication dimensions as contributing to the overall cluttering severity. Using a 9-point Likert type scoring system 31 cluttering specialists (with an average of 19 years of experience with cluttering) rated the relative importance of eight speech and language dimensions often associated with cluttering from '1' ('not important') at the low end to a '9' ('very important') at the high saliency end. Though the salience ratings differed the values in most cases were toward the high end of the rating scale. Additionally correlational analyses revealed several patterns of inter-correlation among the dimensions indicating that contribution of each communication dimension to overall cluttering severity may not be the same for all. Rather, it suggested that these dimensions may speak to cluttering severity through differential perceptual pathways that characterized the thinking of the experts who participated. Greater understanding of the various communication behaviors contributing to cluttering, severity is needed for theoretical research and clinical purposes. To the extent that the dimensions studied are thought to be relevant for cluttering, the results strengthen the notion that these dimensions (and perhaps others) should be included if we are to capture a comprehensive picture of cluttering severity. (a) describe the multidimensionality of cluttering; (b) discuss the perceptual saliency of speech-language dimensions associated with cluttering; (c) describe the interrelatedness of various speech-language dimensions associated with cluttering; (d) discuss how experts in cluttering rate the saliency of speech and language dimensions associated with cluttering when provided a list of these dimensions. Copyright © 2013 Elsevier Inc. All rights reserved.

Quantifying clutter: A comparison of four methods and their relationship to bat detection

Treesearch

Joy M. O’Keefe; Susan C. Loeb; Hoke S. Hill Jr.; J. Drew Lanham

2014-01-01

The degree of spatial complexity in the environment, or clutter, affects the quality of foraging habitats for bats and their detection with acoustic systems. Clutter has been assessed in a variety of ways but there are no standardized methods for measuring clutter. We compared four methods (Visual Clutter, Cluster, Single Variable, and Clutter Index) and related these...

Optimization of Visual Information Presentation for Visual Prosthesis.

PubMed

Guo, Fei; Yang, Yuan; Gao, Yong

2018-01-01

Visual prosthesis applying electrical stimulation to restore visual function for the blind has promising prospects. However, due to the low resolution, limited visual field, and the low dynamic range of the visual perception, huge loss of information occurred when presenting daily scenes. The ability of object recognition in real-life scenarios is severely restricted for prosthetic users. To overcome the limitations, optimizing the visual information in the simulated prosthetic vision has been the focus of research. This paper proposes two image processing strategies based on a salient object detection technique. The two processing strategies enable the prosthetic implants to focus on the object of interest and suppress the background clutter. Psychophysical experiments show that techniques such as foreground zooming with background clutter removal and foreground edge detection with background reduction have positive impacts on the task of object recognition in simulated prosthetic vision. By using edge detection and zooming technique, the two processing strategies significantly improve the recognition accuracy of objects. We can conclude that the visual prosthesis using our proposed strategy can assist the blind to improve their ability to recognize objects. The results will provide effective solutions for the further development of visual prosthesis.

Optimization of Visual Information Presentation for Visual Prosthesis

PubMed Central

Gao, Yong

2018-01-01

Visual prosthesis applying electrical stimulation to restore visual function for the blind has promising prospects. However, due to the low resolution, limited visual field, and the low dynamic range of the visual perception, huge loss of information occurred when presenting daily scenes. The ability of object recognition in real-life scenarios is severely restricted for prosthetic users. To overcome the limitations, optimizing the visual information in the simulated prosthetic vision has been the focus of research. This paper proposes two image processing strategies based on a salient object detection technique. The two processing strategies enable the prosthetic implants to focus on the object of interest and suppress the background clutter. Psychophysical experiments show that techniques such as foreground zooming with background clutter removal and foreground edge detection with background reduction have positive impacts on the task of object recognition in simulated prosthetic vision. By using edge detection and zooming technique, the two processing strategies significantly improve the recognition accuracy of objects. We can conclude that the visual prosthesis using our proposed strategy can assist the blind to improve their ability to recognize objects. The results will provide effective solutions for the further development of visual prosthesis. PMID:29731769

Application of Smoothing Techniques for Tracking Maneuvering Targets. Multiple Target Tracking in Clutter: New Approaches

DTIC Science & Technology

1992-07-01

target state estimation is affected not only by the measurement noise but also by the uncertainty in the origins of the measurements. To improve the...to identify targets in the presence of anticipated background noise (including earth, lunar, star backgrounds, complicated spacecraft structures...each other. Futhermore, those frames are often degraded versions of the original scene due to blur and noise . Through the task of image registration

Big brown bats (Eptesicus fuscus) reveal diverse strategies for sonar target tracking in clutter.

PubMed

Mao, Beatrice; Aytekin, Murat; Wilkinson, Gerald S; Moss, Cynthia F

2016-09-01

Bats actively adjust the acoustic features of their sonar calls to control echo information specific to a given task and environment. A previous study investigated how bats adapted their echolocation behavior when tracking a moving target in the presence of a stationary distracter at different distances and angular offsets. The use of only one distracter, however, left open the possibility that a bat could reduce the interference of the distracter by turning its head. Here, bats tracked a moving target in the presence of one or two symmetrically placed distracters to investigate adaptive echolocation behavior in a situation where vocalizing off-axis would result in increased interference from distracter echoes. Both bats reduced bandwidth and duration but increased sweep rate in more challenging distracter conditions, and surprisingly, made more head turns in the two-distracter condition compared to one, but only when distracters were placed at large angular offsets. However, for most variables examined, subjects showed distinct strategies to reduce clutter interference, either by (1) changing spectral or temporal features of their calls, or (2) producing large numbers of sonar sound groups and consistent head-turning behavior. The results suggest that individual bats can use different strategies for target tracking in cluttered environments.

A Semiparametric Model for Hyperspectral Anomaly Detection

DTIC Science & Technology

2012-01-01

treeline ) in the presence of natural background clutter (e.g., trees, dirt roads, grasses). Each target consists of about 7 × 4 pixels, and each pixel...vehicles near the treeline in Cube 1 (Figure 1) constitutes the target set, but, since anomaly detectors are not designed to detect a particular target

Using Morphological Filters for Pupil Detection in Infrared Videos

DTIC Science & Technology

2010-01-05

detect the subjects’ pupils, with manual parameterization of the filter coefficients. False detections due to background clutter from eyeglasses and...5 c) Fitting the detected objects with ellipses...boundaries overlaid on the original infrared image..................... 7 Figure 8 – Fitting the elongated pupils with circles often failed

Assessing clutter reduction in parallel coordinates using image processing techniques

NASA Astrophysics Data System (ADS)

Alhamaydh, Heba; Alzoubi, Hussein; Almasaeid, Hisham

2018-01-01

Information visualization has appeared as an important research field for multidimensional data and correlation analysis in recent years. Parallel coordinates (PCs) are one of the popular techniques to visual high-dimensional data. A problem with the PCs technique is that it suffers from crowding, a clutter which hides important data and obfuscates the information. Earlier research has been conducted to reduce clutter without loss in data content. We introduce the use of image processing techniques as an approach for assessing the performance of clutter reduction techniques in PC. We use histogram analysis as our first measure, where the mean feature of the color histograms of the possible alternative orderings of coordinates for the PC images is calculated and compared. The second measure is the extracted contrast feature from the texture of PC images based on gray-level co-occurrence matrices. The results show that the best PC image is the one that has the minimal mean value of the color histogram feature and the maximal contrast value of the texture feature. In addition to its simplicity, the proposed assessment method has the advantage of objectively assessing alternative ordering of PC visualization.

Improvement of Automated Identification of the Heart Wall in Echocardiography by Suppressing Clutter Component

NASA Astrophysics Data System (ADS)

Takahashi, Hiroki; Hasegawa, Hideyuki; Kanai, Hiroshi

2013-07-01

For the facilitation of analysis and elimination of the operator dependence in estimating the myocardial function in echocardiography, we have previously developed a method for automated identification of the heart wall. However, there are misclassified regions because the magnitude-squared coherence (MSC) function of echo signals, which is one of the features in the previous method, is sensitively affected by the clutter components such as multiple reflection and off-axis echo from external tissue or the nearby myocardium. The objective of the present study is to improve the performance of automated identification of the heart wall. For this purpose, we proposed a method to suppress the effect of the clutter components on the MSC of echo signals by applying an adaptive moving target indicator (MTI) filter to echo signals. In vivo experimental results showed that the misclassified regions were significantly reduced using our proposed method in the longitudinal axis view of the heart.

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

Designing clutter rejection filters with complex coefficients for airborne pulsed Doppler weather radar

NASA Technical Reports Server (NTRS)

Jamora, Dennis A.

1993-01-01

Ground clutter interference is a major problem for airborne pulse Doppler radar operating at low altitudes in a look-down mode. With Doppler zero set at the aircraft ground speed, ground clutter rejection filtering is typically accomplished using a high-pass filter with real valued coefficients and a stopband notch centered at zero Doppler. Clutter spectra from the NASA Wind Shear Flight Experiments of l991-1992 show that the dominant clutter mode can be located away from zero Doppler, particularly at short ranges dominated by sidelobe returns. Use of digital notch filters with complex valued coefficients so that the stopband notch can be located at any Doppler frequency is investigated. Several clutter mode tracking algorithms are considered to estimate the Doppler frequency location of the dominant clutter mode. From the examination of night data, when a dominant clutter mode away from zero Doppler is present, complex filtering is able to significantly increase clutter rejection over use of a notch filter centered at zero Doppler.

Robust pedestrian detection and tracking from a moving vehicle

NASA Astrophysics Data System (ADS)

Tuong, Nguyen Xuan; Müller, Thomas; Knoll, Alois

2011-01-01

In this paper, we address the problem of multi-person detection, tracking and distance estimation in a complex scenario using multi-cameras. Specifically, we are interested in a vision system for supporting the driver in avoiding any unwanted collision with the pedestrian. We propose an approach using Histograms of Oriented Gradients (HOG) to detect pedestrians on static images and a particle filter as a robust tracking technique to follow targets from frame to frame. Because the depth map requires expensive computation, we extract depth information of targets using Direct Linear Transformation (DLT) to reconstruct 3D-coordinates of correspondent points found by running Speeded Up Robust Features (SURF) on two input images. Using the particle filter the proposed tracker can efficiently handle target occlusions in a simple background environment. However, to achieve reliable performance in complex scenarios with frequent target occlusions and complex cluttered background, results from the detection module are integrated to create feedback and recover the tracker from tracking failures due to the complexity of the environment and target appearance model variability. The proposed approach is evaluated on different data sets both in a simple background scenario and a cluttered background environment. The result shows that, by integrating detector and tracker, a reliable and stable performance is possible even if occlusion occurs frequently in highly complex environment. A vision-based collision avoidance system for an intelligent car, as a result, can be achieved.

Particle Filtering with Region-based Matching for Tracking of Partially Occluded and Scaled Targets*

PubMed Central

Nakhmani, Arie; Tannenbaum, Allen

2012-01-01

Visual tracking of arbitrary targets in clutter is important for a wide range of military and civilian applications. We propose a general framework for the tracking of scaled and partially occluded targets, which do not necessarily have prominent features. The algorithm proposed in the present paper utilizes a modified normalized cross-correlation as the likelihood for a particle filter. The algorithm divides the template, selected by the user in the first video frame, into numerous patches. The matching process of these patches by particle filtering allows one to handle the target’s occlusions and scaling. Experimental results with fixed rectangular templates show that the method is reliable for videos with nonstationary, noisy, and cluttered background, and provides accurate trajectories in cases of target translation, scaling, and occlusion. PMID:22506088

On the Use of Low-Cost Radar Networks for Collision Warning Systems Aboard Dumpers

PubMed Central

González-Partida, José-Tomás; León-Infante, Francisco; Blázquez-García, Rodrigo; Burgos-García, Mateo

2014-01-01

The use of dumpers is one of the main causes of accidents in construction sites, many of them with fatal consequences. These kinds of work machines have many blind angles that complicate the driving task due to their large size and volume. To guarantee safety conditions is necessary to use automatic aid systems that can detect and locate the different objects and people in a work area. One promising solution is a radar network based on low-cost radar transceivers aboard the dumper. The complete system is specified to operate with a very low false alarm rate to avoid unnecessary stops of the dumper that reduce its productivity. The main sources of false alarm are the heavy ground clutter, and the interferences between the radars of the network. This article analyses the clutter for LFM signaling and proposes the use of Offset Linear Frequency Modulated Continuous Wave (OLFM-CW) as radar signal. This kind of waveform can be optimized to reject clutter and self-interferences. Jointly, a data fusion chain could be used to reduce the false alarm rate of the complete radar network. A real experiment is shown to demonstrate the feasibility of the proposed system. PMID:24577521

On the use of low-cost radar networks for collision warning systems aboard dumpers.

PubMed

González-Partida, José-Tomás; León-Infante, Francisco; Blázquez-García, Rodrigo; Burgos-García, Mateo

2014-02-26

The use of dumpers is one of the main causes of accidents in construction sites, many of them with fatal consequences. These kinds of work machines have many blind angles that complicate the driving task due to their large size and volume. To guarantee safety conditions is necessary to use automatic aid systems that can detect and locate the different objects and people in a work area. One promising solution is a radar network based on low-cost radar transceivers aboard the dumper. The complete system is specified to operate with a very low false alarm rate to avoid unnecessary stops of the dumper that reduce its productivity. The main sources of false alarm are the heavy ground clutter, and the interferences between the radars of the network. This article analyses the clutter for LFM signaling and proposes the use of Offset Linear Frequency Modulated Continuous Wave (OLFM-CW) as radar signal. This kind of waveform can be optimized to reject clutter and self-interferences. Jointly, a data fusion chain could be used to reduce the false alarm rate of the complete radar network. A real experiment is shown to demonstrate the feasibility of the proposed system.

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.

An automated data exploitation system for airborne sensors

NASA Astrophysics Data System (ADS)

Chen, Hai-Wen; McGurr, Mike

2014-06-01

Advanced wide area persistent surveillance (WAPS) sensor systems on manned or unmanned airborne vehicles are essential for wide-area urban security monitoring in order to protect our people and our warfighter from terrorist attacks. Currently, human (imagery) analysts process huge data collections from full motion video (FMV) for data exploitation and analysis (real-time and forensic), providing slow and inaccurate results. An Automated Data Exploitation System (ADES) is urgently needed. In this paper, we present a recently developed ADES for airborne vehicles under heavy urban background clutter conditions. This system includes four processes: (1) fast image registration, stabilization, and mosaicking; (2) advanced non-linear morphological moving target detection; (3) robust multiple target (vehicles, dismounts, and human) tracking (up to 100 target tracks); and (4) moving or static target/object recognition (super-resolution). Test results with real FMV data indicate that our ADES can reliably detect, track, and recognize multiple vehicles under heavy urban background clutters. Furthermore, our example shows that ADES as a baseline platform can provide capability for vehicle abnormal behavior detection to help imagery analysts quickly trace down potential threats and crimes.

A model of clutter for complex, multivariate geospatial displays.

PubMed

Lohrenz, Maura C; Trafton, J Gregory; Beck, R Melissa; Gendron, Marlin L

2009-02-01

A novel model of measuring clutter in complex geospatial displays was compared with human ratings of subjective clutter as a measure of convergent validity. The new model is called the color-clustering clutter (C3) model. Clutter is a known problem in displays of complex data and has been shown to affect target search performance. Previous clutter models are discussed and compared with the C3 model. Two experiments were performed. In Experiment 1, participants performed subjective clutter ratings on six classes of information visualizations. Empirical results were used to set two free parameters in the model. In Experiment 2, participants performed subjective clutter ratings on aeronautical charts. Both experiments compared and correlated empirical data to model predictions. The first experiment resulted in a .76 correlation between ratings and C3. The second experiment resulted in a .86 correlation, significantly better than results from a model developed by Rosenholtz et al. Outliers to our correlation suggest further improvements to C3. We suggest that (a) the C3 model is a good predictor of subjective impressions of clutter in geospatial displays, (b) geospatial clutter is a function of color density and saliency (primary C3 components), and (c) pattern analysis techniques could further improve C3. The C3 model could be used to improve the design of electronic geospatial displays by suggesting when a display will be too cluttered for its intended audience.

Detection of exudates in fundus imagery using a constant false-alarm rate (CFAR) detector

NASA Astrophysics Data System (ADS)

Khanna, Manish; Kapoor, Elina

2014-05-01

Diabetic retinopathy is the leading cause of blindness in adults in the United States. The presence of exudates in fundus imagery is the early sign of diabetic retinopathy so detection of these lesions is essential in preventing further ocular damage. In this paper we present a novel technique to automatically detect exudates in fundus imagery that is robust against spatial and temporal variations of background noise. The detection threshold is adjusted dynamically, based on the local noise statics around the pixel under test in order to maintain a pre-determined, constant false alarm rate (CFAR). The CFAR detector is often used to detect bright targets in radar imagery where the background clutter can vary considerably from scene to scene and with angle to the scene. Similarly, the CFAR detector addresses the challenge of detecting exudate lesions in RGB and multispectral fundus imagery where the background clutter often exhibits variations in brightness and texture. These variations present a challenge to common, global thresholding detection algorithms and other methods. Performance of the CFAR algorithm is tested against a publicly available, annotated, diabetic retinopathy database and preliminary testing suggests that performance of the CFAR detector proves to be superior to techniques such as Otsu thresholding.

Microwave properties of a quiet sea

NASA Technical Reports Server (NTRS)

Stacey, J.

1985-01-01

The microwave flux responses of a quiet sea are observed at five microwave frequencies and with both horizontal and vertical polarizations at each frequency--a simultaneous 10 channel receiving system. The measurements are taken from Earth orbit with an articulating antenna. The 10 channel responses are taken simultaneously since they share a common articulating collector with a multifrequency feed. The plotted flux responses show: (1) the effects of the relative, on-axis-gain of the collecting aperture for each frequency; (2) the effects of polarization rotation in the output responses of the receive when the collecting aperture mechanically rotates about a feed that is fixed; (3) the difference between the flux magnitudes for the horizontal and vertical channels, at each of the five frequencies, and for each pointing position, over a 44 degree scan angle; and (4) the RMS value of the clutter--as reckoned over the interval of a full swath for each of the 10 channels. The clutter is derived from the standard error of estimate of the plotted swath response for each channel. The expected value of the background temperature is computed for each of the three quiet seas. The background temperature includes contributions from the cosmic background, the downwelling path, the sea surface, and the upwelling path.

Bed Bug Tips

EPA Pesticide Factsheets

How to deal with bed bugs in one printable page. Ten tips include ensuring correct insect identification, reducing clutter, understand integrated pest management, using mattress and box spring encasements, and heat treatment.

Searching in clutter : visual attention strategies of expert pilots

DOT National Transportation Integrated Search

2012-10-22

Clutter can slow visual search. However, experts may develop attention strategies that alleviate the effects of clutter on search performance. In the current study we examined the effects of global and local clutter on visual search performance and a...

Detection of buried targets using a new enhanced very early time electromagnetic (VETEM) prototype system

USGS Publications Warehouse

Cui, T.J.; Chew, W.C.; Aydiner, A.A.; Wright, D.L.; Smith, D.V.

2001-01-01

In this paper, numerical simulations of a new enhanced very early time electromagnetic (VETEM) prototype system are presented, where a horizontal transmitting loop and two horizontal receiving loops are used to detect buried targets, in which three loops share the same axis and the transmitter is located at the center of receivers. In the new VETEM system, the difference of signals from two receivers is taken to eliminate strong direct-signals from the transmitter and background clutter and furthermore to obtain a better SNR for buried targets. Because strong coupling exists between the transmitter and receivers, accurate analysis of the three-loop antenna system is required, for which a loop-tree basis function method has been utilized to overcome the low-frequency breakdown problem. In the analysis of scattering problem from buried targets, a conjugate gradient (CG) method with fast Fourier transform (FFT) is applied to solve the electric field integral equation. However, the convergence of such CG-FFT algorithm is extremely slow at very low frequencies. In order to increase the convergence rate, a frequency-hopping approach has been used. Finally, the primary, coupling, reflected, and scattered magnetic fields are evaluated at receiving loops to calculate the output electric current. Numerous simulation results are given to interpret the new VETEM system. Comparing with other single-transmitter-receiver systems, the new VETEM has better SNR and ability to reduce the clutter.

An integrated measure of display clutter based on feature content, user knowledge and attention allocation factors.

PubMed

Pankok, Carl; Kaber, David B

2018-05-01

Existing measures of display clutter in the literature generally exhibit weak correlations with task performance, which limits their utility in safety-critical domains. A literature review led to formulation of an integrated display data- and user knowledge-driven measure of display clutter. A driving simulation experiment was conducted in which participants were asked to search 'high' and 'low' clutter displays for navigation information. Data-driven measures and subjective perceptions of clutter were collected along with patterns of visual attention allocation and driving performance responses during time periods in which participants searched the navigation display for information. The new integrated measure was more strongly correlated with driving performance than other, previously developed measures of clutter, particularly in the case of low-clutter displays. Integrating display data and user knowledge factors with patterns of visual attention allocation shows promise for measuring display clutter and correlation with task performance, particularly for low-clutter displays. Practitioner Summary: A novel measure of display clutter was formulated, accounting for display data content, user knowledge states and patterns of visual attention allocation. The measure was evaluated in terms of correlations with driver performance in a safety-critical driving simulation study. The measure exhibited stronger correlations with task performance than previously defined measures.

Performance Evaluation of Adaptive Imaging Based on Multiphase Apodization with Cross-correlation: A Pilot Study in Abdominal Ultrasound.

PubMed

Shin, Junseob; Chen, Yu; Malhi, Harshawn; Chen, Frank; Yen, Jesse

2018-05-01

Degradation of image contrast caused by phase aberration, off-axis clutter, and reverberation clutter remains one of the most important problems in abdominal ultrasound imaging. Multiphase apodization with cross-correlation (MPAX) is a novel beamforming technique that enhances ultrasound image contrast by adaptively suppressing unwanted acoustic clutter. MPAX employs multiple pairs of complementary sinusoidal phase apodizations to intentionally introduce grating lobes that can be used to derive a weighting matrix, which mostly preserves the on-axis signals from tissue but reduces acoustic clutter contributions when multiplied with the beamformed radio-frequency (RF) signals. In this paper, in vivo performance of the MPAX technique was evaluated in abdominal ultrasound using data sets obtained from 10 human subjects referred for abdominal ultrasound at the USC Keck School of Medicine. Improvement in image contrast was quantified, first, by the contrast-to-noise ratio (CNR) and, second, by the rating of two experienced radiologists. The MPAX technique was evaluated for longitudinal and transverse views of the abdominal aorta, the inferior vena cava, the gallbladder, and the portal vein. Our in vivo results and analyses demonstrate the feasibility of the MPAX technique in enhancing image contrast in abdominal ultrasound and show potential for creating high contrast ultrasound images with improved target detectability and diagnostic confidence.

Tracking through laser-induced clutter for air-to-ground directed energy system

NASA Astrophysics Data System (ADS)

Belen'kii, Mikhail; Brinkley, Timothy; Hughes, Kevin; Tannenbaum, Allen

2003-09-01

The agility and speed with which directed energy can be retargeted and delivered to the target makes a laser weapon highly desirable in tactical battlefield environments. A directed energy system can effectively damage and possibly destroy relatively soft targets on the ground. In order to accurately point a high-energy beam at the target, the directed energy system must be able to acquire and track targets of interest in highly cluttered environments, under different weather, smoke, and camouflage conditions and in the presence of turbulence and thermal blooming. To meet these requirements, we proposed a concept of a multi spectral tracker, which integrates three sensors: SAR radar, a passive MWIR optical tracker, and a range-gated laser illuminated tracker. In this paper we evaluated the feasibility of the integrated optical tracker and arrived to the following conclusions: a) the contrast enhancement by mapping the original pixel distribution to the desired one enhances the target identification capability, b) a reduction of the divergence of the illuminating beam reduces rms pointing error of a laser tracker, c) a clutter removal algorithm based on active contours is capable of capturing targets in highly cluttered environments, d) the daytime rms pointing error caused by anisoplanatism of the track point to the aim point is comparable to the diffraction-limited beam spot size, f) the peak intensity shift from the optical axis caused by thermal blooming at 5 km range for the air-to-ground engagement scenario is on the order of 8 μrad, and it is 10 μrad at 10 km range, and e) the thermal blooming reduces the peak average power in a 2 cm bucket at 5 km range by a factor of 8, and it reduces the peak average power in the bucket at 10 km range by a factor of 22.

3rd Generation Thermal Imager Sensor Performance

DTIC Science & Technology

2006-11-01

suffers in the day compared to the night. This degradation is related to high levels of daytime clutter caused by solar reflections and loading and...1 2 3 4 5 LWIR σT (K) M W IR σ T (K ) MWIR = LWIR White Building Block Door Road Roof Shingle Window Rural Backgrounds: MWIR σT vs LWIR σT

Capabilities of radar as they might relate to entomological studies

NASA Technical Reports Server (NTRS)

Skolnik, M. I.

1979-01-01

A tutoral background of radar capabilities and its potential for insect research is provided. The basic principles and concepts of radar were reviewed. Information on current radar equipment was examined. Specific issues related to insect research included; target cross-section, radar frequency, tracking target recognition and false alarms, clutter reduction, radar transmitter power, and ascertained atmospheric processes.

A Polarization Technique for Mitigating Low Grazing Angle Radar Sea Clutter

DTIC Science & Technology

2017-03-03

alarm mitigation, low grazing angles, polarimetry , radar, sea clutter. I. INTRODUCTION Sea clutter poses unique challenges for maritime radars looking...radar polarimetry offers a practical means of robustly mitigating LGA sea clutter across a range of radar and environmental parameters, we stood up a

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.

Retrodiction for Bayesian multiple-hypothesis/multiple-target tracking in densely cluttered environment

NASA Astrophysics Data System (ADS)

Koch, Wolfgang

1996-05-01

Sensor data processing in a dense target/dense clutter environment is inevitably confronted with data association conflicts which correspond with the multiple hypothesis character of many modern approaches (MHT: multiple hypothesis tracking). In this paper we analyze the efficiency of retrodictive techniques that generalize standard fixed interval smoothing to MHT applications. 'Delayed estimation' based on retrodiction provides uniquely interpretable and accurate trajectories from ambiguous MHT output if a certain time delay is tolerated. In a Bayesian framework the theoretical background of retrodiction and its intimate relation to Bayesian MHT is sketched. By a simulated example with two closely-spaced targets, relatively low detection probabilities, and rather high false return densities, we demonstrate the benefits of retrodiction and quantitatively discuss the achievable track accuracies and the time delays involved for typical radar parameters.

PMHT Approach for Multi-Target Multi-Sensor Sonar Tracking in Clutter.

PubMed

Li, Xiaohua; Li, Yaan; Yu, Jing; Chen, Xiao; Dai, Miao

2015-11-06

Multi-sensor sonar tracking has many advantages, such as the potential to reduce the overall measurement uncertainty and the possibility to hide the receiver. However, the use of multi-target multi-sensor sonar tracking is challenging because of the complexity of the underwater environment, especially the low target detection probability and extremely large number of false alarms caused by reverberation. In this work, to solve the problem of multi-target multi-sensor sonar tracking in the presence of clutter, a novel probabilistic multi-hypothesis tracker (PMHT) approach based on the extended Kalman filter (EKF) and unscented Kalman filter (UKF) is proposed. The PMHT can efficiently handle the unknown measurements-to-targets and measurements-to-transmitters data association ambiguity. The EKF and UKF are used to deal with the high degree of nonlinearity in the measurement model. The simulation results show that the proposed algorithm can improve the target tracking performance in a cluttered environment greatly, and its computational load is low.

Slot Antenna Integrated Re-Entrant Resonator Based Wireless Pressure Sensor for High-Temperature Applications.

PubMed

Su, Shujing; Lu, Fei; Wu, Guozhu; Wu, Dezhi; Tan, Qiulin; Dong, Helei; Xiong, Jijun

2017-08-25

The highly sensitive pressure sensor presented in this paper aims at wireless passive sensing in a high temperature environment by using microwave backscattering technology. The structure of the re-entrant resonator was analyzed and optimized using theoretical calculation, software simulation, and its equivalent lump circuit model was first modified by us. Micro-machining and high-temperature co-fired ceramic (HTCC) process technologies were applied to fabricate the sensor, solving the common problem of cavity sealing during the air pressure loading test. In addition, to prevent the response signal from being immersed in the strong background clutter of the hermetic metal chamber, which makes its detection difficult, we proposed two key techniques to improve the signal to noise ratio: the suppression of strong background clutter and the detection of the weak backscattered signal of the sensor. The pressure sensor demonstrated in this paper works well for gas pressure loading between 40 and 120 kPa in a temperature range of 24 °C to 800 °C. The experimental results show that the sensor resonant frequency lies at 2.1065 GHz, with a maximum pressure sensitivity of 73.125 kHz/kPa.

Clutter in electronic medical records: examining its performance and attentional costs using eye tracking.

PubMed

Moacdieh, Nadine; Sarter, Nadine

2015-06-01

The objective was to use eye tracking to trace the underlying changes in attention allocation associated with the performance effects of clutter, stress, and task difficulty in visual search and noticing tasks. Clutter can degrade performance in complex domains, yet more needs to be known about the associated changes in attention allocation, particularly in the presence of stress and for different tasks. Frequently used and relatively simple eye tracking metrics do not effectively capture the various effects of clutter, which is critical for comprehensively analyzing clutter and developing targeted, real-time countermeasures. Electronic medical records (EMRs) were chosen as the application domain for this research. Clutter, stress, and task difficulty were manipulated, and physicians' performance on search and noticing tasks was recorded. Several eye tracking metrics were used to trace attention allocation throughout those tasks, and subjective data were gathered via a debriefing questionnaire. Clutter degraded performance in terms of response time and noticing accuracy. These decrements were largely accentuated by high stress and task difficulty. Eye tracking revealed the underlying attentional mechanisms, and several display-independent metrics were shown to be significant indicators of the effects of clutter. Eye tracking provides a promising means to understand in detail (offline) and prevent (in real time) major performance breakdowns due to clutter. Display designers need to be aware of the risks of clutter in EMRs and other complex displays and can use the identified eye tracking metrics to evaluate and/or adjust their display. © 2015, Human Factors and Ergonomics Society.

Reducing Surface Clutter in Cloud Profiling Radar Data

NASA Technical Reports Server (NTRS)

Tanelli, Simone; Pak, Kyung; Durden, Stephen; Im, Eastwood

2008-01-01

An algorithm has been devised to reduce ground clutter in the data products of the CloudSat Cloud Profiling Radar (CPR), which is a nadir-looking radar instrument, in orbit around the Earth, that measures power backscattered by clouds as a function of distance from the instrument. Ground clutter contaminates the CPR data in the lowest 1 km of the atmospheric profile, heretofore making it impossible to use CPR data to satisfy the scientific interest in studying clouds and light rainfall at low altitude. The algorithm is based partly on the fact that the CloudSat orbit is such that the geodetic altitude of the CPR varies continuously over a range of approximately 25 km. As the geodetic altitude changes, the radar timing parameters are changed at intervals defined by flight software in order to keep the troposphere inside a data-collection time window. However, within each interval, the surface of the Earth continuously "scans through" (that is, it moves across) a few range bins of the data time window. For each radar profile, only few samples [one for every range-bin increment ((Delta)r = 240 m)] of the surface-clutter signature are available around the range bin in which the peak of surface return is observed, but samples in consecutive radar profiles are offset slightly (by amounts much less than (Delta)r) with respect to each other according to the relative change in geodetic altitude. As a consequence, in a case in which the surface area under examination is homogenous (e.g., an ocean surface), a sequence of consecutive radar profiles of the surface in that area contains samples of the surface response with range resolution (Delta)p much finer than the range-bin increment ((Delta)p << r). Once the high-resolution surface response has thus become available, the profile of surface clutter can be accurately estimated by use of a conventional maximum-correlation scheme: A translated and scaled version of the high-resolution surface response is fitted to the observed low-resolution profile. The translation and scaling factors that optimize the fit in a maximum-correlation sense represent (1) the true position of the surface relative to the sampled surface peak and (2) the magnitude of the surface backscatter. The performance of this algorithm has been tested on CloudSat data acquired over an ocean surface. A preliminary analysis of the test data showed a surface-clutter-rejection ratio over flat surfaces of >10 dB and a reduction of the contaminated altitude over ocean from about 1 km to about 0.5 km (over the ocean). The algorithm has been embedded in CloudSat L1B processing as of Release 04 (July 2007), and the estimated flat surface clutter is removed in L2B-GEOPROF product from the observed profile of reflectivity (see CloudSat product documentation for details and performance at http://www.cloudsat.cira.colostate.edu/ dataSpecs.php?prodid=1).

Cluttering

MedlinePlus

... to plan and evaluate treatment.) Myers, F. L. & St. Louis, K. O. (1992). Cluttering: A clinical perspective . ... on the nature, diagnosis, and treatment of cluttering.) St. Louis, K. O. (Ed.) (1996). Research and opinion ...

Study of clutter origin in in-vivo epi-optoacoustic imaging of human forearms

NASA Astrophysics Data System (ADS)

Preisser, Stefan; Held, Gerrit; Akarçay, Hidayet G.; Jaeger, Michael; Frenz, Martin

2016-09-01

Epi-optoacoustic (OA) imaging offers flexible clinical diagnostics of the human body when the irradiation optic is attached to or directly integrated into the acoustic probe. Epi-OA images, however, encounter clutter that deteriorates contrast and significantly limits imaging depth. This study elaborates clutter origin in clinical epi-optoacoustic imaging using a linear array probe for scanning the human forearm. We demonstrate that the clutter strength strongly varies with the imaging location but stays stable over time, indicating that clutter is caused by anatomical structures. OA transients which are generated by strong optical absorbers located at the irradiation spot were identified to be the main source of clutter. These transients obscure deep in-plane OA signals when detected by the transducer either directly or after being acoustically scattered in the imaging plane. In addition, OA transients generated in the skin below the probe result in acoustic reverberations, which cause problems in image interpretation and limit imaging depth. Understanding clutter origin allows a better interpretation of clinical OA imaging, helps to design clutter compensation techniques and raises the prospect of contrast optimization via the design of the irradiation geometry.

Expertise Effects in Face-Selective Areas are Robust to Clutter and Diverted Attention, but not to Competition

PubMed Central

McGugin, Rankin Williams; Van Gulick, Ana E.; Tamber-Rosenau, Benjamin J.; Ross, David A.; Gauthier, Isabel

2015-01-01

Expertise effects for nonface objects in face-selective brain areas may reflect stable aspects of neuronal selectivity that determine how observers perceive objects. However, bottom-up (e.g., clutter from irrelevant objects) and top-down manipulations (e.g., attentional selection) can influence activity, affecting the link between category selectivity and individual performance. We test the prediction that individual differences expressed as neural expertise effects for cars in face-selective areas are sufficiently stable to survive clutter and manipulations of attention. Additionally, behavioral work and work using event related potentials suggest that expertise effects may not survive competition; we investigate this using functional magnetic resonance imaging. Subjects varying in expertise with cars made 1-back decisions about cars, faces, and objects in displays containing one or 2 objects, with only one category attended. Univariate analyses suggest car expertise effects are robust to clutter, dampened by reducing attention to cars, but nonetheless more robust to manipulations of attention than competition. While univariate expertise effects are severely abolished by competition between cars and faces, multivariate analyses reveal new information related to car expertise. These results demonstrate that signals in face-selective areas predict expertise effects for nonface objects in a variety of conditions, although individual differences may be expressed in different dependent measures depending on task and instructions. PMID:24682187

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.

Protecting Yourself from Bed Bugs in Public Places

EPA Pesticide Factsheets

Infestations in non-residential areas are rare, but may still present opportunities for hitchhiking bugs. So reduce clutter, stow belongings separately, monitor or inspect upholstered furniture, educate staff, and keep integrated pest management in mind.

Impulse radar with swept range gate

DOEpatents

McEwan, Thomas E.

1998-09-08

A radar range finder and hidden object locator is based on ultra-wide band radar with a high resolution swept range gate. The device generates an equivalent time amplitude scan with a typical range of 4 inches to 20 feet, and an analog range resolution as limited by a jitter of on the order of 0.01 inches. A differential sampling receiver is employed to effectively eliminate ringing and other aberrations induced in the receiver by the near proximity of the transmit antenna (10), so a background subtraction is not needed, simplifying the circuitry while improving performance. Techniques are used to reduce clutter in the receive signal, such as decoupling the receive (24) and transmit cavities (22) by placing a space between them, using conductive or radiative damping elements on the cavities, and using terminating plates on the sides of the openings. The antennas can be arranged in a side-by-side parallel spaced apart configuration or in a coplanar opposed configuration which significantly reduces main bang coupling.

Impulse radar with swept range gate

DOEpatents

McEwan, T.E.

1998-09-08

A radar range finder and hidden object locator is based on ultra-wide band radar with a high resolution swept range gate. The device generates an equivalent time amplitude scan with a typical range of 4 inches to 20 feet, and an analog range resolution as limited by a jitter of on the order of 0.01 inches. A differential sampling receiver is employed to effectively eliminate ringing and other aberrations induced in the receiver by the near proximity of the transmit antenna, so a background subtraction is not needed, simplifying the circuitry while improving performance. Techniques are used to reduce clutter in the receive signal, such as decoupling the receive and transmit cavities by placing a space between them, using conductive or radiative damping elements on the cavities, and using terminating plates on the sides of the openings. The antennas can be arranged in a side-by-side parallel spaced apart configuration or in a coplanar opposed configuration which significantly reduces main bang coupling. 25 figs.

The influence of clutter on real-world scene search: evidence from search efficiency and eye movements.

PubMed

Henderson, John M; Chanceaux, Myriam; Smith, Tim J

2009-01-23

We investigated the relationship between visual clutter and visual search in real-world scenes. Specifically, we investigated whether visual clutter, indexed by feature congestion, sub-band entropy, and edge density, correlates with search performance as assessed both by traditional behavioral measures (response time and error rate) and by eye movements. Our results demonstrate that clutter is related to search performance. These results hold for both traditional search measures and for eye movements. The results suggest that clutter may serve as an image-based proxy for search set size in real-world scenes.

The design and implementation of radar clutter modelling and adaptive target detection techniques

NASA Astrophysics Data System (ADS)

Ali, Mohammed Hussain

The analysis and reduction of radar clutter is investigated. Clutter is the term applied to unwanted radar reflections from land, sea, precipitation, and/or man-made objects. A great deal of useful information regarding the characteristics of clutter can be obtained by the application of frequency domain analytical methods. Thus, some considerable time was spent assessing the various techniques available and their possible application to radar clutter. In order to better understand clutter, use of a clutter model was considered desirable. There are many techniques which will enable a target to be detected in the presence of clutter. One of the most flexible of these is that of adaptive filtering. This technique was thoroughly investigated and a method for improving its efficacy was devised. The modified adaptive filter employed differential adaption times to enhance detectability. Adaptation time as a factor relating to target detectability is a new concept and was investigated in some detail. It was considered desirable to implement the theoretical work in dedicated hardware to confirm that the modified clutter model and the adaptive filter technique actually performed as predicted. The equipment produced is capable of operation in real time and provides an insight into real time DSP applications. This equipment is sufficiently rapid to produce a real time display on the actual PPI system. Finally a software package was also produced which would simulate the operation of a PPI display and thus ease the interpretation of the filter outputs.

Preparing for Treatment Against Bed Bugs

EPA Pesticide Factsheets

Whether hiring a pest management professional or trying to eliminate the bugs yourself, taking these first steps will increase effectiveness and speed: reduce clutter, use encasements on your mattress and box spring, vacuum and heat treat, and seal cracks.

Removing interfering clutter associated with radar pulses that an airborne radar receives from a radar transponder

DOEpatents

Ormesher, Richard C.; Axline, Robert M.

2008-12-02

Interfering clutter in radar pulses received by an airborne radar system from a radar transponder can be suppressed by developing a representation of the incoming echo-voltage time-series that permits the clutter associated with predetermined parts of the time-series to be estimated. These estimates can be used to estimate and suppress the clutter associated with other parts of the time-series.

Handheld Broadband Electromagnetic UXO Sensor

DTIC Science & Technology

2006-12-01

metal pipes of various sizes, some ferrous (steel) and some nonferrous (3 aluminum, 2 copper), have been buried at depths ranging from 10 to 110cm...Cart- or Sled-Mounted, and Pushed or Towed ......4 Figure 4. Example of Metallic Target Spectra for Sensor Axis...1 1.0 EXECUTIVE SUMMARY 1.1 BACKGROUND Detection of unexploded ordnance (UXO) and discrimination between UXO and metallic clutter pose challenges

Effects of clutter on information processing deficits in individuals with hoarding disorder.

PubMed

Raines, Amanda M; Timpano, Kiara R; Schmidt, Norman B

2014-09-01

Current cognitive behavioral models of hoarding view hoarding as a multifaceted problem stemming from various information processing deficits. However, there is also reason to suspect that the consequences of hoarding may in turn impact or modulate deficits in information processing. The current study sought to expand upon the existing literature by manipulating clutter to examine whether the presence of a cluttered environment affects information processing. Participants included 34 individuals with hoarding disorder. Participants were randomized into a clutter or non-clutter condition and asked to complete various neuropsychological tasks of memory and attention. Results revealed that hoarding severity was associated with difficulties in sustained attention. However, individuals in the clutter condition relative to the non-clutter condition did not experience greater deficits in information processing. Limitations include the cross-sectional design and small sample size. The current findings add considerably to a growing body of literature on the relationships between information processing deficits and hoarding behaviors. Research of this type is integral to understanding the etiology and maintenance of hoarding. Copyright © 2014 Elsevier B.V. All rights reserved.

Subaperture clutter filter with CFAR signal detection

DOEpatents

Ormesher, Richard C.; Naething, Richard M.

2016-08-30

The various technologies presented herein relate to the determination of whether a received signal comprising radar clutter further comprises a communication signal. The communication signal can comprise of a preamble, a data symbol, communication data, etc. A first portion of the radar clutter is analyzed to determine a radar signature of the first portion of the radar clutter. A second portion of the radar clutter can be extracted based on the radar signature of the first portion. Following extraction, any residual signal can be analyzed to retrieve preamble data, etc. The received signal can be based upon a linear frequency modulation (e.g., a chirp modulation) whereby the chirp frequency can be determined and the frequency of transmission of the communication signal can be based accordingly thereon. The duration and/or bandwidth of the communication signal can be a portion of the duration and/or the bandwidth of the radar clutter.

Air Defense Initiative (ADI) Clutter Model

DTIC Science & Technology

1998-04-01

Pusey, P. N., 1976 , "A Model for Non-Rayleigh Sea Echo," IEEE AP- 24 , No.6, November 197 6 James, W. J., 1961, The Effect of the Weather in Eastern...system procurement. RADC has been involved in the development of clutter models for system procurements for many years. Between 1976 and 1979, RADC...performed measurements and suggested clutter models for the SEEK IGLOO ( 1976 ) and the SEEK FROST (1978-9) programs. Since 1980, current clutter models

Expertise Effects in Face-Selective Areas are Robust to Clutter and Diverted Attention, but not to Competition.

PubMed

McGugin, Rankin Williams; Van Gulick, Ana E; Tamber-Rosenau, Benjamin J; Ross, David A; Gauthier, Isabel

2015-09-01

Expertise effects for nonface objects in face-selective brain areas may reflect stable aspects of neuronal selectivity that determine how observers perceive objects. However, bottom-up (e.g., clutter from irrelevant objects) and top-down manipulations (e.g., attentional selection) can influence activity, affecting the link between category selectivity and individual performance. We test the prediction that individual differences expressed as neural expertise effects for cars in face-selective areas are sufficiently stable to survive clutter and manipulations of attention. Additionally, behavioral work and work using event related potentials suggest that expertise effects may not survive competition; we investigate this using functional magnetic resonance imaging. Subjects varying in expertise with cars made 1-back decisions about cars, faces, and objects in displays containing one or 2 objects, with only one category attended. Univariate analyses suggest car expertise effects are robust to clutter, dampened by reducing attention to cars, but nonetheless more robust to manipulations of attention than competition. While univariate expertise effects are severely abolished by competition between cars and faces, multivariate analyses reveal new information related to car expertise. These results demonstrate that signals in face-selective areas predict expertise effects for nonface objects in a variety of conditions, although individual differences may be expressed in different dependent measures depending on task and instructions. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Terradynamically streamlined shapes in animals and robots enhance traversability through densely cluttered terrain.

PubMed

Li, Chen; Pullin, Andrew O; Haldane, Duncan W; Lam, Han K; Fearing, Ronald S; Full, Robert J

2015-06-22

Many animals, modern aircraft, and underwater vehicles use fusiform, streamlined body shapes that reduce fluid dynamic drag to achieve fast and effective locomotion in air and water. Similarly, numerous small terrestrial animals move through cluttered terrain where three-dimensional, multi-component obstacles like grass, shrubs, vines, and leaf litter also resist motion, but it is unknown whether their body shape plays a major role in traversal. Few ground vehicles or terrestrial robots have used body shape to more effectively traverse environments such as cluttered terrain. Here, we challenged forest-floor-dwelling discoid cockroaches (Blaberus discoidalis) possessing a thin, rounded body to traverse tall, narrowly spaced, vertical, grass-like compliant beams. Animals displayed high traversal performance (79 ± 12% probability and 3.4 ± 0.7 s time). Although we observed diverse obstacle traversal strategies, cockroaches primarily (48 ± 9% probability) used a novel roll maneuver, a form of natural parkour, allowing them to rapidly traverse obstacle gaps narrower than half their body width (2.0 ± 0.5 s traversal time). Reduction of body roundness by addition of artificial shells nearly inhibited roll maneuvers and decreased traversal performance. Inspired by this discovery, we added a thin, rounded exoskeletal shell to a legged robot with a nearly cuboidal body, common to many existing terrestrial robots. Without adding sensory feedback or changing the open-loop control, the rounded shell enabled the robot to traverse beam obstacles with gaps narrower than shell width via body roll. Such terradynamically 'streamlined' shapes can reduce terrain resistance and enhance traversability by assisting effective body reorientation via distributed mechanical feedback. Our findings highlight the need to consider body shape to improve robot mobility in real-world terrain often filled with clutter, and to develop better locomotor-ground contact models to understand interaction with 3D, multi-component terrain.

Influence of visual clutter on the effect of navigated safety inspection: a case study on elevator installation.

PubMed

Liao, Pin-Chao; Sun, Xinlu; Liu, Mei; Shih, Yu-Nien

2018-01-11

Navigated safety inspection based on task-specific checklists can increase the hazard detection rate, theoretically with interference from scene complexity. Visual clutter, a proxy of scene complexity, can theoretically impair visual search performance, but its impact on the effect of safety inspection performance remains to be explored for the optimization of navigated inspection. This research aims to explore whether the relationship between working memory and hazard detection rate is moderated by visual clutter. Based on a perceptive model of hazard detection, we: (a) developed a mathematical influence model for construction hazard detection; (b) designed an experiment to observe the performance of hazard detection rate with adjusted working memory under different levels of visual clutter, while using an eye-tracking device to observe participants' visual search processes; (c) utilized logistic regression to analyze the developed model under various visual clutter. The effect of a strengthened working memory on the detection rate through increased search efficiency is more apparent in high visual clutter. This study confirms the role of visual clutter in construction-navigated inspections, thus serving as a foundation for the optimization of inspection planning.

Two Long-Wave Infrared Spectral Polarimeters for Use in Understanding Polarization Phenomenology

DTIC Science & Technology

2002-05-01

3550 Aberdeen SE Kirtland Air Force Base, New Mexico 87117 Abstract. Spectrally varying long-wave infrared ( LWIR ) polarization measurements can be used...to identify materials and to discriminate samples from a cluttered background. Two LWIR instruments have been built and fielded by the Air Force...Research Laboratory: a multispectral LWIR imaging polarimeter (LIP) and a full-Stokes Fourier transform in- frared (FTIR) spectral polarimeter (FSP

Design Goals for Future Camouflage Systems

DTIC Science & Technology

1981-01-01

rthur D tittle Inc TABLE OF CONTENTS (continued) Page 7. Build Up the Energy Level of the Background (Clutter Enhancement, etc.) V-13 8. Decoys V-14 9...of electronic warfare, and is excluded from this project. Within each class, the following issues are addressed: * the energy field and the physics...recognized image (unlike the range/reflectivity/ motion signatures offered by most radars) and this makes camouflage even more difficult. Techniques for

Increased clutter level in echocardiography due to specular reflection

NASA Astrophysics Data System (ADS)

Fatemi, Ali; Torp, Hans; Aakhus, Svend; Rodriguez-Molares, Alfonso

2017-03-01

State-of-the-art echocardiography allows to correctly diagnose most of cardiovascular diseases. An unknown source of clutter, however, hinders the visualization of the heart in some cases. We believe this clutter is caused by the ultrasound beam being partially reflected by the ribs into the elevation direction, so that structures outside the imaging plane are displayed on top of the heart image as clutter noise. We conducted in vitro experiments in a water tank using a synthetic ventricle and pig ribs. By partially blocking the probe with the ribs in the elevation direction, objects outside the imaging plane were rendered in the B-mode image, which confirms that the ribs can behave as specular reflectors. In addition, we succeeded in reproducing clutter noise using a piece of polystyrene to simulate the reflections from the lungs. This indicates that the origin of the clutter noise in echocardiograms can be reverberation coming from the lungs via specular reflection at the ribs.

New subspace methods for ATR

NASA Astrophysics Data System (ADS)

Zhang, Peng; Peng, Jing; Sims, S. Richard F.

2005-05-01

In ATR applications, each feature is a convolution of an image with a filter. It is important to use most discriminant features to produce compact representations. We propose two novel subspace methods for dimension reduction to address limitations associated with Fukunaga-Koontz Transform (FKT). The first method, Scatter-FKT, assumes that target is more homogeneous, while clutter can be anything other than target and anywhere. Thus, instead of estimating a clutter covariance matrix, Scatter-FKT computes a clutter scatter matrix that measures the spread of clutter from the target mean. We choose dimensions along which the difference in variation between target and clutter is most pronounced. When the target follows a Gaussian distribution, Scatter-FKT can be viewed as a generalization of FKT. The second method, Optimal Bayesian Subspace, is derived from the optimal Bayesian classifier. It selects dimensions such that the minimum Bayes error rate can be achieved. When both target and clutter follow Gaussian distributions, OBS computes optimal subspace representations. We compare our methods against FKT using character image as well as IR data.

A Method for the Automatic Detection of Insect Clutter in Doppler-Radar Returns.

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

Luke,E.; Kollias, P.; Johnson, K.

2006-06-12

The accurate detection and removal of insect clutter from millimeter wavelength cloud radar (MMCR) returns is of high importance to boundary layer cloud research (e.g., Geerts et al., 2005). When only radar Doppler moments are available, it is difficult to produce a reliable screening of insect clutter from cloud returns because their distributions overlap. Hence, screening of MMCR insect clutter has historically involved a laborious manual process of cross-referencing radar moments against measurements from other collocated instruments, such as lidar. Our study looks beyond traditional radar moments to ask whether analysis of recorded Doppler spectra can serve as the basismore » for reliable, automatic insect clutter screening. We focus on the MMCR operated by the Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) program at its Southern Great Plains (SGP) facility in Oklahoma. Here, archiving of full Doppler spectra began in September 2003, and during the warmer months, a pronounced insect presence regularly introduces clutter into boundary layer returns.« less

Ground-Vegetation Clutter Affects Phyllostomid Bat Assemblage Structure in Lowland Amazonian Forest.

PubMed

Marciente, Rodrigo; Bobrowiec, Paulo Estefano D; Magnusson, William E

2015-01-01

Vegetation clutter is a limiting factor for bats that forage near ground level, and may determine the distribution of species and guilds. However, many studies that evaluated the effects of vegetation clutter on bats have used qualitative descriptions rather than direct measurements of vegetation density. Moreover, few studies have evaluated the effect of vegetation clutter on a regional scale. Here, we evaluate the influence of the physical obstruction of vegetation on phyllostomid-bat assemblages along a 520 km transect in continuous Amazonian forest. We sampled bats using mist nets in eight localities during 80 nights (3840 net-hours) and estimated the ground-vegetation density with digital photographs. The total number of species, number of animalivorous species, total number of frugivorous species, number of understory frugivorous species, and abundance of canopy frugivorous bats were negatively associated with vegetation clutter. The bat assemblages showed a nested structure in relation to degree of clutter, with animalivorous and understory frugivorous bats distributed throughout the vegetation-clutter gradient, while canopy frugivores were restricted to sites with more open vegetation. The species distribution along the gradient of vegetation clutter was not closely associated with wing morphology, but aspect ratio and wing load differed between frugivores and animalivores. Vegetation structure plays an important role in structuring assemblages of the bats at the regional scale by increasing beta diversity between sites. Differences in foraging strategy and diet of the guilds seem to have contributed more to the spatial distribution of bats than the wing characteristics of the species alone.

Matching by linear programming and successive convexification.

PubMed

Jiang, Hao; Drew, Mark S; Li, Ze-Nian

2007-06-01

We present a novel convex programming scheme to solve matching problems, focusing on the challenging problem of matching in a large search range and with cluttered background. Matching is formulated as metric labeling with L1 regularization terms, for which we propose a novel linear programming relaxation method and an efficient successive convexification implementation. The unique feature of the proposed relaxation scheme is that a much smaller set of basis labels is used to represent the original label space. This greatly reduces the size of the searching space. A successive convexification scheme solves the labeling problem in a coarse to fine manner. Importantly, the original cost function is reconvexified at each stage, in the new focus region only, and the focus region is updated so as to refine the searching result. This makes the method well-suited for large label set matching. Experiments demonstrate successful applications of the proposed matching scheme in object detection, motion estimation, and tracking.

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

Young, Derek P.; Jacklin, Neil; Punnoose, Ratish J.

Time-reversal is a wave focusing technique that makes use of the reciprocity of wireless propagation channels. It works particularly well in a cluttered environment with associated multipath reflection. This technique uses the multipath in the environment to increase focusing ability. Time-reversal can also be used to null signals, either to reduce unintentional interference or to prevent eavesdropping. It does not require controlled geometric placement of the transmit antennas. Unlike existing techniques it can work without line-of-sight. We have explored the performance of time-reversal focusing in a variety of simulated environments. We have also developed new algorithms to simultaneously focus atmore » a location while nulling at an eavesdropper location. We have experimentally verified these techniques in a realistic cluttered environment.« less

Chinese Herbal Medicine Image Recognition and Retrieval by Convolutional Neural Network

PubMed Central

Sun, Xin; Qian, Huinan

2016-01-01

Chinese herbal medicine image recognition and retrieval have great potential of practical applications. Several previous studies have focused on the recognition with hand-crafted image features, but there are two limitations in them. Firstly, most of these hand-crafted features are low-level image representation, which is easily affected by noise and background. Secondly, the medicine images are very clean without any backgrounds, which makes it difficult to use in practical applications. Therefore, designing high-level image representation for recognition and retrieval in real world medicine images is facing a great challenge. Inspired by the recent progress of deep learning in computer vision, we realize that deep learning methods may provide robust medicine image representation. In this paper, we propose to use the Convolutional Neural Network (CNN) for Chinese herbal medicine image recognition and retrieval. For the recognition problem, we use the softmax loss to optimize the recognition network; then for the retrieval problem, we fine-tune the recognition network by adding a triplet loss to search for the most similar medicine images. To evaluate our method, we construct a public database of herbal medicine images with cluttered backgrounds, which has in total 5523 images with 95 popular Chinese medicine categories. Experimental results show that our method can achieve the average recognition precision of 71% and the average retrieval precision of 53% over all the 95 medicine categories, which are quite promising given the fact that the real world images have multiple pieces of occluded herbal and cluttered backgrounds. Besides, our proposed method achieves the state-of-the-art performance by improving previous studies with a large margin. PMID:27258404

Estimating the delay-Doppler of target echo in a high clutter underwater environment using wideband linear chirp signals: Evaluation of performance with experimental data.

PubMed

Yu, Ge; Yang, T C; Piao, Shengchun

2017-10-01

A chirp signal is a signal with linearly varying instantaneous frequency over the signal bandwidth, also known as a linear frequency modulated (LFM) signal. It is widely used in communication, radar, active sonar, and other applications due to its Doppler tolerance property in signal detection using the matched filter (MF) processing. Modern sonar uses high-gain, wideband signals to improve the signal to reverberation ratio. High gain implies a high product of the signal bandwidth and duration. However, wideband and/or long duration LFM signals are no longer Doppler tolerant. The shortcoming of the standard MF processing is loss of performance, and bias in range estimation. This paper uses the wideband ambiguity function and the fractional Fourier transform method to estimate the target velocity and restore the performance. Target velocity or Doppler provides a clue for differentiating the target from the background reverberation and clutter. The methods are applied to simulated and experimental data.

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.

Background characterization techniques for target detection using scene metrics and pattern recognition

NASA Astrophysics Data System (ADS)

Noah, Paul V.; Noah, Meg A.; Schroeder, John W.; Chernick, Julian A.

1990-09-01

The U.S. Army has a requirement to develop systems for the detection and identification of ground targets in a clutter environment. Autonomous Homing Munitions (AHM) using infrared, visible, millimeter wave and other sensors are being investigated for this application. Advanced signal processing and computational approaches using pattern recognition and artificial intelligence techniques combined with multisensor data fusion have the potential to meet the Army's requirements for next generation ARM.

The pulse-pair algorithm as a robust estimator of turbulent weather spectral parameters using airborne pulse Doppler radar

NASA Technical Reports Server (NTRS)

Baxa, Ernest G., Jr.; Lee, Jonggil

1991-01-01

The pulse pair method for spectrum parameter estimation is commonly used in pulse Doppler weather radar signal processing since it is economical to implement and can be shown to be a maximum likelihood estimator. With the use of airborne weather radar for windshear detection, the turbulent weather and strong ground clutter return spectrum differs from that assumed in its derivation, so the performance robustness of the pulse pair technique must be understood. Here, the effect of radar system pulse to pulse phase jitter and signal spectrum skew on the pulse pair algorithm performance is discussed. Phase jitter effect may be significant when the weather return signal to clutter ratio is very low and clutter rejection filtering is attempted. The analysis can be used to develop design specifications for airborne radar system phase stability. It is also shown that the weather return spectrum skew can cause a significant bias in the pulse pair mean windspeed estimates, and that the poly pulse pair algorithm can reduce this bias. It is suggested that use of a spectrum mode estimator may be more appropriate in characterizing the windspeed within a radar range resolution cell for detection of hazardous windspeed gradients.

Ground-Vegetation Clutter Affects Phyllostomid Bat Assemblage Structure in Lowland Amazonian Forest

PubMed Central

Marciente, Rodrigo; Bobrowiec, Paulo Estefano D.; Magnusson, William E.

2015-01-01

Vegetation clutter is a limiting factor for bats that forage near ground level, and may determine the distribution of species and guilds. However, many studies that evaluated the effects of vegetation clutter on bats have used qualitative descriptions rather than direct measurements of vegetation density. Moreover, few studies have evaluated the effect of vegetation clutter on a regional scale. Here, we evaluate the influence of the physical obstruction of vegetation on phyllostomid-bat assemblages along a 520 km transect in continuous Amazonian forest. We sampled bats using mist nets in eight localities during 80 nights (3840 net-hours) and estimated the ground-vegetation density with digital photographs. The total number of species, number of animalivorous species, total number of frugivorous species, number of understory frugivorous species, and abundance of canopy frugivorous bats were negatively associated with vegetation clutter. The bat assemblages showed a nested structure in relation to degree of clutter, with animalivorous and understory frugivorous bats distributed throughout the vegetation-clutter gradient, while canopy frugivores were restricted to sites with more open vegetation. The species distribution along the gradient of vegetation clutter was not closely associated with wing morphology, but aspect ratio and wing load differed between frugivores and animalivores. Vegetation structure plays an important role in structuring assemblages of the bats at the regional scale by increasing beta diversity between sites. Differences in foraging strategy and diet of the guilds seem to have contributed more to the spatial distribution of bats than the wing characteristics of the species alone. PMID:26066654

A Track Initiation Method for the Underwater Target Tracking Environment

NASA Astrophysics Data System (ADS)

Li, Dong-dong; Lin, Yang; Zhang, Yao

2018-04-01

A novel efficient track initiation method is proposed for the harsh underwater target tracking environment (heavy clutter and large measurement errors): track splitting, evaluating, pruning and merging method (TSEPM). Track initiation demands that the method should determine the existence and initial state of a target quickly and correctly. Heavy clutter and large measurement errors certainly pose additional difficulties and challenges, which deteriorate and complicate the track initiation in the harsh underwater target tracking environment. There are three primary shortcomings for the current track initiation methods to initialize a target: (a) they cannot eliminate the turbulences of clutter effectively; (b) there may be a high false alarm probability and low detection probability of a track; (c) they cannot estimate the initial state for a new confirmed track correctly. Based on the multiple hypotheses tracking principle and modified logic-based track initiation method, in order to increase the detection probability of a track, track splitting creates a large number of tracks which include the true track originated from the target. And in order to decrease the false alarm probability, based on the evaluation mechanism, track pruning and track merging are proposed to reduce the false tracks. TSEPM method can deal with the track initiation problems derived from heavy clutter and large measurement errors, determine the target's existence and estimate its initial state with the least squares method. What's more, our method is fully automatic and does not require any kind manual input for initializing and tuning any parameter. Simulation results indicate that our new method improves significantly the performance of the track initiation in the harsh underwater target tracking environment.

Logarithmic r-θ mapping for hybrid optical neural network filter for multiple objects recognition within cluttered scenes

NASA Astrophysics Data System (ADS)

Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.; Birch, Phil M.

2009-04-01

θThe window unit in the design of the complex logarithmic r-θ mapping for hybrid optical neural network filter can allow multiple objects of the same class to be detected within the input image. Additionally, the architecture of the neural network unit of the complex logarithmic r-θ mapping for hybrid optical neural network filter becomes attractive for accommodating the recognition of multiple objects of different classes within the input image by modifying the output layer of the unit. We test the overall filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. Logarithmic r-θ mapping for hybrid optical neural network filter is shown to exhibit with a single pass over the input data simultaneously in-plane rotation, out-of-plane rotation, scale, log r-θ map translation and shift invariance, and good clutter tolerance by recognizing correctly the different objects within the cluttered scenes. We record in our results additional extracted information from the cluttered scenes about the objects' relative position, scale and in-plane rotation.

Effect of the Temperature-Emissivity Contrast on the Chemical Signal for Gas Plume Detection Using Thermal Image Data

PubMed Central

Walsh, Stephen; Chilton, Larry; Tardiff, Mark; Metoyer, Candace

2008-01-01

Detecting and identifying weak gaseous plumes using thermal imaging data is complicated by many factors. These include variability due to atmosphere, ground and plume temperature, and background clutter. This paper presents an analysis of one formulation of the physics-based radiance model, which describes at-sensor observed radiance. The background emissivity and plume/ground temperatures are isolated, and their effects on chemical signal are described. This analysis shows that the plume's physical state, emission or absorption, is directly dependent on the background emissivity and plume/ground temperatures. It then describes what conditions on the background emissivity and plume/ground temperatures have inhibiting or amplifying effects on the chemical signal. These claims are illustrated by analyzing synthetic hyperspectral imaging data with the adaptive matched filter using two chemicals and three distinct background emissivities. PMID:27873881

Saliency Detection on Light Field.

PubMed

Li, Nianyi; Ye, Jinwei; Ji, Yu; Ling, Haibin; Yu, Jingyi

2017-08-01

Existing saliency detection approaches use images as inputs and are sensitive to foreground/background similarities, complex background textures, and occlusions. We explore the problem of using light fields as input for saliency detection. Our technique is enabled by the availability of commercial plenoptic cameras that capture the light field of a scene in a single shot. We show that the unique refocusing capability of light fields provides useful focusness, depths, and objectness cues. We further develop a new saliency detection algorithm tailored for light fields. To validate our approach, we acquire a light field database of a range of indoor and outdoor scenes and generate the ground truth saliency map. Experiments show that our saliency detection scheme can robustly handle challenging scenarios such as similar foreground and background, cluttered background, complex occlusions, etc., and achieve high accuracy and robustness.

Global Infrasound Association Based on Probabilistic Clutter Categorization

NASA Astrophysics Data System (ADS)

Arora, N. S.; Mialle, P.

2015-12-01

The IDC collects waveforms from a global network of infrasound sensors maintained by the IMS, and automatically detects signal onsets and associates them to form event hypotheses. However, a large number of signal onsets are due to local clutter sources such as microbaroms (from standing waves in the oceans), waterfalls, dams, gas flares, surf (ocean breaking waves) etc. These sources are either too diffuse or too local to form events. Worse still, the repetitive nature of this clutter leads to a large number of false event hypotheses due to the random matching of clutter at multiple stations. Previous studies, for example [1], have worked on categorization of clutter using long term trends on detection azimuth, frequency, and amplitude at each station. In this work we continue the same line of reasoning to build a probabilistic model of clutter that is used as part of NET-VISA [2], a Bayesian approach to network processing. The resulting model is a fusion of seismic, hydro-acoustic and infrasound processing built on a unified probabilistic framework. Notes: The attached figure shows all the unassociated arrivals detected at IMS station I09BR for 2012 distributed by azimuth and center frequency. (The title displays the bandwidth of the kernel density estimate along the azimuth and frequency dimensions).This plot shows multiple micro-barom sources as well as other sources of infrasound clutter. A diverse clutter-field such as this one is quite common for most IMS infrasound stations, and it highlights the dangers of forming events without due consideration of this source of noise. References: [1] Infrasound categorization Towards a statistics-based approach. J. Vergoz, P. Gaillard, A. Le Pichon, N. Brachet, and L. Ceranna. ITW 2011 [2] NET-VISA: Network Processing Vertically Integrated Seismic Analysis. N. S. Arora, S. Russell, and E. Sudderth. BSSA 2013.

Clutter elimination for deep clinical optoacoustic imaging using localised vibration tagging (LOVIT)☆

PubMed Central

Jaeger, Michael; Bamber, Jeffrey C.; Frenz, Martin

2013-01-01

This paper investigates a novel method which allows clutter elimination in deep optoacoustic imaging. Clutter significantly limits imaging depth in clinical optoacoustic imaging, when irradiation optics and ultrasound detector are integrated in a handheld probe for flexible imaging of the human body. Strong optoacoustic transients generated at the irradiation site obscure weak signals from deep inside the tissue, either directly by propagating towards the probe, or via acoustic scattering. In this study we demonstrate that signals of interest can be distinguished from clutter by tagging them at the place of origin with localised tissue vibration induced by the acoustic radiation force in a focused ultrasonic beam. We show phantom results where this technique allowed almost full clutter elimination and thus strongly improved contrast for deep imaging. Localised vibration tagging by means of acoustic radiation force is especially promising for integration into ultrasound systems that already have implemented radiation force elastography. PMID:25302147

Characterisation of High Grazing Angle X-band Sea-clutter Doppler Spectra

DTIC Science & Technology

2013-08-01

0397 2 Background The ocean surface is a highly complex dynamical system and relating Doppler spectra to surface conditions is a difficult problem...1966] then extended this theory to water and classified it as a ‘slightly rough’ surface. He showed that the scattering elements of primary importance...incidence field. This is the definition for the Bragg water -wave propagation number defined in the spatial frequency domain as kw = 2k0 cos θ, where

Dual-energy contrast enhanced digital breast tomosynthesis: concept, method, and evaluation on phantoms

NASA Astrophysics Data System (ADS)

Puong, Sylvie; Patoureaux, Fanny; Iordache, Razvan; Bouchevreau, Xavier; Muller, Serge

2007-03-01

In this paper, we present the development of dual-energy Contrast-Enhanced Digital Breast Tomosynthesis (CEDBT). A method to produce background clutter-free slices from a set of low and high-energy projections is introduced, along with a scheme for the determination of the optimal low and high-energy techniques. Our approach consists of a dual-energy recombination of the projections, with an algorithm that has proven its performance in Contrast-Enhanced Digital Mammography1 (CEDM), followed by an iterative volume reconstruction. The aim is to eliminate the anatomical background clutter and to reconstruct slices where the gray level is proportional to the local iodine volumetric concentration. Optimization of the low and high-energy techniques is performed by minimizing the total glandular dose to reach a target iodine Signal Difference to Noise Ratio (SDNR) in the slices. In this study, we proved that this optimization could be done on the projections, by consideration of the SDNR in the projections instead of the SDNR in the slices, and verified this with phantom measurements. We also discuss some limitations of dual-energy CEDBT, due to the restricted angular range for the projection views, and to the presence of scattered radiation. Experiments on textured phantoms with iodine inserts were conducted to assess the performance of dual-energy CEDBT. Texture contrast was nearly completely removed and the iodine signal was enhanced in the slices.

A unified framework for gesture recognition and spatiotemporal gesture segmentation.

PubMed

Alon, Jonathan; Athitsos, Vassilis; Yuan, Quan; Sclaroff, Stan

2009-09-01

Within the context of hand gesture recognition, spatiotemporal gesture segmentation is the task of determining, in a video sequence, where the gesturing hand is located and when the gesture starts and ends. Existing gesture recognition methods typically assume either known spatial segmentation or known temporal segmentation, or both. This paper introduces a unified framework for simultaneously performing spatial segmentation, temporal segmentation, and recognition. In the proposed framework, information flows both bottom-up and top-down. A gesture can be recognized even when the hand location is highly ambiguous and when information about when the gesture begins and ends is unavailable. Thus, the method can be applied to continuous image streams where gestures are performed in front of moving, cluttered backgrounds. The proposed method consists of three novel contributions: a spatiotemporal matching algorithm that can accommodate multiple candidate hand detections in every frame, a classifier-based pruning framework that enables accurate and early rejection of poor matches to gesture models, and a subgesture reasoning algorithm that learns which gesture models can falsely match parts of other longer gestures. The performance of the approach is evaluated on two challenging applications: recognition of hand-signed digits gestured by users wearing short-sleeved shirts, in front of a cluttered background, and retrieval of occurrences of signs of interest in a video database containing continuous, unsegmented signing in American Sign Language (ASL).

Research Topics on Cluttered Environments Interrogation and Propagation

DTIC Science & Technology

2014-11-04

propagation in random and complex media and looked at specific applications associated with imaging and communication through a cluttered medium...imaging and communication schemes. We have used the results on the fourth moment to analyze wavefront correction schemes and obtained novel...and com- plex media and looked at specific applications associated with imaging and communication through a cluttered medium. The main new

Limits to Clutter Cancellation in Multi-Aperture GMTI Data

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

Doerry, Armin W.; Bickel, Douglas L.

2015-03-01

Multi-aperture or multi-subaperture antennas are fundamental to Ground Moving Target Indicator (GMTI) radar systems in order to detect slow-moving targets with Doppler characteristics similar to clutter. Herein we examine the performance of several subaperture architectures for their clutter cancelling performance. Significantly, more antenna phase centers isn’t always better, and in fact is sometimes worse, for detecting targets.

Modeling visual clutter perception using proto-object segmentation

PubMed Central

Yu, Chen-Ping; Samaras, Dimitris; Zelinsky, Gregory J.

2014-01-01

We introduce the proto-object model of visual clutter perception. This unsupervised model segments an image into superpixels, then merges neighboring superpixels that share a common color cluster to obtain proto-objects—defined here as spatially extended regions of coherent features. Clutter is estimated by simply counting the number of proto-objects. We tested this model using 90 images of realistic scenes that were ranked by observers from least to most cluttered. Comparing this behaviorally obtained ranking to a ranking based on the model clutter estimates, we found a significant correlation between the two (Spearman's ρ = 0.814, p < 0.001). We also found that the proto-object model was highly robust to changes in its parameters and was generalizable to unseen images. We compared the proto-object model to six other models of clutter perception and demonstrated that it outperformed each, in some cases dramatically. Importantly, we also showed that the proto-object model was a better predictor of clutter perception than an actual count of the number of objects in the scenes, suggesting that the set size of a scene may be better described by proto-objects than objects. We conclude that the success of the proto-object model is due in part to its use of an intermediate level of visual representation—one between features and objects—and that this is evidence for the potential importance of a proto-object representation in many common visual percepts and tasks. PMID:24904121

Bistatic Clutter Phenomenological Measurement/Model Development

DTIC Science & Technology

1988-05-01

The objectives of this program are to provide technical analyses, test planning, and participation in the collection of near- simultaneous bistatic and...realistic clutter environment 2. Collect near- simultaneous monostatic and bistatic clutter data characteristic of relatively well-behaved terrain. The...FROM * waypoint at the same time and on the proper heading but this is not critical. The next waypoint or LINEUP waypoint is the first point where

Hierarchical streamline bundles.

PubMed

Yu, Hongfeng; Wang, Chaoli; Shene, Ching-Kuang; Chen, Jacqueline H

2012-08-01

Effective 3D streamline placement and visualization play an essential role in many science and engineering disciplines. The main challenge for effective streamline visualization lies in seed placement, i.e., where to drop seeds and how many seeds should be placed. Seeding too many or too few streamlines may not reveal flow features and patterns either because it easily leads to visual clutter in rendering or it conveys little information about the flow field. Not only does the number of streamlines placed matter, their spatial relationships also play a key role in understanding the flow field. Therefore, effective flow visualization requires the streamlines to be placed in the right place and in the right amount. This paper introduces hierarchical streamline bundles, a novel approach to simplifying and visualizing 3D flow fields defined on regular grids. By placing seeds and generating streamlines according to flow saliency, we produce a set of streamlines that captures important flow features near critical points without enforcing the dense seeding condition. We group spatially neighboring and geometrically similar streamlines to construct a hierarchy from which we extract streamline bundles at different levels of detail. Streamline bundles highlight multiscale flow features and patterns through clustered yet not cluttered display. This selective visualization strategy effectively reduces visual clutter while accentuating visual foci, and therefore is able to convey the desired insight into the flow data.

Investigation of an EMI sensor for detection of large metallic objects in the presence of metallic clutter

NASA Astrophysics Data System (ADS)

Black, Christopher; McMichael, Ian; Riggs, Lloyd

2005-06-01

Electromagnetic induction (EMI) sensors and magnetometers have successfully detected surface laid, buried, and visually obscured metallic objects. Potential military activities could require detection of these objects at some distance from a moving vehicle in the presence of metallic clutter. Results show that existing EMI sensors have limited range capabilities and suffer from false alarms due to clutter. This paper presents results of an investigation of an EMI sensor designed for detecting large metallic objects on a moving platform in a high clutter environment. The sensor was developed by the U.S. Army RDECOM CERDEC NVESD in conjunction with the Johns Hopkins University Applied Physics Laboratory.

Land mine detection using multispectral image fusion

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

Clark, G.A.; Sengupta, S.K.; Aimonetti, W.D.

1995-03-29

Our system fuses information contained in registered images from multiple sensors to reduce the effects of clutter and improve the ability to detect surface and buried land mines. The sensor suite currently consists of a camera that acquires images in six bands (400nm, 500nm, 600nm, 700nm, 800nm and 900nm). Past research has shown that it is extremely difficult to distinguish land mines from background clutter in images obtained from a single sensor. It is hypothesized, however, that information fused from a suite of various sensors is likely to provide better detection reliability, because the suite of sensors detects a varietymore » of physical properties that are more separable in feature space. The materials surrounding the mines can include natural materials (soil, rocks, foliage, water, etc.) and some artifacts. We use a supervised learning pattern recognition approach to detecting the metal and plastic land mines. The overall process consists of four main parts: Preprocessing, feature extraction, feature selection, and classification. These parts are used in a two step process to classify a subimage. We extract features from the images, and use feature selection algorithms to select only the most important features according to their contribution to correct detections. This allows us to save computational complexity and determine which of the spectral bands add value to the detection system. The most important features from the various sensors are fused using a supervised learning pattern classifier (the probabilistic neural network). We present results of experiments to detect land mines from real data collected from an airborne platform, and evaluate the usefulness of fusing feature information from multiple spectral bands.« less

Ultra-wideband horn antenna with abrupt radiator

DOEpatents

McEwan, Thomas E.

1998-01-01

An ultra-wideband horn antenna transmits and receives impulse waveforms for short-range radars and impulse time-of flight systems. The antenna reduces or eliminates various sources of close-in radar clutter, including pulse dispersion and ringing, sidelobe clutter, and feedline coupling into the antenna. Dispersion is minimized with an abrupt launch point radiator element; sidelobe and feedline coupling are minimized by recessing the radiator into a metallic horn. Low frequency cut-off associated with a horn is extended by configuring the radiator drive impedance to approach a short circuit at low frequencies. A tapered feed plate connects at one end to a feedline, and at the other end to a launcher plate which is mounted to an inside wall of the horn. The launcher plate and feed plate join at an abrupt edge which forms the single launch point of the antenna.

Underwater Intruder Detection Sonar for Harbour Protection: State of the Art Review and Implications

DTIC Science & Technology

2006-10-01

intruder would appear as a small moving “ blob ” of energetic echo in the echograph, and the operator could judge whether the contact is a threat that calls...visually then as a small fluctuating “ blob ” against a fluctuating background of sound clutter and reverberation, making it difficult to visually...4. Non-random false alarms caused by genuine underwater contacts that happened not to be intruders—by large fish , or schools of fish , or marine

Co-training Framework of Generative and Disciminative Trackers with Partial Occlusion Handling

DTIC Science & Technology

2011-01-01

ARO W911NF-06-1-0094. The first author was also supported by the Vietnam Education Foundation. We thank Zdenek Kalal for his help with the P-N Tracker...handling challenging situations with cluttered background. Recently, Kalal et al. [11] proposed the P-N Tracker us- ing positive and negative constraints to...Vietnam Education Foundation. We thank Zdenek Kalal for his help with the P-N Tracker [11]. References [1] A. Adam, E. Rivlin, and I. Shimshoni. Robust

On Adaptive Cell-Averaging CFAR (Constant False-Alarm Rate) Radar Signal Detection

DTIC Science & Technology

1987-10-01

SIICILE COPY 4 F FInI Tedwill Rlmrt to October 197 00 C\\JT ON ADAPTIVE CELL-AVERA81NG CFAR I RADAR SIGNAL DETECTION Syracuse University Mourud krket...NY 13441-5700 ELEMENT NO. NO. NO ACCESSION NO. 11. TITLE (Include Security Classification) 61102F 2’ 05 J8 PD - ON ADAPTIVE CELL-AVERAGING CFAR RADAR... CFAR ). One approach to adaptive detection in nonstationary noise and clutter background is to compare the processed target signal to an adaptive

Counter Unmanned Aerial Systems Testing: Evaluation of VIS SWIR MWIR and LWIR passive imagers.

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

Birch, Gabriel Carlisle; Woo, Bryana Lynn

This report contains analysis of unmanned aerial systems as imaged by visible, short-wave infrared, mid-wave infrared, and long-wave infrared passive devices. Testing was conducted at the Nevada National Security Site (NNSS) during the week of August 15, 2016. Target images in all spectral bands are shown and contrast versus background is reported. Calculations are performed to determine estimated pixels-on-target for detection and assessment levels, and the number of pixels needed to cover a hemisphere for detection or assessment at defined distances. Background clutter challenges are qualitatively discussed for different spectral bands, and low contrast scenarios are highlighted for long-wave infraredmore » imagers.« less

51. WEST ACROSS CLUTTER TO WEST WALL OF WELLSERVICE SHED ...

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

51. WEST ACROSS CLUTTER TO WEST WALL OF WELL-SERVICE SHED ADDITION ON REAR OF FACTORY BUILDING. AT LOWER RIGHT FOREGROUND IS 1960S PICKUP TRUCK, THE LAST MOTOR VEHICLE USED IN WELL SERVICE BY THE KREGEL WINDMILL COMPANY. MOST OF THE OBJECTS VISIBLE IN THIS VIEW ARE CLUTTER NOT RELATED TO THE WELL SERVICE BUSINESS. - Kregel Windmill Company Factory, 1416 Central Avenue, Nebraska City, Otoe County, NE

Handheld Sensor for UXO Discrimination:

DTIC Science & Technology

2006-06-01

between buried UXO and clutter. This project demonstrated the use of commercially available technology (Geonics EM61-HH handheld metal detector ) for...determine whether each target was UXO or clutter. The Geonics EM61-HH handheld metal detector is a pulsed electromagnetic induction (EMI) sensor. The...processing, the EM61-HH handheld metal detector can 2 be used in a cued identification mode to reliably discriminate between buried UXO and clutter

Active Listening in a Bat Cocktail Party: Adaptive Echolocation and Flight Behaviors of Big Brown Bats, Eptesicus fuscus, Foraging in a Cluttered Acoustic Environment.

PubMed

Warnecke, Michaela; Chiu, Chen; Engelberg, Jonathan; Moss, Cynthia F

2015-09-01

In their natural environment, big brown bats forage for small insects in open spaces, as well as in vegetation and in the presence of acoustic clutter. While searching and hunting for prey, bats experience sonar interference, not only from densely cluttered environments, but also from calls of conspecifics foraging in close proximity. Previous work has shown that when two bats compete for a single prey item in a relatively open environment, one of the bats may go silent for extended periods of time, which can serve to minimize sonar interference between conspecifics. Additionally, pairs of big brown bats have been shown to adjust frequency characteristics of their vocalizations to avoid acoustic interference in echo processing. In this study, we extended previous work by examining how the presence of conspecifics and environmental clutter influence the bat's echolocation behavior. By recording multichannel audio and video data of bats engaged in insect capture in open and cluttered spaces, we quantified the bats' vocal and flight behaviors. Big brown bats flew individually and in pairs in an open and cluttered room, and the results of this study shed light on the different strategies that this species employs to negotiate a complex and dynamic environment. © 2015 S. Karger AG, Basel.

Transponder data processing methods and systems

DOEpatents

Axline, Robert M.

2003-06-10

This invention is a radar/tag system where pulses from a radar cause a tag (or transponder) to respond to the radar. The radar, along with its conventional pulse transmissions, sends a reference signal to the tag. The tag recovers the reference signal and uses it to shift the center frequency of the received radar pulse to a different frequency. This shift causes the frequencies of the tag response pulses to be disjoint from those of the transmit pulse. In this way, radar clutter can be eliminated from the tag responses. The radar predicts, to within a small Doppler offset, the center frequency of tag response pulses. The radar can create synthetic-aperture-radar-like images and moving-target-indicator-radar-like maps containing the signature of the tag against a background of thermal noise and greatly attenuated radar clutter. The radar can geolocate the tag precisely and accurately (to within better than one meter of error). The tag can encode status and environmental data onto its response pulses, and the radar can receive and decode this information.

Background adaptive division filtering for hand-held ground penetrating radar

NASA Astrophysics Data System (ADS)

Lee, Matthew A.; Anderson, Derek T.; Ball, John E.; White, Julie L.

2016-05-01

The challenge in detecting explosive hazards is that there are multiple types of targets buried at different depths in a highlycluttered environment. A wide array of target and clutter signatures exist, which makes detection algorithm design difficult. Such explosive hazards are typically deployed in past and present war zones and they pose a grave threat to the safety of civilians and soldiers alike. This paper focuses on a new image enhancement technique for hand-held ground penetrating radar (GPR). Advantages of the proposed technique is it runs in real-time and it does not require the radar to remain at a constant distance from the ground. Herein, we evaluate the performance of the proposed technique using data collected from a U.S. Army test site, which includes targets with varying amounts of metal content, placement depths, clutter and times of day. Receiver operating characteristic (ROC) curve-based results are presented for the detection of shallow, medium and deeply buried targets. Preliminary results are very encouraging and they demonstrate the usefulness of the proposed filtering technique.

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.

Shallow Water UXO Technology Demonstration Site Scoring Record Number 5 (NAEVA/XTECH, EM61 MKII)

DTIC Science & Technology

2007-01-01

Clutter items fit into one of three categories: ferrous, nonferrous , and mixed metals . The ferrous and nonferrous items have been further...fragments that have both a ferrous and nonferrous component and could reasonably be encountered in a range area. The mixed- metals clutter was placed...components; however, industrial scrap metal and cultural items are present as well. The mixed- metals clutter is composed of scrap ordnance items or

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.

Dysfluencies in the speech of adults with intellectual disabilities and reported speech difficulties.

PubMed

Coppens-Hofman, Marjolein C; Terband, Hayo R; Maassen, Ben A M; van Schrojenstein Lantman-De Valk, Henny M J; van Zaalen-op't Hof, Yvonne; Snik, Ad F M

2013-01-01

In individuals with an intellectual disability, speech dysfluencies are more common than in the general population. In clinical practice, these fluency disorders are generally diagnosed and treated as stuttering rather than cluttering. To characterise the type of dysfluencies in adults with intellectual disabilities and reported speech difficulties with an emphasis on manifestations of stuttering and cluttering, which distinction is to help optimise treatment aimed at improving fluency and intelligibility. The dysfluencies in the spontaneous speech of 28 adults (18-40 years; 16 men) with mild and moderate intellectual disabilities (IQs 40-70), who were characterised as poorly intelligible by their caregivers, were analysed using the speech norms for typically developing adults and children. The speakers were subsequently assigned to different diagnostic categories by relating their resulting dysfluency profiles to mean articulatory rate and articulatory rate variability. Twenty-two (75%) of the participants showed clinically significant dysfluencies, of which 21% were classified as cluttering, 29% as cluttering-stuttering and 25% as clear cluttering at normal articulatory rate. The characteristic pattern of stuttering did not occur. The dysfluencies in the speech of adults with intellectual disabilities and poor intelligibility show patterns that are specific for this population. Together, the results suggest that in this specific group of dysfluent speakers interventions should be aimed at cluttering rather than stuttering. The reader will be able to (1) describe patterns of dysfluencies in the speech of adults with intellectual disabilities that are specific for this group of people, (2) explain that a high rate of dysfluencies in speech is potentially a major determiner of poor intelligibility in adults with ID and (3) describe suggestions for intervention focusing on cluttering rather than stuttering in dysfluent speakers with ID. Copyright © 2013 Elsevier Inc. All rights reserved.

Echolocating Big Brown Bats, Eptesicus fuscus, Modulate Pulse Intervals to Overcome Range Ambiguity in Cluttered Surroundings

PubMed Central

Wheeler, Alyssa R.; Fulton, Kara A.; Gaudette, Jason E.; Simmons, Ryan A.; Matsuo, Ikuo; Simmons, James A.

2016-01-01

Big brown bats (Eptesicus fuscus) emit trains of brief, wideband frequency-modulated (FM) echolocation sounds and use echoes of these sounds to orient, find insects, and guide flight through vegetation. They are observed to emit sounds that alternate between short and long inter-pulse intervals (IPIs), forming sonar sound groups. The occurrence of these strobe groups has been linked to flight in cluttered acoustic environments, but how exactly bats use sonar sound groups to orient and navigate is still a mystery. Here, the production of sound groups during clutter navigation was examined. Controlled flight experiments were conducted where the proximity of the nearest obstacles was systematically decreased while the extended scene was kept constant. Four bats flew along a corridor of varying widths (100, 70, and 40 cm) bounded by rows of vertically hanging plastic chains while in-flight echolocation calls were recorded. Bats shortened their IPIs for more rapid spatial sampling and also grouped their sounds more tightly when flying in narrower corridors. Bats emitted echolocation calls with progressively shorter IPIs over the course of a flight, and began their flights by emitting shorter starting IPI calls when clutter was denser. The percentage of sound groups containing 3 or more calls increased with increasing clutter proximity. Moreover, IPI sequences having internal structure become more pronounced when corridor width narrows. A novel metric for analyzing the temporal organization of sound sequences was developed, and the results indicate that the time interval between echolocation calls depends heavily on the preceding time interval. The occurrence of specific IPI patterns were dependent upon clutter, which suggests that sonar sound grouping may be an adaptive strategy for coping with pulse-echo ambiguity in cluttered surroundings. PMID:27445723

Study of Command and Control (C&C) Structures on the Employment of Collaborative Engagement Capability (CEC) on Land Systems

DTIC Science & Technology

2012-09-01

especially the sophisticated sea- skimming missiles that take advantage of the earth’s spherical nature as well the “sea clutter” that obstructs...radar capabilities such as the radar scanning range and ability to filter sea clutter to detect sea- skimming missile. The longer the range and the more...sea clutter Compact, cluttered with buildings, residents Common Threats Long-range sea skimming missiles Projectiles Platform Large platform

Iterative nonlinear joint transform correlation for the detection of objects in cluttered scenes

NASA Astrophysics Data System (ADS)

Haist, Tobias; Tiziani, Hans J.

1999-03-01

An iterative correlation technique with digital image processing in the feedback loop for the detection of small objects in cluttered scenes is proposed. A scanning aperture is combined with the method in order to improve the immunity against noise and clutter. Multiple reference objects or different views of one object are processed in parallel. We demonstrate the method by detecting a noisy and distorted face in a crowd with a nonlinear joint transform correlator.

Parametric Coding of the Size and Clutter of Natural Scenes in the Human Brain

PubMed Central

Park, Soojin; Konkle, Talia; Oliva, Aude

2015-01-01

Estimating the size of a space and its degree of clutter are effortless and ubiquitous tasks of moving agents in a natural environment. Here, we examine how regions along the occipital–temporal lobe respond to pictures of indoor real-world scenes that parametrically vary in their physical “size” (the spatial extent of a space bounded by walls) and functional “clutter” (the organization and quantity of objects that fill up the space). Using a linear regression model on multivoxel pattern activity across regions of interest, we find evidence that both properties of size and clutter are represented in the patterns of parahippocampal cortex, while the retrosplenial cortex activity patterns are predominantly sensitive to the size of a space, rather than the degree of clutter. Parametric whole-brain analyses confirmed these results. Importantly, this size and clutter information was represented in a way that generalized across different semantic categories. These data provide support for a property-based representation of spaces, distributed across multiple scene-selective regions of the cerebral cortex. PMID:24436318

Maximum-likelihood spectral estimation and adaptive filtering techniques with application to airborne Doppler weather radar. Thesis Technical Report No. 20

NASA Technical Reports Server (NTRS)

Lai, Jonathan Y.

1994-01-01

This dissertation focuses on the signal processing problems associated with the detection of hazardous windshears using airborne Doppler radar when weak weather returns are in the presence of strong clutter returns. In light of the frequent inadequacy of spectral-processing oriented clutter suppression methods, we model a clutter signal as multiple sinusoids plus Gaussian noise, and propose adaptive filtering approaches that better capture the temporal characteristics of the signal process. This idea leads to two research topics in signal processing: (1) signal modeling and parameter estimation, and (2) adaptive filtering in this particular signal environment. A high-resolution, low SNR threshold maximum likelihood (ML) frequency estimation and signal modeling algorithm is devised and proves capable of delineating both the spectral and temporal nature of the clutter return. Furthermore, the Least Mean Square (LMS) -based adaptive filter's performance for the proposed signal model is investigated, and promising simulation results have testified to its potential for clutter rejection leading to more accurate estimation of windspeed thus obtaining a better assessment of the windshear hazard.

Spectrum Modal Analysis for the Detection of Low-Altitude Windshear with Airborne Doppler Radar

NASA Technical Reports Server (NTRS)

Kunkel, Matthew W.

1992-01-01

A major obstacle in the estimation of windspeed patterns associated with low-altitude windshear with an airborne pulsed Doppler radar system is the presence of strong levels of ground clutter which can strongly bias a windspeed estimate. Typical solutions attempt to remove the clutter energy from the return through clutter rejection filtering. Proposed is a method whereby both the weather and clutter modes present in a return spectrum can be identified to yield an unbiased estimate of the weather mode without the need for clutter rejection filtering. An attempt will be made to show that modeling through a second order extended Prony approach is sufficient for the identification of the weather mode. A pattern recognition approach to windspeed estimation from the identified modes is derived and applied to both simulated and actual flight data. Comparisons between windspeed estimates derived from modal analysis and the pulse-pair estimator are included as well as associated hazard factors. Also included is a computationally attractive method for estimating windspeeds directly from the coefficients of a second-order autoregressive model. Extensions and recommendations for further study are included.

Ultrasensitive Ambient Mass Spectrometric Analysis with a Pin-to-Capillary Flowing Atmospheric-Pressure Afterglow Source

PubMed Central

Shelley, Jacob T.; Wiley, Joshua S.; Hieftje, Gary M.

2011-01-01

The advent of ambient desorption/ionization mass spectrometry has resulted in a strong interest in ionization sources that are capable of direct analyte sampling and ionization. One source that has enjoyed increasing interest is the Flowing Atmospheric-Pressure Afterglow (FAPA). FAPA has been proven capable of directly desorbing/ionizing samples in any phase (solid, liquid, or gas) and with impressive limits of detection (<100 fmol). The FAPA was also shown to be less affected by competitive-ionization matrix effects than other plasma-based sources. However, the original FAPA design exhibited substantial background levels, cluttered background spectra in the negative-ion mode, and significant oxidation of aromatic analytes, which ultimately compromised analyte identification and quantification. In the present study, a change in the FAPA configuration from a pin-to-plate to a pin-to-capillary geometry was found to vastly improve performance. Background signals in positive- and negative-ionization modes were reduced by 89% and 99%, respectively. Additionally, the capillary anode strongly reduced the amount of atomic oxygen that could cause oxidation of analytes. Temperatures of the gas stream that interacts with the sample, which heavily influences desorption capabilities, were compared between the two sources by means of IR thermography. The performance of the new FAPA configuration is evaluated through the determination of a variety of compounds in positive- and negative-ion mode, including agrochemicals and explosives. A detection limit of 4 amol was found for the direct determination of the agrochemical ametryn, and appears to be spectrometer-limited. The ability to quickly screen for analytes in bulk liquid samples with the pin-to-capillary FAPA is also shown. PMID:21627097

Ultrasensitive ambient mass spectrometric analysis with a pin-to-capillary flowing atmospheric-pressure afterglow source.

PubMed

Shelley, Jacob T; Wiley, Joshua S; Hieftje, Gary M

2011-07-15

The advent of ambient desorption/ionization mass spectrometry has resulted in a strong interest in ionization sources that are capable of direct analyte sampling and ionization. One source that has enjoyed increasing interest is the flowing atmospheric-pressure afterglow (FAPA). The FAPA has been proven capable of directly desorbing/ionizing samples in any phase (solid, liquid, or gas) and with impressive limits of detection (<100 fmol). The FAPA was also shown to be less affected by competitive-ionization matrix effects than other plasma-based sources. However, the original FAPA design exhibited substantial background levels, cluttered background spectra in the negative-ion mode, and significant oxidation of aromatic analytes, which ultimately compromised analyte identification and quantification. In the present study, a change in the FAPA configuration from a pin-to-plate to a pin-to-capillary geometry was found to vastly improve performance. Background signals in positive- and negative-ionization modes were reduced by 89% and 99%, respectively. Additionally, the capillary anode strongly reduced the amount of atomic oxygen that could cause oxidation of analytes. Temperatures of the gas stream that interacts with the sample, which heavily influences desorption capabilities, were compared between the two sources by means of IR thermography. The performance of the new FAPA configuration is evaluated through the determination of a variety of compounds in positive- and negative-ion mode, including agrochemicals and explosives. A detection limit of 4 amol was found for the direct determination of the agrochemical ametryn and appears to be spectrometer-limited. The ability to quickly screen for analytes in bulk liquid samples with the pin-to-capillary FAPA is also shown.

Ultra-wideband horn antenna with abrupt radiator

DOEpatents

McEwan, T.E.

1998-05-19

An ultra-wideband horn antenna transmits and receives impulse waveforms for short-range radars and impulse time-of flight systems. The antenna reduces or eliminates various sources of close-in radar clutter, including pulse dispersion and ringing, sidelobe clutter, and feedline coupling into the antenna. Dispersion is minimized with an abrupt launch point radiator element; sidelobe and feedline coupling are minimized by recessing the radiator into a metallic horn. Low frequency cut-off associated with a horn is extended by configuring the radiator drive impedance to approach a short circuit at low frequencies. A tapered feed plate connects at one end to a feedline, and at the other end to a launcher plate which is mounted to an inside wall of the horn. The launcher plate and feed plate join at an abrupt edge which forms the single launch point of the antenna. 8 figs.

Cognitive Algorithms for Signal Processing

DTIC Science & Technology

2011-03-18

Analysis of Millennial Spiritual Issues,” Zygon, Journal of Science and Religion , 43(4), 797-821, 2008. [46] R. Linnehan, C. Mutz, L.I. Perlovsky, B...dimensions of X and Y : (a) true ‘smile’ and ‘frown’ patterns are shown without clutter; (b) actual image available for recognition (signal is below...clutter in 2 dimensions of X(n) = (X, Y ), is given by l(X(n)|m = clutter) = 1/ (X •  Y ), X = (Xmax-Xmin),  Y = (Ymax-Ymin); (6) 13 Minimal

Shallow Water UXO Technology Demonstration Site Scoring Record No. 1. Technology Type/Platform: GEN-3 Array

DTIC Science & Technology

2008-04-01

Clutter items fit into one of three categories: ferrous, nonferrous , and mixed metals . The ferrous and nonferrous items have been further divided into...that have both a ferrous and nonferrous component and could reasonably be encountered in a range area. The mixed- metals clutter was placed in the...however, there are also industrial scrap metal and cultural items as well. The mixed- metals clutter is comprised of scrap ordnance items or fragments

Coordinate-Based Clustering Method for Indoor Fingerprinting Localization in Dense Cluttered Environments.

PubMed

Liu, Wen; Fu, Xiao; Deng, Zhongliang

2016-12-02

Indoor positioning technologies has boomed recently because of the growing commercial interest in indoor location-based service (ILBS). Due to the absence of satellite signal in Global Navigation Satellite System (GNSS), various technologies have been proposed for indoor applications. Among them, Wi-Fi fingerprinting has been attracting much interest from researchers because of its pervasive deployment, flexibility and robustness to dense cluttered indoor environments. One challenge, however, is the deployment of Access Points (AP), which would bring a significant influence on the system positioning accuracy. This paper concentrates on WLAN based fingerprinting indoor location by analyzing the AP deployment influence, and studying the advantages of coordinate-based clustering compared to traditional RSS-based clustering. A coordinate-based clustering method for indoor fingerprinting location, named Smallest-Enclosing-Circle-based (SEC), is then proposed aiming at reducing the positioning error lying in the AP deployment and improving robustness to dense cluttered environments. All measurements are conducted in indoor public areas, such as the National Center For the Performing Arts (as Test-bed 1) and the XiDan Joy City (Floors 1 and 2, as Test-bed 2), and results show that SEC clustering algorithm can improve system positioning accuracy by about 32.7% for Test-bed 1, 71.7% for Test-bed 2 Floor 1 and 73.7% for Test-bed 2 Floor 2 compared with traditional RSS-based clustering algorithms such as K-means.

Coordinate-Based Clustering Method for Indoor Fingerprinting Localization in Dense Cluttered Environments

PubMed Central

Liu, Wen; Fu, Xiao; Deng, Zhongliang

2016-01-01

Indoor positioning technologies has boomed recently because of the growing commercial interest in indoor location-based service (ILBS). Due to the absence of satellite signal in Global Navigation Satellite System (GNSS), various technologies have been proposed for indoor applications. Among them, Wi-Fi fingerprinting has been attracting much interest from researchers because of its pervasive deployment, flexibility and robustness to dense cluttered indoor environments. One challenge, however, is the deployment of Access Points (AP), which would bring a significant influence on the system positioning accuracy. This paper concentrates on WLAN based fingerprinting indoor location by analyzing the AP deployment influence, and studying the advantages of coordinate-based clustering compared to traditional RSS-based clustering. A coordinate-based clustering method for indoor fingerprinting location, named Smallest-Enclosing-Circle-based (SEC), is then proposed aiming at reducing the positioning error lying in the AP deployment and improving robustness to dense cluttered environments. All measurements are conducted in indoor public areas, such as the National Center For the Performing Arts (as Test-bed 1) and the XiDan Joy City (Floors 1 and 2, as Test-bed 2), and results show that SEC clustering algorithm can improve system positioning accuracy by about 32.7% for Test-bed 1, 71.7% for Test-bed 2 Floor 1 and 73.7% for Test-bed 2 Floor 2 compared with traditional RSS-based clustering algorithms such as K-means. PMID:27918454

Topological anomaly detection performance with multispectral polarimetric imagery

NASA Astrophysics Data System (ADS)

Gartley, M. G.; Basener, W.,

2009-05-01

Polarimetric imaging has demonstrated utility for increasing contrast of manmade targets above natural background clutter. Manual detection of manmade targets in multispectral polarimetric imagery can be challenging and a subjective process for large datasets. Analyst exploitation may be improved utilizing conventional anomaly detection algorithms such as RX. In this paper we examine the performance of a relatively new approach to anomaly detection, which leverages topology theory, applied to spectral polarimetric imagery. Detection results for manmade targets embedded in a complex natural background will be presented for both the RX and Topological Anomaly Detection (TAD) approaches. We will also present detailed results examining detection sensitivities relative to: (1) the number of spectral bands, (2) utilization of Stoke's images versus intensity images, and (3) airborne versus spaceborne measurements.

Synthetic aperture radar images with composite azimuth resolution

DOEpatents

Bielek, Timothy P; Bickel, Douglas L

2015-03-31

A synthetic aperture radar (SAR) image is produced by using all phase histories of a set of phase histories to produce a first pixel array having a first azimuth resolution, and using less than all phase histories of the set to produce a second pixel array having a second azimuth resolution that is coarser than the first azimuth resolution. The first and second pixel arrays are combined to produce a third pixel array defining a desired SAR image that shows distinct shadows of moving objects while preserving detail in stationary background clutter.

Polarimetric discrimination of atmospheric particulate matter

NASA Astrophysics Data System (ADS)

Raman, Prashant; Fuller, Kirk; Gregory, Don

2012-06-01

A polarimeter capable of measuring the complete Mueller matrix of highly scattering samples in transmission and reflection from 300 to 1100 nm has been constructed and tested. Exploratory research has been conducted which may lead to the standoff detection of bio-aerosols in the atmosphere. The polarization properties of bsubtilis (surrogate for anthrax spore) have been compared to ambient particulate matter species such as pollen, dust and soot (all sampled onto microscope slides) and differentiating features have been identified. The application of this technique for the discrimination of bio-aerosol from background clutter has been demonstrated.

Polarimetric subspace target detector for SAR data based on the Huynen dihedral model

NASA Astrophysics Data System (ADS)

Larson, Victor J.; Novak, Leslie M.

1995-06-01

Two new polarimetric subspace target detectors are developed based on a dihedral signal model for bright peaks within a spatially extended target signature. The first is a coherent dihedral target detector based on the exact Huynen model for a dihedral. The second is a noncoherent dihedral target detector based on the Huynen model with an extra unknown phase term. Expressions for these polarimetric subspace target detectors are developed for both additive Gaussian clutter and more general additive spherically invariant random vector clutter including the K-distribution. For the case of Gaussian clutter with unknown clutter parameters, constant false alarm rate implementations of these polarimetric subspace target detectors are developed. The performance of these dihedral detectors is demonstrated with real millimeter-wave fully polarimetric SAR data. The coherent dihedral detector which is developed with a more accurate description of a dihedral offers no performance advantage over the noncoherent dihedral detector which is computationally more attractive. The dihedral detectors do a better job of separating a set of tactical military targets from natural clutter compared to a detector that assumes no knowledge about the polarimetric structure of the target signal.

Estimation of the rain signal in the presence of large surface clutter

NASA Technical Reports Server (NTRS)

Ahamad, Atiq; Moore, Richard K.

1994-01-01

The principal limitation for the use of a spaceborne imaging SAR as a rain radar is the surface-clutter problem. Signals may be estimated in the presence of noise by averaging large numbers of independent samples. This method was applied to obtain an estimate of the rain echo by averaging a set of N(sub c) samples of the clutter in a separate measurement and subtracting the clutter estimate from the combined estimate. The number of samples required for successful estimation (within 10-20%) for off-vertical angles of incidence appears to be prohibitively large. However, by appropriately degrading the resolution in both range and azimuth, the required number of samples can be obtained. For vertical incidence, the number of samples required for successful estimation is reasonable. In estimating the clutter it was assumed that the surface echo is the same outside the rain volume as it is within the rain volume. This may be true for the forest echo, but for convective storms over the ocean the surface echo outside the rain volume is very different from that within. It is suggested that the experiment be performed with vertical incidence over forest to overcome this limitation.

[Design Method Analysis and Performance Comparison of Wall Filter for Ultrasound Color Flow Imaging].

PubMed

Wang, Lutao; Xiao, Jun; Chai, Hua

2015-08-01

The successful suppression of clutter arising from stationary or slowly moving tissue is one of the key issues in medical ultrasound color blood imaging. Remaining clutter may cause bias in the mean blood frequency estimation and results in a potentially misleading description of blood-flow. In this paper, based on the principle of general wall-filter, the design process of three classes of filters, infinitely impulse response with projection initialization (Prj-IIR), polynomials regression (Pol-Reg), and eigen-based filters are previewed and analyzed. The performance of the filters was assessed by calculating the bias and variance of a mean blood velocity using a standard autocorrelation estimator. Simulation results show that the performance of Pol-Reg filter is similar to Prj-IIR filters. Both of them can offer accurate estimation of mean blood flow speed under steady clutter conditions, and the clutter rejection ability can be enhanced by increasing the ensemble size of Doppler vector. Eigen-based filters can effectively remove the non-stationary clutter component, and further improve the estimation accuracy for low speed blood flow signals. There is also no significant increase in computation complexity for eigen-based filters when the ensemble size is less than 10.

Enhanced Cleaning and Education to Prevent Transmission of Clostridium difficile in Pediatrics

PubMed Central

Aslam, Anoshé; Melendez, Giselle; Wang, Min; Stell, Frederic; Kelly, Paulette; Killinger, James; Dannaoui, Aimee; Riedman, Scott; Lopez, Ruben; Ackerman, Jill; Chou, Alexander; Wexler, Leonard; Smith, David; Sanchez, Stacy; Robilotti, Elizabeth; Kamboj, Mini; Eagan, Janet

2017-01-01

Abstract Background Transmission of healthcare-associated Clostridium difficile infection (HA-CDI) has been shown to occur directly or indirectly through a contaminated environment. At a tertiary-care cancer center, HA-CDI rates were higher for pediatric units than for other general oncology units. To address the problem, a multidisciplinary team, including Infection Control, Nursing, and Environmental Services (EVS), was convened and identified refusals and room clutter as barriers to proper cleaning of rooms on the unit. Aim: The aim of this study seeks to reduce HA-CDI in the inpatient pediatrics setting through environmental and educational interventions. Methods In the first phase of the study from February to April 2016, a baseline assessment of prevalent environmental disinfection practices was made among Nursing, EVS, Physicians, and Patient Representatives. Based on this feedback, the following were implemented during Phase 2, from June through October 2016: 1) Unit-wide disinfection with bleach twice a day including common and high traffic areas; 2) Initiation of a “preferred time for cleaning” program to engage families; 3) Enhanced visitor and family education on PPE use; 4) Creation of a communication plan in case of refusal to clean rooms; and 5) Dedicated use of diaper scales. Results During the first phase of the study, the following barriers to cleaning were identified: 1) High refusal rate as cleaning was perceived as inconvenient by families due to timing; 2) Common perception among EVS staff that multiple requests for cleaning the room may appear intrusive to the families; 3) Excessive clutter in the room; 4) Lack of education regarding PPE use; and 5) Shared equipment for diapers. To overcome these barriers, several interventions as outlined in methods were implemented. In Phase 2, there were 0 cases of HA-CDI identified in pediatric patients starting in July through October, 2016. Conclusion Control of CDI on pediatric units poses unique challenges. Engagement of key stakeholders is essential to identify and meet these challenges and to devise effective strategies that will ultimately lead to reduced hospital-based transmission of CDI. Disclosures All authors: No reported disclosures.

Catheter tracking via online learning for dynamic motion compensation in transcatheter aortic valve implantation.

PubMed

Wang, Peng; Zheng, Yefeng; John, Matthias; Comaniciu, Dorin

2012-01-01

Dynamic overlay of 3D models onto 2D X-ray images has important applications in image guided interventions. In this paper, we present a novel catheter tracking for motion compensation in the Transcatheter Aortic Valve Implantation (TAVI). To address such challenges as catheter shape and appearance changes, occlusions, and distractions from cluttered backgrounds, we present an adaptive linear discriminant learning method to build a measurement model online to distinguish catheters from background. An analytic solution is developed to effectively and efficiently update the discriminant model and to minimize the classification errors between the tracking object and backgrounds. The online learned discriminant model is further combined with an offline learned detector and robust template matching in a Bayesian tracking framework. Quantitative evaluations demonstrate the advantages of this method over current state-of-the-art tracking methods in tracking catheters for clinical applications.

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.

Motion detection, novelty filtering, and target tracking using an interferometric technique with GaAs phase conjugate mirror

NASA Technical Reports Server (NTRS)

Cheng, Li-Jen (Inventor); Liu, Tsuen-Hsi (Inventor)

1991-01-01

A method and apparatus for detecting and tracking moving objects in a noise environment cluttered with fast- and slow-moving objects and other time-varying background. A pair of phase conjugate light beams carrying the same spatial information commonly cancel each other out through an image subtraction process in a phase conjugate interferometer, wherein gratings are formed in a fast photorefractive phase conjugate mirror material. In the steady state, there is no output. When the optical path of one of the two phase conjugate beams is suddenly changed, the return beam loses its phase conjugate nature and the interferometer is out of balance, resulting in an observable output. The observable output lasts until the phase conjugate nature of the beam has recovered. The observable time of the output signal is roughly equal to the formation time of the grating. If the optical path changing time is slower than the formation time, the change of optical path becomes unobservable, because the index grating can follow the change. Thus, objects traveling at speeds which result in a path changing time which is slower than the formation time are not observable and do not clutter the output image view.

Application of speed-enhanced spatial domain correlation filters for real-time security monitoring

NASA Astrophysics Data System (ADS)

Gardezi, Akber; Bangalore, Nagachetan; Al-Kandri, Ahmed; Birch, Philip; Young, Rupert; Chatwin, Chris

2011-11-01

A speed enhanced space variant correlation filer which has been designed to be invariant to change in orientation and scale of the target object but also to be spatially variant, i.e. the filter function becoming dependant on local clutter conditions within the image. The speed enhancement of the filter is due to the use of optimization techniques employing low-pass filtering to restrict kernel movement to be within regions of interest. The detection and subsequent identification capability of the two-stage process has been evaluated in highly cluttered backgrounds using both visible and thermal imagery acquired from civil and defense domains along with associated training data sets for target detection and classification. In this paper a series of tests have been conducted in multiple scenarios relating to situations that pose a security threat. Performance matrices comprised of peak-to-correlation energy (PCE) and peak-to-side lobe ratio (PSR) measurements of the correlation output have been calculated to allow the definition of a recognition criterion. The hardware implementation of the system has been discussed in terms of Field Programmable Gate Array (FPGA) chipsets with implementation bottle necks and their solution being considered.

Water Detection Based on Object Reflections

NASA Technical Reports Server (NTRS)

Rankin, Arturo L.; Matthies, Larry H.

2012-01-01

Water bodies are challenging terrain hazards for terrestrial unmanned ground vehicles (UGVs) for several reasons. Traversing through deep water bodies could cause costly damage to the electronics of UGVs. Additionally, a UGV that is either broken down due to water damage or becomes stuck in a water body during an autonomous operation will require rescue, potentially drawing critical resources away from the primary operation and increasing the operation cost. Thus, robust water detection is a critical perception requirement for UGV autonomous navigation. One of the properties useful for detecting still water bodies is that their surface acts as a horizontal mirror at high incidence angles. Still water bodies in wide-open areas can be detected by geometrically locating the exact pixels in the sky that are reflecting on candidate water pixels on the ground, predicting if ground pixels are water based on color similarity to the sky and local terrain features. But in cluttered areas where reflections of objects in the background dominate the appearance of the surface of still water bodies, detection based on sky reflections is of marginal value. Specifically, this software attempts to solve the problem of detecting still water bodies on cross-country terrain in cluttered areas at low cost.

Mars radar clutter and surface roughness characteristics from MARSIS data

NASA Astrophysics Data System (ADS)

Campbell, Bruce A.; Schroeder, Dustin M.; Whitten, Jennifer L.

2018-01-01

Radar sounder studies of icy, sedimentary, and volcanic settings can be affected by reflections from surface topography surrounding the sensor nadir location. These off-nadir ;clutter; returns appear at similar time delays to subsurface echoes and complicate geologic interpretation. Additionally, broadening of the radar echo in delay by surface returns sets a limit on the detectability of subsurface interfaces. We use MARSIS 4 MHz data to study variations in the nadir and off-nadir clutter echoes, from about 300 km to 1000 km altitude, R, for a wide range of surface roughness. This analysis uses a new method of characterizing ionospheric attenuation to merge observations over a range of solar zenith angle and date. Mirror-like reflections should scale as R-2, but the observed 4 MHz nadir echoes often decline by a somewhat smaller power-law factor because MARSIS on-board processing increases the number of summed pulses with altitude. Prior predictions of the contributions from clutter suggest a steeper decline with R than the nadir echoes, but in very rough areas the ratio of off-nadir returns to nadir echoes shows instead an increase of about R1/2 with altitude. This is likely due in part to an increase in backscatter from the surface as the radar incidence angle at some round-trip time delay declines with increasing R. It is possible that nadir and clutter echo properties in other planetary sounding observations, including RIME and REASON flyby data for Europa, will vary in the same way with altitude, but there may be differences in the nature and scale of target roughness (e.g., icy versus rocky surfaces). We present global maps of the ionosphere- and altitude-corrected nadir echo strength, and of a ;clutter; parameter based on the ratio of off-nadir to nadir echoes. The clutter map offers a view of surface roughness at ∼75 m length scale, bridging the spatial-scale gap between SHARAD roughness estimates and MOLA-derived parameters.

Automatic target recognition and detection in infrared imagery under cluttered background

NASA Astrophysics Data System (ADS)

Gundogdu, Erhan; Koç, Aykut; Alatan, A. Aydın.

2017-10-01

Visual object classification has long been studied in visible spectrum by utilizing conventional cameras. Since the labeled images has recently increased in number, it is possible to train deep Convolutional Neural Networks (CNN) with significant amount of parameters. As the infrared (IR) sensor technology has been improved during the last two decades, labeled images extracted from IR sensors have been started to be used for object detection and recognition tasks. We address the problem of infrared object recognition and detection by exploiting 15K images from the real-field with long-wave and mid-wave IR sensors. For feature learning, a stacked denoising autoencoder is trained in this IR dataset. To recognize the objects, the trained stacked denoising autoencoder is fine-tuned according to the binary classification loss of the target object. Once the training is completed, the test samples are propagated over the network, and the probability of the test sample belonging to a class is computed. Moreover, the trained classifier is utilized in a detect-by-classification method, where the classification is performed in a set of candidate object boxes and the maximum confidence score in a particular location is accepted as the score of the detected object. To decrease the computational complexity, the detection step at every frame is avoided by running an efficient correlation filter based tracker. The detection part is performed when the tracker confidence is below a pre-defined threshold. The experiments conducted on the real field images demonstrate that the proposed detection and tracking framework presents satisfactory results for detecting tanks under cluttered background.

Revisiting flow maps: a classification and a 3D alternative to visual clutter

NASA Astrophysics Data System (ADS)

Gu, Yuhang; Kraak, Menno-Jan; Engelhardt, Yuri

2018-05-01

Flow maps have long been servicing people in exploring movement by representing origin-destination data (OD data). Due to recent developments in data collecting techniques the amount of movement data is increasing dramatically. With such huge amounts of data, visual clutter in flow maps is becoming a challenge. This paper revisits flow maps, provides an overview of the characteristics of OD data and proposes a classification system for flow maps. For dealing with problems of visual clutter, 3D flow maps are proposed as potential alternative to 2D flow maps.

10 cm radar ground clutter measurements taken from a coastal steamer radar on passage from Bergen to North Cape in May 1982

NASA Astrophysics Data System (ADS)

Williams, P. D. L.

1983-08-01

The range of R.C.S. values from a high rising natural coastline viewed by radar on a ship proceeding along that coast from 1 to 10 miles away. The range of R.C.S. values from the mountainous country just inland of the first coastal echo. The likely range of spatial filling factor of inland ground clutter and radar detection of aircraft flying overland in these regions using interclutter visibility rather than classic DOPPLER MTI methods of ""sub clutter'' detection are addressed.

Developing the fuzzy c-means clustering algorithm based on maximum entropy for multitarget tracking in a cluttered environment

NASA Astrophysics Data System (ADS)

Chen, Xiao; Li, Yaan; Yu, Jing; Li, Yuxing

2018-01-01

For fast and more effective implementation of tracking multiple targets in a cluttered environment, we propose a multiple targets tracking (MTT) algorithm called maximum entropy fuzzy c-means clustering joint probabilistic data association that combines fuzzy c-means clustering and the joint probabilistic data association (PDA) algorithm. The algorithm uses the membership value to express the probability of the target originating from measurement. The membership value is obtained through fuzzy c-means clustering objective function optimized by the maximum entropy principle. When considering the effect of the public measurement, we use a correction factor to adjust the association probability matrix to estimate the state of the target. As this algorithm avoids confirmation matrix splitting, it can solve the high computational load problem of the joint PDA algorithm. The results of simulations and analysis conducted for tracking neighbor parallel targets and cross targets in a different density cluttered environment show that the proposed algorithm can realize MTT quickly and efficiently in a cluttered environment. Further, the performance of the proposed algorithm remains constant with increasing process noise variance. The proposed algorithm has the advantages of efficiency and low computational load, which can ensure optimum performance when tracking multiple targets in a dense cluttered environment.

Modeling and Analysis of Target Echo and Clutter in Range-Dependent Bistatic Environments: FY14 Annual Report for ONR

DTIC Science & Technology

2014-09-30

with energy source level ESL of 198.4 dB; the omnidirectional results were reduced by the effective reverberation response [EP09] of 19.7 dB. The...analysis and improved environmental inputs. Similar graphs (not shown) were obtained for the 1900–2000 Hz LFM and 2700–2800 Hz LFM, using ESLs of

Getting it Right: The Art of Strategy and Operational Warfare

DTIC Science & Technology

2008-01-01

level strategic guidance. This latest revision reduces doctrinal clutter, and its crisp prose is a welcome stylistic improvement over previous...elements of power as “instruments,” joint doc- trine fails to make the cognitive discrimination necessary to deal with the challenges we face and...military, and economic elemental categories. This confusion creates a cognitive disso- nance within joint doctrine that remains unre- solved, seeing

Physics of tissue harmonic imaging by ultrasound

NASA Astrophysics Data System (ADS)

Jing, Yuan

Tissue Harmonic Imaging (THI) is an imaging modality that is currently deployed on diagnostic ultrasound scanners. In THI the amplitude of the ultrasonic pulse that is used to probe the tissue is large enough that the pulse undergoes nonlinear distortion as it propagates into the tissue. One result of the distortion is that as the pulse propagates energy is shifted from the fundamental frequency of the source pulse into its higher harmonics. These harmonics will scatter off objects in the tissue and images formed from the scattered higher harmonics are considered to have superior quality to the images formed from the fundamental frequency. Processes that have been suggested as possibly responsible for the improved imaging in THI include: (1) reduced sensitivity to reverberation, (2) reduced sensitivity to aberration, and (3) reduction in side lobes. By using a combination of controlled experiments and numerical simulations, these three reasons have been investigated. A single element transducer and a clinical ultrasound scanner with a phased array transducer were used to image a commercial tissue-mimicking phantom with calibrated targets. The higher image quality achieved with THI was quantified in terms of spatial resolution and "clutter" signals. A three-dimensional model of the forward propagation of nonlinear sound beams in media with arbitrary spatial properties (a generalized KZK equation) was developed. A time-domain code for solving the KZK equation was validated with measurements of the acoustic field generated by the single element transducer and the phased array transducer. The code was used to investigate the impact of aberration using tissue-like media with three-dimensional variations in all acoustic properties. The three-dimensional maps of tissue properties were derived from the datasets available through the Visible Female project. The experiments and simulations demonstrated that second harmonic imaging (1) suffers less clutter associated with reverberation; (2) is not immune to aberration effects and (3) suffers less clutter due to reduced side-lobe levels. The results indicate that side lobe suppression is the most significant reason for the improvement of second harmonic imaging.

A parallel efficient partitioning algorithm for the statistical model of dynamic sea clutter at low grazing angle

NASA Astrophysics Data System (ADS)

Wu, Tao; Wu, Zhensen; Linghu, Longxiang

2017-10-01

Study of characteristics of sea clutter is very important for signal processing of radar, detection of targets on sea surface and remote sensing. The sea state is complex at Low grazing angle (LGA), and it is difficult with its large irradiation area and a great deal simulation facets. A practical and efficient model to obtain radar clutter of dynamic sea in different sea condition is proposed, basing on the physical mechanism of interaction between electromagnetic wave and sea wave. The classical analysis method for sea clutter is basing on amplitude and spectrum distribution, taking the clutter as random processing model, which is equivocal in its physical mechanism. To achieve electromagnetic field from sea surface, a modified phase from facets is considered, and the backscattering coefficient is calculated by Wu's improved two-scale model, which can solve the statistical sea backscattering problem less than 5 degree, considering the effects of the surface slopes joint probability density, the shadowing function, the skewness of sea waves and the curvature of the surface on the backscattering from the ocean surface. We make the assumption that the scattering contribution of each facet is independent, the total field is the superposition of each facet in the receiving direction. Such data characters are very suitable to compute on GPU threads. So we can make the best of GPU resource. We have achieved a speedup of 155-fold for S band and 162-fold for Ku/Χ band on the Tesla K80 GPU as compared with Intel® Core™ CPU. In this paper, we mainly study the high resolution data, and the time resolution is millisecond, so we may have 10,00 time points, and we analyze amplitude probability density distribution of radar clutter.

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

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.

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.

A closed curve is much more than an incomplete one: effect of closure in figure-ground segmentation.

PubMed

Kovács, I; Julesz, B

1993-08-15

Detection of fragmented closed contours against a cluttered background occurs much beyond the local coherence distance (maximal separation between segments) of nonclosed contours. This implies that the extent of interaction between locally connected detectors is boosted according to the global stimulus structure. We further show that detection of a target probe is facilitated when the probe is positioned inside a closed circle. To explain the striking contour segregation ability found here, and performance enhancement inside closed boundaries, we propose the existence of a synergetic process in early vision.

Detection of concealed explosives at stand-off distances using wide band swept millimetre waves

NASA Astrophysics Data System (ADS)

Andrews, David A.; Rezgui, Nacer D.; Smith, Sarah E.; Bowring, Nicholas; Southgate, Matthew; Baker, John G.

2008-10-01

Millimetre waves in the range 20 to 110 GHz have been used to detect the presence and thickness of dielectric materials, such as explosives, by measuring the frequency response of the return signal. Interference between the reflected signals from the front and back surfaces of the dielectric provides a characteristic frequency variation in the return signal, which may be processed to yield its optical depth [Bowring et al, Meas. Sci. Technol. 19, 024004 (2008)]. The depth resolution depends on the sweep bandwidth, which is typically 10 to 30 GHz. By using super-heterodyne detection the range of the object can also be determined, which enables a signal from a target, such as a suicide bomber to be extracted from background clutter. Using millimetre wave optics only a small area of the target is illuminated at a time, thus reducing interference from different parts of a human target. Results are presented for simulated explosive materials with water or human backing at stand-off distances. A method of data analysis that involves pattern recognition enables effective differentiation of target types.

Certification of windshear performance with RTCA class D radomes

NASA Technical Reports Server (NTRS)

Mathews, Bruce D.; Miller, Fran; Rittenhouse, Kirk; Barnett, Lee; Rowe, William

1994-01-01

Superposition testing of detection range performance forms a digital signal for input into a simulation of signal and data processing equipment and algorithms to be employed in a sensor system for advanced warning of hazardous windshear. For suitable pulse-Doppler radar, recording of the digital data at the input to the digital signal processor furnishes a realistic operational scenario and environmentally responsive clutter signal including all sidelobe clutter, ground moving target indications (GMTI), and large signal spurious due to mainbeam clutter and/or RFI respective of the urban airport clutter and aircraft scenarios (approach and landing antenna pointing). For linear radar system processes, a signal at the same point in the process from a hazard phenomena may be calculated from models of the scattering phenomena, for example, as represented in fine 3 dimensional reflectivity and velocity grid structures. Superposition testing furnishes a competing signal environment for detection and warning time performance confirmation of phenomena uncontrollable in a natural environment.

Target-adaptive polarimetric synthetic aperture radar target discrimination using maximum average correlation height filters.

PubMed

Sadjadi, Firooz A; Mahalanobis, Abhijit

2006-05-01

We report the development of a technique for adaptive selection of polarization ellipse tilt and ellipticity angles such that the target separation from clutter is maximized. From the radar scattering matrix [S] and its complex components, in phase and quadrature phase, the elements of the Mueller matrix are obtained. Then, by means of polarization synthesis, the radar cross section of the radar scatters are obtained at different transmitting and receiving polarization states. By designing a maximum average correlation height filter, we derive a target versus clutter distance measure as a function of four transmit and receive polarization state angles. The results of applying this method on real synthetic aperture radar imagery indicate a set of four transmit and receive angles that lead to maximum target versus clutter discrimination. These optimum angles are different for different targets. Hence, by adaptive control of the state of polarization of polarimetric radar, one can noticeably improve the discrimination of targets from clutter.

Age differences in search of web pages: the effects of link size, link number, and clutter.

PubMed

Grahame, Michael; Laberge, Jason; Scialfa, Charles T

2004-01-01

Reaction time, eye movements, and errors were measured during visual search of Web pages to determine age-related differences in performance as a function of link size, link number, link location, and clutter. Participants (15 young adults, M = 23 years; 14 older adults, M = 57 years) searched Web pages for target links that varied from trial to trial. During one half of the trials, links were enlarged from 10-point to 12-point font. Target location was distributed among the left, center, and bottom portions of the screen. Clutter was manipulated according to the percentage of used space, including graphics and text, and the number of potentially distracting nontarget links was varied. Increased link size improved performance, whereas increased clutter and links hampered search, especially for older adults. Results also showed that links located in the left region of the page were found most easily. Actual or potential applications of this research include Web site design to increase usability, particularly for older adults.

Unsupervised iterative detection of land mines in highly cluttered environments.

PubMed

Batman, Sinan; Goutsias, John

2003-01-01

An unsupervised iterative scheme is proposed for land mine detection in heavily cluttered scenes. This scheme is based on iterating hybrid multispectral filters that consist of a decorrelating linear transform coupled with a nonlinear morphological detector. Detections extracted from the first pass are used to improve results in subsequent iterations. The procedure stops after a predetermined number of iterations. The proposed scheme addresses several weaknesses associated with previous adaptations of morphological approaches to land mine detection. Improvement in detection performance, robustness with respect to clutter inhomogeneities, a completely unsupervised operation, and computational efficiency are the main highlights of the method. Experimental results reveal excellent performance.

Identification of the ideal clutter metric to predict time dependence of human visual search

NASA Astrophysics Data System (ADS)

Cartier, Joan F.; Hsu, David H.

1995-05-01

The Army Night Vision and Electronic Sensors Directorate (NVESD) has recently performed a human perception experiment in which eye tracker measurements were made on trained military observers searching for targets in infrared images. This data offered an important opportunity to evaluate a new technique for search modeling. Following the approach taken by Jeff Nicoll, this model treats search as a random walk in which the observers are in one of two states until they quit: they are either searching, or they are wandering around looking for a point of interest. When wandering they skip rapidly from point to point. When examining they move more slowly, reflecting the fact that target discrimination requires additional thought processes. In this paper we simulate the random walk, using a clutter metric to assign relative attractiveness to points of interest within the image which are competing for the observer's attention. The NVESD data indicates that a number of standard clutter metrics are good estimators of the apportionment of observer's time between wandering and examining. Conversely, the apportionment of observer time spent wandering and examining could be used to reverse engineer the ideal clutter metric which would most perfectly describe the behavior of the group of observers. It may be possible to use this technique to design the optimal clutter metric to predict performance of visual search.

Clutter and target discrimination in forward-looking ground penetrating radar using sparse structured basis pursuits

NASA Astrophysics Data System (ADS)

Camilo, Joseph A.; Malof, Jordan M.; Torrione, Peter A.; Collins, Leslie M.; Morton, Kenneth D.

2015-05-01

Forward-looking ground penetrating radar (FLGPR) is a remote sensing modality that has recently been investigated for buried threat detection. FLGPR offers greater standoff than other downward-looking modalities such as electromagnetic induction and downward-looking GPR, but it suffers from high false alarm rates due to surface and ground clutter. A stepped frequency FLGPR system consists of multiple radars with varying polarizations and bands, each of which interacts differently with subsurface materials and therefore might potentially be able to discriminate clutter from true buried targets. However, it is unclear which combinations of bands and polarizations would be most useful for discrimination or how to fuse them. This work applies sparse structured basis pursuit, a supervised statistical model which searches for sets of bands that are collectively effective for discriminating clutter from targets. The algorithm works by trying to minimize the number of selected items in a dictionary of signals; in this case the separate bands and polarizations make up the dictionary elements. A structured basis pursuit algorithm is employed to gather groups of modes together in collections to eliminate whole polarizations or sensors. The approach is applied to a large collection of FLGPR data for data around emplaced target and non-target clutter. The results show that a sparse structure basis pursuits outperforms a conventional CFAR anomaly detector while also pruning out unnecessary bands of the FLGPR sensor.

Performance of the NASA Airborne Radar with the Windshear Database for Forward-Looking Systems

NASA Technical Reports Server (NTRS)

Switzer, George F.; Britt, Charles L.

1996-01-01

This document describes the simulation approach used to test the performance of the NASA airborne windshear radar. An explanation of the actual radar hardware and processing algorithms provides an understanding of the parameters used in the simulation program. This report also contains a brief overview of the NASA airborne windshear radar experimental flight test results. A description of the radar simulation program shows the capabilities of the program and the techniques used for certification evaluation. Simulation of the NASA radar is comprised of three steps. First, the choice of the ground clutter data must be made. The ground clutter is the return from objects in or nearby an airport facility. The choice of the ground clutter also dictates the aircraft flight path since ground clutter is gathered while in flight. The second step is the choice of the radar parameters and the running of the simulation program which properly combines the ground clutter data with simulated windshear weather data. The simulated windshear weather data is comprised of a number of Terminal Area Simulation System (TASS) model results. The final step is the comparison of the radar simulation results to the known windshear data base. The final evaluation of the radar simulation is based on the ability to detect hazardous windshear with the aircraft at a safe distance while at the same time not displaying false alerts.

Target oriented dimensionality reduction of hyperspectral data by Kernel Fukunaga-Koontz Transform

NASA Astrophysics Data System (ADS)

Binol, Hamidullah; Ochilov, Shuhrat; Alam, Mohammad S.; Bal, Abdullah

2017-02-01

Principal component analysis (PCA) is a popular technique in remote sensing for dimensionality reduction. While PCA is suitable for data compression, it is not necessarily an optimal technique for feature extraction, particularly when the features are exploited in supervised learning applications (Cheriyadat and Bruce, 2003) [1]. Preserving features belonging to the target is very crucial to the performance of target detection/recognition techniques. Fukunaga-Koontz Transform (FKT) based supervised band reduction technique can be used to provide this requirement. FKT achieves feature selection by transforming into a new space in where feature classes have complimentary eigenvectors. Analysis of these eigenvectors under two classes, target and background clutter, can be utilized for target oriented band reduction since each basis functions best represent target class while carrying least information of the background class. By selecting few eigenvectors which are the most relevant to the target class, dimension of hyperspectral data can be reduced and thus, it presents significant advantages for near real time target detection applications. The nonlinear properties of the data can be extracted by kernel approach which provides better target features. Thus, we propose constructing kernel FKT (KFKT) to present target oriented band reduction. The performance of the proposed KFKT based target oriented dimensionality reduction algorithm has been tested employing two real-world hyperspectral data and results have been reported consequently.

SPECSweb Post-Tracking Classification Method

DTIC Science & Technology

2011-07-01

The Specular-Cued Surveillance Web (SPECSweb) multistatic tracker effectively reduces false track rate through the use of two amplitude thresholds...Cueing – Clutter 1 Introduction A concept referred to as the “Specular-Cued Surveillance Web (SPECSweb)” is being pursued to mitigate the data...on 5-8 July 2011. Sponsored in part by Office of Naval Research and U.S. Army Research Laboratory. 14. ABSTRACT The Specular-Cued Surveillance Web

Dipole Models for UXO Discrimination at Live Sites

DTIC Science & Technology

2017-05-01

Discriminator CCR Combined Classifier Ranking cm Centimeter(s) EM Electromagnetic EMI Electromagnetic Induction ESTCP Environmental Security Technology...fraction of the anomalies as arising from non-hazardous items that could be safely left in the ground. Of particular note, the contractor EM -61-MK2 cart...use of classification metrics applied to production quality EM - 61 data, it was possible to significantly reduce the number of clutter items excavated

Quantification of visual clutter using a computation model of human perception : an application for head-up displays

DOT National Transportation Integrated Search

2004-03-20

A means of quantifying the cluttering effects of symbols is needed to evaluate the impact of displaying an increasing volume of information on aviation displays such as head-up displays. Human visual perception has been successfully modeled by algori...

Anomaly clustering in hyperspectral images

NASA Astrophysics Data System (ADS)

Doster, Timothy J.; Ross, David S.; Messinger, David W.; Basener, William F.

2009-05-01

The topological anomaly detection algorithm (TAD) differs from other anomaly detection algorithms in that it uses a topological/graph-theoretic model for the image background instead of modeling the image with a Gaussian normal distribution. In the construction of the model, TAD produces a hard threshold separating anomalous pixels from background in the image. We build on this feature of TAD by extending the algorithm so that it gives a measure of the number of anomalous objects, rather than the number of anomalous pixels, in a hyperspectral image. This is done by identifying, and integrating, clusters of anomalous pixels via a graph theoretical method combining spatial and spectral information. The method is applied to a cluttered HyMap image and combines small groups of pixels containing like materials, such as those corresponding to rooftops and cars, into individual clusters. This improves visualization and interpretation of objects.

Motion detection, novelty filtering, and target tracking using an interferometric technique with a GaAs phase conjugate mirror

NASA Technical Reports Server (NTRS)

Cheng, Li-Jen (Inventor); Liu, Tsuen-Hsi (Inventor)

1990-01-01

A method and apparatus is disclosed for detecting and tracking moving objects in a noise environment cluttered with fast-and slow-moving objects and other time-varying background. A pair of phase conjugate light beams carrying the same spatial information commonly cancel each other out through an image subtraction process in a phase conjugate interferometer, wherein gratings are formed in a fast photo-refractive phase conjugate mirror material. In the steady state, there is no output. When the optical path of one of the two phase conjugate beams is suddenly changed, the return beam loses its phase conjugate nature and the inter-ferometer is out of balance, resulting in an observable output. The observable output lasts until the phase conjugate nature of the beam has recovered. The observable time of the output signal is roughly equal to the formation time of the grating. If the optical path changing time is slower than the formation time, the change of optical path becomes unobservable, because the index grating can follow the change. Thus, objects traveling at speeds which result in a path changing time which is slower than the formation time are not observable and do not clutter the output image view.

Low-resolution ship detection from high-altitude aerial images

NASA Astrophysics Data System (ADS)

Qi, Shengxiang; Wu, Jianmin; Zhou, Qing; Kang, Minyang

2018-02-01

Ship detection from optical images taken by high-altitude aircrafts such as unmanned long-endurance airships and unmanned aerial vehicles has broad applications in marine fishery management, ship monitoring and vessel salvage. However, the major challenge is the limited capability of information processing on unmanned high-altitude platforms. Furthermore, in order to guarantee the wide detection range, unmanned aircrafts generally cruise at high altitudes, resulting in imagery with low-resolution targets and strong clutters suffered by heavy clouds. In this paper, we propose a low-resolution ship detection method to extract ships from these high-altitude optical images. Inspired by a recent research on visual saliency detection indicating that small salient signals could be well detected by a gradient enhancement operation combined with Gaussian smoothing, we propose the facet kernel filtering to rapidly suppress cluttered backgrounds and delineate candidate target regions from the sea surface. Then, the principal component analysis (PCA) is used to compute the orientation of the target axis, followed by a simplified histogram of oriented gradient (HOG) descriptor to characterize the ship shape property. Finally, support vector machine (SVM) is applied to discriminate real targets and false alarms. Experimental results show that the proposed method actually has high efficiency in low-resolution ship detection.

Writer identification on historical Glagolitic documents

NASA Astrophysics Data System (ADS)

Fiel, Stefan; Hollaus, Fabian; Gau, Melanie; Sablatnig, Robert

2013-12-01

This work aims at automatically identifying scribes of historical Slavonic manuscripts. The quality of the ancient documents is partially degraded by faded-out ink or varying background. The writer identification method used is based on image features, which are described with Scale Invariant Feature Transform (SIFT) features. A visual vocabulary is used for the description of handwriting characteristics, whereby the features are clustered using a Gaussian Mixture Model and employing the Fisher kernel. The writer identification approach is originally designed for grayscale images of modern handwritings. But contrary to modern documents, the historical manuscripts are partially corrupted by background clutter and water stains. As a result, SIFT features are also found on the background. Since the method shows also good results on binarized images of modern handwritings, the approach was additionally applied on binarized images of the ancient writings. Experiments show that this preprocessing step leads to a significant performance increase: The identification rate on binarized images is 98.9%, compared to an identification rate of 87.6% gained on grayscale images.

Path Planning for Non-Circular, Non-Holonomic Robots in Highly Cluttered Environments.

PubMed

Samaniego, Ricardo; Lopez, Joaquin; Vazquez, Fernando

2017-08-15

This paper presents an algorithm for finding a solution to the problem of planning a feasible path for a slender autonomous mobile robot in a large and cluttered environment. The presented approach is based on performing a graph search on a kinodynamic-feasible lattice state space of high resolution; however, the technique is applicable to many search algorithms. With the purpose of allowing the algorithm to consider paths that take the robot through narrow passes and close to obstacles, high resolutions are used for the lattice space and the control set. This introduces new challenges because one of the most computationally expensive parts of path search based planning algorithms is calculating the cost of each one of the actions or steps that could potentially be part of the trajectory. The reason for this is that the evaluation of each one of these actions involves convolving the robot's footprint with a portion of a local map to evaluate the possibility of a collision, an operation that grows exponentially as the resolution is increased. The novel approach presented here reduces the need for these convolutions by using a set of offline precomputed maps that are updated, by means of a partial convolution, as new information arrives from sensors or other sources. Not only does this improve run-time performance, but it also provides support for dynamic search in changing environments. A set of alternative fast convolution methods are also proposed, depending on whether the environment is cluttered with obstacles or not. Finally, we provide both theoretical and experimental results from different experiments and applications.

Microvascular flow estimation by contrast-assisted ultrasound B-scan and statistical parametric images.

PubMed

Tsui, Po-Hsiang; Yeh, Chih-Kuang; Chang, Chien-Cheng

2009-05-01

The microbubbles destruction/replenishment technique has been previously applied to estimating blood flow in the microcirculation. The rate of increase of the time-intensity curve (TIC) due to microbubbles flowing into the region of interest (ROI), as measured from B-mode images, closely reflects the flow velocity. In previous studies, we proposed a new approach called the time-Nakagami-parameter curve (TNC) obtained from Nakagami images to monitor microbubble replenishment for quantifying the microvascular flow velocity. This study aimed to further explore some effects that may affect the TNC to estimate the microflow, including microbubble concentration, ultrasound transmitting energy, attenuation, intrinsic noise, and tissue clutter. In order to well control each effect production, we applied a typical simulation method to investigate the TIC and TNC. The rates of increase of the TIC and TNC were expressed by the rate constants beta(I) and beta(N), respectively, of a monoexponential model. The results show that beta(N) quantifies the microvascular flow velocity similarly to the conventional beta(I) . Moreover, the measures of beta(I) and beta(N) are not influenced by microbubble concentration, transducer excitation energy, and attenuation effect. Although the effect of intrinsic signals contributed by noise and blood would influence the TNC behavior, the TNC method has a better tolerance of tissue clutter than the TIC does, allowing the presence of some clutter components in the ROI. The results suggest that the TNC method can be used as a complementary tool for the conventional TIC to reduce the wall filter requirements for blood flow measurement in the microcirculation.

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.

Joint Target Detection and Tracking Filter for Chilbolton Advanced Meteorological Radar Data Processing

NASA Astrophysics Data System (ADS)

Pak, A.; Correa, J.; Adams, M.; Clark, D.; Delande, E.; Houssineau, J.; Franco, J.; Frueh, C.

2016-09-01

Recently, the growing number of inactive Resident Space Objects (RSOs), or space debris, has provoked increased interest in the field of Space Situational Awareness (SSA) and various investigations of new methods for orbital object tracking. In comparison with conventional tracking scenarios, state estimation of an orbiting object entails additional challenges, such as orbit determination and orbital state and covariance propagation in the presence of highly nonlinear system dynamics. The sensors which are available for detecting and tracking space debris are prone to multiple clutter measurements. Added to this problem, is the fact that it is unknown whether or not a space debris type target is present within such sensor measurements. Under these circumstances, traditional single-target filtering solutions such as Kalman Filters fail to produce useful trajectory estimates. The recent Random Finite Set (RFS) based Finite Set Statistical (FISST) framework has yielded filters which are more appropriate for such situations. The RFS based Joint Target Detection and Tracking (JoTT) filter, also known as the Bernoulli filter, is a single target, multiple measurements filter capable of dealing with cluttered and time-varying backgrounds as well as modeling target appearance and disappearance in the scene. Therefore, this paper presents the application of the Gaussian mixture-based JoTT filter for processing measurements from Chilbolton Advanced Meteorological Radar (CAMRa) which contain both defunct and operational satellites. The CAMRa is a fully-steerable radar located in southern England, which was recently modified to be used as a tracking asset in the European Space Agency SSA program. The experiments conducted show promising results regarding the capability of such filters in processing cluttered radar data. The work carried out in this paper was funded by the USAF Grant No. FA9550-15-1-0069, Chilean Conicyt - Fondecyt grant number 1150930, EU Erasmus Mundus MSc Scholarship, Defense Science and Technology Laboratory (DSTL), U. K., and the Chilean Conicyt, Fondecyt project grant number 1150930.

Analysis and Modeling of Multistatic Clutter and Reverberation and Support for the FORA

DTIC Science & Technology

2015-09-30

experiments, the 2014 Nordic Seas experiment. The PI’s technical objectives for the experiment are to characterize and model multistatic bottom clutter... Nordic Seas experiments, as well as other efforts as directed by ONR-OA. APPROACH There is a 6-year ONR OA plan for three large experiments

The estimation of lower refractivity uncertainty from radar sea clutter using the Bayesian—MCMC method

NASA Astrophysics Data System (ADS)

Sheng, Zheng

2013-02-01

The estimation of lower atmospheric refractivity from radar sea clutter (RFC) is a complicated nonlinear optimization problem. This paper deals with the RFC problem in a Bayesian framework. It uses the unbiased Markov Chain Monte Carlo (MCMC) sampling technique, which can provide accurate posterior probability distributions of the estimated refractivity parameters by using an electromagnetic split-step fast Fourier transform terrain parabolic equation propagation model within a Bayesian inversion framework. In contrast to the global optimization algorithm, the Bayesian—MCMC can obtain not only the approximate solutions, but also the probability distributions of the solutions, that is, uncertainty analyses of solutions. The Bayesian—MCMC algorithm is implemented on the simulation radar sea-clutter data and the real radar sea-clutter data. Reference data are assumed to be simulation data and refractivity profiles are obtained using a helicopter. The inversion algorithm is assessed (i) by comparing the estimated refractivity profiles from the assumed simulation and the helicopter sounding data; (ii) the one-dimensional (1D) and two-dimensional (2D) posterior probability distribution of solutions.

Buried landmine detection using multivariate normal clustering

NASA Astrophysics Data System (ADS)

Duston, Brian M.

2001-10-01

A Bayesian classification algorithm is presented for discriminating buried land mines from buried and surface clutter in Ground Penetrating Radar (GPR) signals. This algorithm is based on multivariate normal (MVN) clustering, where feature vectors are used to identify populations (clusters) of mines and clutter objects. The features are extracted from two-dimensional images created from ground penetrating radar scans. MVN clustering is used to determine the number of clusters in the data and to create probability density models for target and clutter populations, producing the MVN clustering classifier (MVNCC). The Bayesian Information Criteria (BIC) is used to evaluate each model to determine the number of clusters in the data. An extension of the MVNCC allows the model to adapt to local clutter distributions by treating each of the MVN cluster components as a Poisson process and adaptively estimating the intensity parameters. The algorithm is developed using data collected by the Mine Hunter/Killer Close-In Detector (MH/K CID) at prepared mine lanes. The Mine Hunter/Killer is a prototype mine detecting and neutralizing vehicle developed for the U.S. Army to clear roads of anti-tank mines.

Evaluation of intensified image enhancement through conspicuity and triangle orientation discrimination measures

NASA Astrophysics Data System (ADS)

Dijk, Judith; van Eekeren, Adam W. M.; Toet, Alexander; den Hollander, Richard J. M.; Schutte, Klamer; van Heijningen, Ad W. P.; Bijl, Piet

2013-04-01

For many military operations, situational awareness is of great importance. During night conditions, this situational awareness can be improved using both analog and digital image-intensified cameras. The quality of image intensifiers is a topic of interest. One of the differences between a digital and analog system is noise behavior. For digital image intensifiers, the noise behavior is not as good as for analog image intensifiers, but it can be improved using noise-reduction techniques. In this paper, the improvement using temporal noise reduction and local adaptive contrast enhancement is shown and quantitatively evaluated by subjective measurement of the conspicuity and triangle orientation discrimination (TOD). The results of the conspicuity and TOD experiments are consistent with each other. The highest improvement is found for a low-clutter environment; for medium- and high-clutter environments, the improvement is less. This can be explained by the fact that image enhancement increases contrast of all image details, irrespective of whether they are targets or clutter. For low-clutter image enhancement, target conspicuity and target detection improvement will be largest, since there are not many distracting elements.

Feature-based RNN target recognition

NASA Astrophysics Data System (ADS)

Bakircioglu, Hakan; Gelenbe, Erol

1998-09-01

Detection and recognition of target signatures in sensory data obtained by synthetic aperture radar (SAR), forward- looking infrared, or laser radar, have received considerable attention in the literature. In this paper, we propose a feature based target classification methodology to detect and classify targets in cluttered SAR images, that makes use of selective signature data from sensory data, together with a neural network technique which uses a set of trained networks based on the Random Neural Network (RNN) model (Gelenbe 89, 90, 91, 93) which is trained to act as a matched filter. We propose and investigate radial features of target shapes that are invariant to rotation, translation, and scale, to characterize target and clutter signatures. These features are then used to train a set of learning RNNs which can be used to detect targets within clutter with high accuracy, and to classify the targets or man-made objects from natural clutter. Experimental data from SAR imagery is used to illustrate and validate the proposed method, and to calculate Receiver Operating Characteristics which illustrate the performance of the proposed algorithm.

A novel imaging technique based on the spatial coherence of backscattered waves: demonstration in the presence of acoustical clutter

NASA Astrophysics Data System (ADS)

Dahl, Jeremy J.; Pinton, Gianmarco F.; Lediju, Muyinatu; Trahey, Gregg E.

2011-03-01

In the last 20 years, the number of suboptimal and inadequate ultrasound exams has increased. This trend has been linked to the increasing population of overweight and obese individuals. The primary causes of image degradation in these individuals are often attributed to phase aberration and clutter. Phase aberration degrades image quality by distorting the transmitted and received pressure waves, while clutter degrades image quality by introducing incoherent acoustical interference into the received pressure wavefront. Although significant research efforts have pursued the correction of image degradation due to phase aberration, few efforts have characterized or corrected image degradation due to clutter. We have developed a novel imaging technique that is capable of differentiating ultrasonic signals corrupted by acoustical interference. The technique, named short-lag spatial coherence (SLSC) imaging, is based on the spatial coherence of the received ultrasonic wavefront at small spatial distances across the transducer aperture. We demonstrate comparative B-mode and SLSC images using full-wave simulations that include the effects of clutter and show that SLSC imaging generates contrast-to-noise ratios (CNR) and signal-to-noise ratios (SNR) that are significantly better than B-mode imaging under noise-free conditions. In the presence of noise, SLSC imaging significantly outperforms conventional B-mode imaging in all image quality metrics. We demonstrate the use of SLSC imaging in vivo and compare B-mode and SLSC images of human thyroid and liver.

Magneto-Radar Hidden Metal Detector

DOEpatents

McEwan, Thomas E.

2005-07-05

A varying magnetic field excites slight vibrations in an object and a radar sensor detects the vibrations at a harmonic of the excitation frequency. The synergy of the magnetic excitation and radar detection provides increased detection range compared to conventional magnetic metal detectors. The radar rejects background clutter by responding only to reflecting objects that are vibrating at a harmonic excitation field, thereby significantly improving detection reliability. As an exemplary arrangement, an ultra-wideband micropower impulse radar (MIR) is capable of being employed to provide superior materials penetration while providing range information. The magneto-radar may be applied to pre-screening magnetic resonance imaging (MRI) patients, landmine detection and finding hidden treasures.

Breaking through the Advertising Clutter: A Qualitative Analysis of Broken Stereotypes in Print and Television Advertisements.

ERIC Educational Resources Information Center

Larson, Charles U.

As a result of the overwhelming amount of print and electronic advertisements which compete for consumer attention, advertisers must find effective methods to get through the ad clutter and capture their audience's interest. Several tactics can accomplish this strategy, including the tactic of breaking or reversing audience expectations or…

Measuring Search Efficiency in Complex Visual Search Tasks: Global and Local Clutter

ERIC Educational Resources Information Center

Beck, Melissa R.; Lohrenz, Maura C.; Trafton, J. Gregory

2010-01-01

Set size and crowding affect search efficiency by limiting attention for recognition and attention against competition; however, these factors can be difficult to quantify in complex search tasks. The current experiments use a quantitative measure of the amount and variability of visual information (i.e., clutter) in highly complex stimuli (i.e.,…

Target and Clutter Scattering and their Effects on Military Radar Performance: Electromagnetic Wave Propagation Panel Specialists Meeting Held in Ottawa, Canada on 6-9 May 1991 (Diffraction par les Cibles et le Fouillis et ses Effets sur les Performances des Radars Militaires)

DTIC Science & Technology

1991-09-01

In subsequent discussions, we shall classify a clutter process to be 2-7 predominantly Rayleigh if the value of f is less than 0.8, and the Pfa ...classified as "others’, the Pfa vs threshold curve , is closer to the Ricean model than to the Rayleigh model, and the value of the parameter 0 was usually...better, and for precipitation clutter the lattice was 4 to approximation of "...equally likely". PD and PFA are 6 dB bettor, here specified a 0.5 and 0.01

Signal-processing analysis of the MC2823 radar fuze: an addendum concerning clutter effects

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

Jelinek, D.A.

1978-07-01

A detailed analysis of the signal processing of the MC2823 radar fuze was published by Thompson in 1976 which enabled the computation of dud probability versus signal-to-noise ratio where the noise was receiver noise. An addendum to Thompson's work was published by Williams in 1978 that modified the weighting function used by Thompson. The analysis presented herein extends the work of Thompson to include the effects of clutter (the non-signal portion of the echo from a terrain) using the new weighting function. This extension enables computation of dud probability versus signal-to-total-noise ratio where total noise is the sum of themore » receiver-noise power and the clutter power.« less

Information transfer rate with serial and simultaneous visual display formats

NASA Astrophysics Data System (ADS)

Matin, Ethel; Boff, Kenneth R.

1988-04-01

Information communication rate for a conventional display with three spatially separated windows was compared with rate for a serial display in which data frames were presented sequentially in one window. For both methods, each frame contained a randomly selected digit with various amounts of additional display 'clutter.' Subjects recalled the digits in a prescribed order. Large rate differences were found, with faster serial communication for all levels of the clutter factors. However, the rate difference was most pronounced for highly cluttered displays. An explanation for the latter effect in terms of visual masking in the retinal periphery was supported by the results of a second experiment. The working hypothesis that serial displays can speed information transfer for automatic but not for controlled processing is discussed.

Motion Tolerant Unfocused Imaging of Physiological Waveforms for Blood Pressure Waveform Estimation Using Ultrasound.

PubMed

Seo, Joohyun; Pietrangelo, Sabino J; Sodini, Charles G; Lee, Hae-Seung

2018-05-01

This paper details unfocused imaging using single-element ultrasound transducers for motion tolerant arterial blood pressure (ABP) waveform estimation. The ABP waveform is estimated based on pulse wave velocity and arterial pulsation through Doppler and M-mode ultrasound. This paper discusses approaches to mitigate the effect of increased clutter due to unfocused imaging on blood flow and diameter waveform estimation. An intensity reduction model (IRM) estimator is described to track the change of diameter, which outperforms a complex cross-correlation model (C3M) estimator in low contrast environments. An adaptive clutter filtering approach is also presented, which reduces the increased Doppler angle estimation error due to unfocused imaging. Experimental results in a flow phantom demonstrate that flow velocity and diameter waveforms can be reliably measured with wide lateral offsets of the transducer position. The distension waveform estimated from human carotid M-mode imaging using the IRM estimator shows physiological baseline fluctuations and 0.6-mm pulsatile diameter change on average, which is within the expected physiological range. These results show the feasibility of this low cost and portable ABP waveform estimation device.

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.

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.

Image retrieval by information fusion based on scalable vocabulary tree and robust Hausdorff distance

NASA Astrophysics Data System (ADS)

Che, Chang; Yu, Xiaoyang; Sun, Xiaoming; Yu, Boyang

2017-12-01

In recent years, Scalable Vocabulary Tree (SVT) has been shown to be effective in image retrieval. However, for general images where the foreground is the object to be recognized while the background is cluttered, the performance of the current SVT framework is restricted. In this paper, a new image retrieval framework that incorporates a robust distance metric and information fusion is proposed, which improves the retrieval performance relative to the baseline SVT approach. First, the visual words that represent the background are diminished by using a robust Hausdorff distance between different images. Second, image matching results based on three image signature representations are fused, which enhances the retrieval precision. We conducted intensive experiments on small-scale to large-scale image datasets: Corel-9, Corel-48, and PKU-198, where the proposed Hausdorff metric and information fusion outperforms the state-of-the-art methods by about 13, 15, and 15%, respectively.

Figure-ground representation and its decay in primary visual cortex.

PubMed

Strother, Lars; Lavell, Cheryl; Vilis, Tutis

2012-04-01

We used fMRI to study figure-ground representation and its decay in primary visual cortex (V1). Human observers viewed a motion-defined figure that gradually became camouflaged by a cluttered background after it stopped moving. V1 showed positive fMRI responses corresponding to the moving figure and negative fMRI responses corresponding to the static background. This positive-negative delineation of V1 "figure" and "background" fMRI responses defined a retinotopically organized figure-ground representation that persisted after the figure stopped moving but eventually decayed. The temporal dynamics of V1 "figure" and "background" fMRI responses differed substantially. Positive "figure" responses continued to increase for several seconds after the figure stopped moving and remained elevated after the figure had disappeared. We propose that the sustained positive V1 "figure" fMRI responses reflected both persistent figure-ground representation and sustained attention to the location of the figure after its disappearance, as did subjects' reports of persistence. The decreasing "background" fMRI responses were relatively shorter-lived and less biased by spatial attention. Our results show that the transition from a vivid figure-ground percept to its disappearance corresponds to the concurrent decay of figure enhancement and background suppression in V1, both of which play a role in form-based perceptual memory.

Cognitive software defined radar: waveform design for clutter and interference suppression

NASA Astrophysics Data System (ADS)

Kirk, Benjamin H.; Owen, Jonathan W.; Narayanan, Ram M.; Blunt, Shannon D.; Martone, Anthony F.; Sherbondy, Kelly D.

2017-05-01

Clutter and radio frequency interference (RFI) are prevalent issues in the field of radar and are specifically of interest to of cognitive radar. Here, methods for applying and testing the utility of cognitive radar for clutter and RFI mitigation are explored. Using the adaptable transmit capability, environmental database, and general "awareness" of a cognitive radar system (i.e. spectrum sensing, geographical location, etc.), a matched waveform is synthesized that improves the signal-to-clutter ratio (SCR), assuming at least an estimate of the target response and the environmental clutter response are known a prior i. RFI may also be mitigated by sensing the RF spectrum and adapting the transmit center frequency and bandwidth using methods that optimize bandwidth and signal-to-interference plus noise ratio (SINR) (i.e. the spectrum sensing, multi-objective (SS-MO) algorithm). The improvement is shown by a decrease in the noise floor. The above methods' effectiveness are examined via a test-bed developed around a software defined radio (SDR). Testing and the general use of commercial off the shelf (COTS) devices are desirable for their cost effectiveness, general ease of use, as well as technical and community support, but these devices provide design challenges in order to be effective. The universal software radio peripheral (USRP) X310 SDR is a relatively cheap and portable device that has all the system components of a basic cognitive radar. Design challenges of the SDR include phase coherency between channels, bandwidth limitations, dynamic range, and speed of computation and data communication / recording.

Model studies of surface noise interference in ground-probing radar

NASA Astrophysics Data System (ADS)

Arcone, S. A.; Delaney, A. J.

1985-11-01

Ground-probing radar can be an effective tool for exploring the top 10 to 20 m of ground, especially in cold regions where the freezing of water decreases signal absorption. However, the large electrical variability of the surface, combined with the short wavelengths used, can often cause severe ground clutter that can mask a desired, deeper return. In this study a model facility was constructed consisting of a metallic reflector covered by sand. Troughs of saturated sand were emplaced at the surface to carry surface electrical properties and to act as a noise source to interfere with the bottom reflections. Antenna polarization and height, and signal stacking in both static (antennas stationary) and dynamic (antennas moving) modes were then investigated as methods for reducing the surface clutter. Polarization parallel to the profile direction (perpendicular to the troughs' axes) gave profiles superior to the perpendicular case because of the dimensional sensitivity of the antenna radiation. Dynamic stacking greatly improved the signal-to-noise ratio because noise sources were averaged as the antennas moved, while the desired reflector, buried at constant depth, was enhanced. Raising the antennas above the surface also reduced noise because the surface area over which reflections were integrated increased. All three noise reduction techniques could be effective in surveys for reflectors at nearly constant depth such as groundwater tables or ice/water interfaces.

DRFM Cordic Processor and Sea Clutter Modeling for Enhancing Structured False Target Synthesis

DTIC Science & Technology

2017-09-01

was implemented using the Verilog hardware description language. The second investigation concerns generating sea clutter to impose on the false target...to achieve accuracy at 5.625o. The resulting design was implemented using the Verilog hardware description language. The second investigation...33 3. Initialization of the Angle Accumulator ....................................34 4. Design Methodology for I/Q Phase

Flight Control in Complex Environments

DTIC Science & Technology

2016-10-24

that allow insects, with their miniature brains and limited sensory systems to fly safely through cluttered natural environments . The most significant...specialisations that allow insects, with their miniature brains and limited sensory systems to fly safely through cluttered natural environments . The most...bees have developed more accurate or effective methods for flying safely through gaps than species from less complex environments . Fig. 4: The

Combatting Inherent Vulnerabilities of CFAR Algorithms and a New Robust CFAR Design

DTIC Science & Technology

1993-09-01

elements of any automatic radar system. Unfortunately, CFAR systems are inherently vulnerable to degradation caused by large clutter edges, multiple ...edges, multiple targets, and electronic countermeasures (ECM) environments. 20 Distribution, Availability of Abstract 21 Abstract Security...inherently vulnerable to degradation caused by large clutter edges, multiple targets and jamming environments. This thesis presents eight popular and studied

Ship Detection in Gaofen-3 SAR Images Based on Sea Clutter Distribution Analysis and Deep Convolutional Neural Network

PubMed Central

You, Hongjian

2018-01-01

Target detection is one of the important applications in the field of remote sensing. The Gaofen-3 (GF-3) Synthetic Aperture Radar (SAR) satellite launched by China is a powerful tool for maritime monitoring. This work aims at detecting ships in GF-3 SAR images using a new land masking strategy, the appropriate model for sea clutter and a neural network as the discrimination scheme. Firstly, the fully convolutional network (FCN) is applied to separate the sea from the land. Then, by analyzing the sea clutter distribution in GF-3 SAR images, we choose the probability distribution model of Constant False Alarm Rate (CFAR) detector from K-distribution, Gamma distribution and Rayleigh distribution based on a tradeoff between the sea clutter modeling accuracy and the computational complexity. Furthermore, in order to better implement CFAR detection, we also use truncated statistic (TS) as a preprocessing scheme and iterative censoring scheme (ICS) for boosting the performance of detector. Finally, we employ a neural network to re-examine the results as the discrimination stage. Experiment results on three GF-3 SAR images verify the effectiveness and efficiency of this approach. PMID:29364194

Ship Detection in Gaofen-3 SAR Images Based on Sea Clutter Distribution Analysis and Deep Convolutional Neural Network.

PubMed

An, Quanzhi; Pan, Zongxu; You, Hongjian

2018-01-24

Target detection is one of the important applications in the field of remote sensing. The Gaofen-3 (GF-3) Synthetic Aperture Radar (SAR) satellite launched by China is a powerful tool for maritime monitoring. This work aims at detecting ships in GF-3 SAR images using a new land masking strategy, the appropriate model for sea clutter and a neural network as the discrimination scheme. Firstly, the fully convolutional network (FCN) is applied to separate the sea from the land. Then, by analyzing the sea clutter distribution in GF-3 SAR images, we choose the probability distribution model of Constant False Alarm Rate (CFAR) detector from K-distribution, Gamma distribution and Rayleigh distribution based on a tradeoff between the sea clutter modeling accuracy and the computational complexity. Furthermore, in order to better implement CFAR detection, we also use truncated statistic (TS) as a preprocessing scheme and iterative censoring scheme (ICS) for boosting the performance of detector. Finally, we employ a neural network to re-examine the results as the discrimination stage. Experiment results on three GF-3 SAR images verify the effectiveness and efficiency of this approach.

Application of musical timbre discrimination features to active sonar classification

NASA Astrophysics Data System (ADS)

Young, Victor W.; Hines, Paul C.; Pecknold, Sean

2005-04-01

In musical acoustics significant effort has been devoted to uncovering the physical basis of timbre perception. Most investigations into timbre rely on multidimensional scaling (MDS), in which different musical sounds are arranged as points in multidimensional space. The Euclidean distance between points corresponds to the perceptual distance between sounds and the multidimensional axes are linked to measurable properties of the sounds. MDS has identified numerous temporal and spectral features believed to be important to timbre perception. There is reason to believe that some of these features may have wider application in the disparate field of underwater acoustics, since anecdotal evidence suggests active sonar returns from metallic objects sound different than natural clutter returns when auralized by human operators. This is particularly encouraging since attempts to develop robust automatic classifiers capable of target-clutter discrimination over a wide range of operational conditions have met with limited success. Spectral features relevant to target-clutter discrimination are believed to include click-pitch and envelope irregularity; relevant temporal features are believed to include duration, sub-band attack/decay time, and time separation pitch. Preliminary results from an investigation into the role of these timbre features in target-clutter discrimination will be presented. [Work supported by NSERC and GDC.

A simulation study of fast neutron interrogation for standoff detection of improvised explosive devices

NASA Astrophysics Data System (ADS)

Heider, S. A.; Dunn, W. L.

2015-11-01

The signature-based radiation-scanning technique utilizes radiation detector responses, called "signatures," and compares these to "templates" in order to differentiate targets that contain certain materials, such as explosives or drugs, from those that do not. Our investigations are aimed at the detection of nitrogen-rich explosives contained in improvised explosive devices. We use the term "clutter" to refer to any non-explosive materials with which the interrogating radiation may interact between source and detector. To deal with the many target types and clutter configurations that may be encountered in the field, the use of "artificial templates" is proposed. The MCNP code was used to simulate 14.1 MeV neutron source beams incident on one type of target containing various clutter and sample materials. Signatures due to inelastic-scatter and prompt-capture gamma rays from hydrogen, carbon, nitrogen, and oxygen and two scattered neutron signatures were considered. Targets containing explosive materials in the presence of clutter were able to be identified from targets that contained only non-explosive ("inert") materials. This study demonstrates that a finite number of artificial templates is sufficient for IED detection with fairly good sensitivity and specificity.

Signal-to-solar clutter calculations of AK-47 muzzle flash at various spectral bandpasses near the potassium D1/D2 doublet

NASA Astrophysics Data System (ADS)

Klett, Karl K., Jr.

2010-04-01

An analysis was performed, using MODTRAN, to determine the best filters to use for detecting the muzzle flash of an AK-47 in daylight conditions in the desert. Filters with bandwidths of 0.05, 0.1, 0.5, 1.0, 3.0, and 5.0 nanometers (nm) were analyzed to understand how the optical bandwidth affects the signal-to-solar clutter ratio. These filters were evaluated near the potassium D1 and D2 doublet emission lines that occur at 769.89 and 766.49 nm respectively that are observed where projectile propellants are used. The maximum spectral radiance, from the AK-47 muzzle flash, is 1.88 x 10-2 W/cm2 str micron, and is approximately equal to the daytime atmospheric spectral radiance. The increased emission, due to the potassium doublet lines, and decreased atmospheric transmission, due to oxygen absorption, combine to create a condition where the signal-to-solar clutter ratio is greater than 1. The 3 nm filter, has a signal-to-solar clutter ratio of 2.09 when centered at 765.37 nm and provides the best combination of both cost and signal sensitivity.

Spread-Spectrum Beamforming and Clutter Filtering for Plane-Wave Color Doppler Imaging.

PubMed

Mansour, Omar; Poepping, Tamie L; Lacefield, James C

2016-07-21

Plane-wave imaging is desirable for its ability to achieve high frame rates, allowing the capture of fast dynamic events and continuous Doppler data. In most implementations of plane-wave imaging, multiple low-resolution images from different plane wave tilt angles are compounded to form a single high-resolution image, thereby reducing the frame rate. Compounding improves the lateral beam profile in the high-resolution image, but it also acts as a low-pass filter in slow time that causes attenuation and aliasing of signals with high Doppler shifts. This paper introduces a spread-spectrum color Doppler imaging method that produces high-resolution images without the use of compounding, thereby eliminating the tradeoff between beam quality, maximum unaliased Doppler frequency, and frame rate. The method uses a long, random sequence of transmit angles rather than a linear sweep of plane wave directions. The random angle sequence randomizes the phase of off-focus (clutter) signals, thereby spreading the clutter power in the Doppler spectrum, while keeping the spectrum of the in-focus signal intact. The ensemble of randomly tilted low-resolution frames also acts as the Doppler ensemble, so it can be much longer than a conventional linear sweep, thereby improving beam formation while also making the slow-time Doppler sampling frequency equal to the pulse repetition frequency. Experiments performed using a carotid artery phantom with constant flow demonstrate that the spread-spectrum method more accurately measures the parabolic flow profile of the vessel and outperforms conventional plane-wave Doppler in both contrast resolution and estimation of high flow velocities. The spread-spectrum method is expected to be valuable for Doppler applications that require measurement of high velocities at high frame rates.

Semantic priming from crowded words.

PubMed

Yeh, Su-Ling; He, Sheng; Cavanagh, Patrick

2012-06-01

Vision in a cluttered scene is extremely inefficient. This damaging effect of clutter, known as crowding, affects many aspects of visual processing (e.g., reading speed). We examined observers' processing of crowded targets in a lexical decision task, using single-character Chinese words that are compact but carry semantic meaning. Despite being unrecognizable and indistinguishable from matched nonwords, crowded prime words still generated robust semantic-priming effects on lexical decisions for test words presented in isolation. Indeed, the semantic-priming effect of crowded primes was similar to that of uncrowded primes. These findings show that the meanings of words survive crowding even when the identities of the words do not, suggesting that crowding does not prevent semantic activation, a process that may have evolved in the context of a cluttered visual environment.

Multispectral Terrain Background Simulation Techniques For Use In Airborne Sensor Evaluation

NASA Astrophysics Data System (ADS)

Weinberg, Michael; Wohlers, Ronald; Conant, John; Powers, Edward

1988-08-01

A background simulation code developed at Aerodyne Research, Inc., called AERIE is designed to reflect the major sources of clutter that are of concern to staring and scanning sensors of the type being considered for various airborne threat warning (both aircraft and missiles) sensors. The code is a first principles model that could be used to produce a consistent image of the terrain for various spectral bands, i.e., provide the proper scene correlation both spectrally and spatially. The code utilizes both topographic and cultural features to model terrain, typically from DMA data, with a statistical overlay of the critical underlying surface properties (reflectance, emittance, and thermal factors) to simulate the resulting texture in the scene. Strong solar scattering from water surfaces is included with allowance for wind driven surface roughness. Clouds can be superimposed on the scene using physical cloud models and an analytical representation of the reflectivity obtained from scattering off spherical particles. The scene generator is augmented by collateral codes that allow for the generation of images at finer resolution. These codes provide interpolation of the basic DMA databases using fractal procedures that preserve the high frequency power spectral density behavior of the original scene. Scenes are presented illustrating variations in altitude, radiance, resolution, material, thermal factors, and emissivities. The basic models utilized for simulation of the various scene components and various "engineering level" approximations are incorporated to reduce the computational complexity of the simulation.

High duty cycle echolocation and prey detection by bats.

PubMed

Lazure, Louis; Fenton, M Brock

2011-04-01

There are two very different approaches to laryngeal echolocation in bats. Although most bats separate pulse and echo in time by signalling at low duty cycles (LDCs), almost 20% of species produce calls at high duty cycles (HDCs) and separate pulse and echo in frequency. HDC echolocators are sensitive to Doppler shifts. HDC echolocation is well suited to detecting fluttering targets such as flying insects against a cluttered background. We used two complementary experiments to evaluate the relative effectiveness of LDC and HDC echolocation for detecting fluttering prey. We measured echoes from fluttering targets by broadcasting artificial bat calls, and found that echo amplitude was greatest for sounds similar to those used in HDC echolocation. We also collected field recordings of syntopic LDC and HDC bats approaching an insect-like fluttering target and found that HDC bats approached the target more often (18.6% of passes) than LDC bats (1.2% of passes). Our results suggest that some echolocation call characteristics, particularly duty cycle and pulse duration, translate into improved ability to detect fluttering targets in clutter, and that HDC echolocation confers a superior ability to detect fluttering prey in the forest understory compared with LDC echolocation. The prevalence of moths in the diets of HDC bats, which is often used as support for the allotonic frequency hypothesis, can therefore be partly explained by the better flutter detection ability of HDC bats.

Wavelet-based polarimetry analysis

NASA Astrophysics Data System (ADS)

Ezekiel, Soundararajan; Harrity, Kyle; Farag, Waleed; Alford, Mark; Ferris, David; Blasch, Erik

2014-06-01

Wavelet transformation has become a cutting edge and promising approach in the field of image and signal processing. A wavelet is a waveform of effectively limited duration that has an average value of zero. Wavelet analysis is done by breaking up the signal into shifted and scaled versions of the original signal. The key advantage of a wavelet is that it is capable of revealing smaller changes, trends, and breakdown points that are not revealed by other techniques such as Fourier analysis. The phenomenon of polarization has been studied for quite some time and is a very useful tool for target detection and tracking. Long Wave Infrared (LWIR) polarization is beneficial for detecting camouflaged objects and is a useful approach when identifying and distinguishing manmade objects from natural clutter. In addition, the Stokes Polarization Parameters, which are calculated from 0°, 45°, 90°, 135° right circular, and left circular intensity measurements, provide spatial orientations of target features and suppress natural features. In this paper, we propose a wavelet-based polarimetry analysis (WPA) method to analyze Long Wave Infrared Polarimetry Imagery to discriminate targets such as dismounts and vehicles from background clutter. These parameters can be used for image thresholding and segmentation. Experimental results show the wavelet-based polarimetry analysis is efficient and can be used in a wide range of applications such as change detection, shape extraction, target recognition, and feature-aided tracking.

Short range micro-power impulse radar with high resolution swept range gate with damped transmit and receive cavities

DOEpatents

McEwan, Thomas E.

1998-01-01

A radar range finder and hidden object locator is based on ultra-wide band radar with a high resolution swept range gate. The device generates an equivalent time amplitude scan with atypical range of 4 inches to 20 feet, and an analog range resolution as limited by a jitter of on the order of 0.01 inches. A differential sampling receiver is employed to effectively eliminate ringing and other aberrations induced in the receiver by the near proximity of the transmit antenna, so a background subtraction is not needed, simplifying the circuitry while improving performance. Uses of the invention include a replacement of ultrasound devices for fluid level sensing, automotive radar, such as cruise control and parking assistance, hidden object location, such as stud and rebar finding. Also, this technology can be used when positioned over a highway lane to collect vehicle count and speed data for traffic control. Techniques are used to reduce clutter in the receive signal, such as decoupling the receive and transmit cavities by placing a space between them, using conductive or radiative damping elements on the cavities, and using terminating plates on the sides of the openings.

Short range micro-power impulse radar with high resolution swept range gate with damped transmit and receive cavities

DOEpatents

McEwan, T.E.

1998-06-30

A radar range finder and hidden object locator is based on ultra-wide band radar with a high resolution swept range gate. The device generates an equivalent time amplitude scan with atypical range of 4 inches to 20 feet, and an analog range resolution as limited by a jitter of on the order of 0.01 inches. A differential sampling receiver is employed to effectively eliminate ringing and other aberrations induced in the receiver by the near proximity of the transmit antenna, so a background subtraction is not needed, simplifying the circuitry while improving performance. Uses of the invention include a replacement of ultrasound devices for fluid level sensing, automotive radar, such as cruise control and parking assistance, hidden object location, such as stud and rebar finding. Also, this technology can be used when positioned over a highway lane to collect vehicle count and speed data for traffic control. Techniques are used to reduce clutter in the receive signal, such as decoupling the receive and transmit cavities by placing a space between them, using conductive or radiative damping elements on the cavities, and using terminating plates on the sides of the openings. 20 figs.

Nonstationary EO/IR Clutter Suppression and Dim Object Tracking

DTIC Science & Technology

2010-01-01

Brown, A., and Brown, J., Enhanced Algorithms for EO /IR Electronic Stabilization, Clutter Suppression, and Track - Before - Detect for Multiple Low...estimation-suppression and nonlinear filtering-based multiple-object track - before - detect . These algorithms are suitable for integration into...In such cases, it is imperative to develop efficient real or near-real time tracking before detection methods. This paper continues the work started

Limitation on the use of a spaceborne SAR for rain measurements

NASA Technical Reports Server (NTRS)

Ahamad, Atiq

1994-01-01

A proof-of-concept experiment for remote sensing of precipitation by SAR is part of the SIR-C/X-SAR experiment. This thesis presents a feasibility study and recommendations for detection of precipitation using SIR-C/X-SAR. The principal limitation to rain measurement from a spaceborne SAR is the poor SCR (signal-to-clutter ratio). This is in part due to the system configuration and largely due to the large magnitude of echoes associated with the surface component. Two geometries apply: off-vertical and vertical pointing angles. Here we present calculations for both. With vertical geometry a large clutter component is associated with range sidelobes of the chirped transmitter pulse. To overcome this problem a narrow transmitted pulse (3 mu sec) processed without dechirping was used. Since the magnitude of the clutter over the ocean is high it is recommended that data in the chirped mode be obtained over the forest due to the significantly lower backscatter associated with it at nadir. With these recommendations, at nadir, it is believed that rain rates greater than 5 mm/hr may be detected. The use of a better weighting function that gives lower sidelobe levels than that used (a raised cos(exp 2)) is also recommended. At off-vertical look angles all the range cells have a large clutter component associated with them due to the geometry. The use of higher angles of incidence (theta greater than 60 deg) is recommended because of better SCR at these angles. With this recommendation, at off-vertical, it is believed that rain rates greater than 10 mm/hr may be detected. Various other techniques are described and recommended to improve the minimum detectable precipitation rate. These include trying to subtract the estimate of the clutter from the combined signal and clutter and trying to separate the Doppler of the rain echo and the surface echo. With these recommendations it is believed that it is possible to detect precipitation as low as 1 mm/hr at vertical and greater than 5 mm/hr at off-vertical look angles.

Statistically Self-Consistent and Accurate Errors for SuperDARN Data

NASA Astrophysics Data System (ADS)

Reimer, A. S.; Hussey, G. C.; McWilliams, K. A.

2018-01-01

The Super Dual Auroral Radar Network (SuperDARN)-fitted data products (e.g., spectral width and velocity) are produced using weighted least squares fitting. We present a new First-Principles Fitting Methodology (FPFM) that utilizes the first-principles approach of Reimer et al. (2016) to estimate the variance of the real and imaginary components of the mean autocorrelation functions (ACFs) lags. SuperDARN ACFs fitted by the FPFM do not use ad hoc or empirical criteria. Currently, the weighting used to fit the ACF lags is derived from ad hoc estimates of the ACF lag variance. Additionally, an overcautious lag filtering criterion is used that sometimes discards data that contains useful information. In low signal-to-noise (SNR) and/or low signal-to-clutter regimes the ad hoc variance and empirical criterion lead to underestimated errors for the fitted parameter because the relative contributions of signal, noise, and clutter to the ACF variance is not taken into consideration. The FPFM variance expressions include contributions of signal, noise, and clutter. The clutter is estimated using the maximal power-based self-clutter estimator derived by Reimer and Hussey (2015). The FPFM was successfully implemented and tested using synthetic ACFs generated with the radar data simulator of Ribeiro, Ponomarenko, et al. (2013). The fitted parameters and the fitted-parameter errors produced by the FPFM are compared with the current SuperDARN fitting software, FITACF. Using self-consistent statistical analysis, the FPFM produces reliable or trustworthy quantitative measures of the errors of the fitted parameters. For an SNR in excess of 3 dB and velocity error below 100 m/s, the FPFM produces 52% more data points than FITACF.

A GPU-Parallelized Eigen-Based Clutter Filter Framework for Ultrasound Color Flow Imaging.

PubMed

Chee, Adrian J Y; Yiu, Billy Y S; Yu, Alfred C H

2017-01-01

Eigen-filters with attenuation response adapted to clutter statistics in color flow imaging (CFI) have shown improved flow detection sensitivity in the presence of tissue motion. Nevertheless, its practical adoption in clinical use is not straightforward due to the high computational cost for solving eigendecompositions. Here, we provide a pedagogical description of how a real-time computing framework for eigen-based clutter filtering can be developed through a single-instruction, multiple data (SIMD) computing approach that can be implemented on a graphical processing unit (GPU). Emphasis is placed on the single-ensemble-based eigen-filtering approach (Hankel singular value decomposition), since it is algorithmically compatible with GPU-based SIMD computing. The key algebraic principles and the corresponding SIMD algorithm are explained, and annotations on how such algorithm can be rationally implemented on the GPU are presented. Real-time efficacy of our framework was experimentally investigated on a single GPU device (GTX Titan X), and the computing throughput for varying scan depths and slow-time ensemble lengths was studied. Using our eigen-processing framework, real-time video-range throughput (24 frames/s) can be attained for CFI frames with full view in azimuth direction (128 scanlines), up to a scan depth of 5 cm ( λ pixel axial spacing) for slow-time ensemble length of 16 samples. The corresponding CFI image frames, with respect to the ones derived from non-adaptive polynomial regression clutter filtering, yielded enhanced flow detection sensitivity in vivo, as demonstrated in a carotid imaging case example. These findings indicate that the GPU-enabled eigen-based clutter filtering can improve CFI flow detection performance in real time.

A positioning system with no line-of-sight restrictions for cluttered environments

NASA Astrophysics Data System (ADS)

Prigge, Eric A.

Accurate sensing of vehicle location and attitude is a fundamental requirement in many mobile-robot applications, but is a very challenging problem in the cluttered and unstructured environment of the real world. Many existing indoor positioning systems are limited in workspace and robustness because they require clear lines of sight or do not provide absolute, drift-free measurements. Examples include overhead vision systems, where an unobstructed view must be maintained between robot and camera, and inertial systems, where the measurements drift over time. The research presented in this dissertation provides a new location- and attitude-sensing system designed specifically to meet the challenges of operation in a realistic, cluttered indoor environment, such as that of an office building or warehouse. The system is not limited by line-of-sight restrictions and produces drift-free measurements throughout a three-dimensional operating volume that can span a large building. Accuracy of several centimeters and a few degrees is delivered at 10 Hz, and any number of the small sensor units can be in operation, all providing estimates in a common reference frame. This positioning system is based on extremely-low-frequency magnetic fields, which have excellent characteristics for penetrating line-of-sight obstructions. Beacons located throughout the workspace create the low-level fields. A sensor unit on the mobile robot samples the local magnetic field and processes the measurements to determine its location and attitude. This research overcomes limitations in existing magnetic-based systems. The design of the signal structure, based on pseudorandom codes, enables the use of multiple, distributed L-beacons and greatly expands coverage volume. The development of real-time identification and correction methods mitigates the impact of distortions caused by materials in the environment. A novel solution algorithm combats both challenges, providing increased coverage volume and reduced sensitivity to materials. This dissertation examines the concept for the system, the challenges encountered during its development, the research solutions that enable the system, the design of a prototype, and results from experimental demonstrations. The positioning system developed through this research provides an effective solution not only for mobile robots navigating cluttered environments, but has application in other areas such as object tracking, augmented reality, and construction.

Precipitation measurement using SIR-C: A feasibility study

NASA Technical Reports Server (NTRS)

Ahamad, Atiq; Moore, Richard K.

1993-01-01

A precipitation detection and measurement experiment is planned for the SIR-C/X-SAR mission. This study was conducted to determine under what conditions an off-nadir experiment is feasible. The signal-to-clutter ratio, the signal-to-noise ratio, and the minimum detectable rain rate were investigated. Available models, used in previous studies, were used for the surface clutter and the rain echo. The study also considers the attenuation of the returns at X band. It was concluded that an off-nadir rain-measurement experiment is feasible only for rain rates greater than 10 mm/hr for look angles greater than 60 deg. For the range of look angles 5 less than theta(sub 1) less than 50, the rain rate required is very high for adequate signal-to-clutter ratio, and hence the feasibility of the experiment.

Performance of Distributed CFAR Processors in Pearson Distributed Clutter

NASA Astrophysics Data System (ADS)

Messali, Zoubeida; Soltani, Faouzi

2006-12-01

This paper deals with the distributed constant false alarm rate (CFAR) radar detection of targets embedded in heavy-tailed Pearson distributed clutter. In particular, we extend the results obtained for the cell averaging (CA), order statistics (OS), and censored mean level CMLD CFAR processors operating in positive alpha-stable (P&S) random variables to more general situations, specifically to the presence of interfering targets and distributed CFAR detectors. The receiver operating characteristics of the greatest of (GO) and the smallest of (SO) CFAR processors are also determined. The performance characteristics of distributed systems are presented and compared in both homogeneous and in presence of interfering targets. We demonstrate, via simulation results, that the distributed systems when the clutter is modelled as positive alpha-stable distribution offer robustness properties against multiple target situations especially when using the "OR" fusion rule.

Fully invariant wavelet enhanced minimum average correlation energy filter for object recognition in cluttered and occluded environments

NASA Astrophysics Data System (ADS)

Tehsin, Sara; Rehman, Saad; Riaz, Farhan; Saeed, Omer; Hassan, Ali; Khan, Muazzam; Alam, Muhammad S.

2017-05-01

A fully invariant system helps in resolving difficulties in object detection when camera or object orientation and position are unknown. In this paper, the proposed correlation filter based mechanism provides the capability to suppress noise, clutter and occlusion. Minimum Average Correlation Energy (MACE) filter yields sharp correlation peaks while considering the controlled correlation peak value. Difference of Gaussian (DOG) Wavelet has been added at the preprocessing stage in proposed filter design that facilitates target detection in orientation variant cluttered environment. Logarithmic transformation is combined with a DOG composite minimum average correlation energy filter (WMACE), capable of producing sharp correlation peaks despite any kind of geometric distortion of target object. The proposed filter has shown improved performance over some of the other variant correlation filters which are discussed in the result section.

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 eliminate noise, improve signal-to-noise ratio, then the multi-point multi-storey vertical Sobel algorithm will be used to detect the sea-sky-line ,so that we can segment sea and sky in the image. Finally using centroid tracking method to capture and trace target. This method has been successfully used to trace target under the sea-sky complex background.

Gabor Jets for Clutter Rejection in Infrared Imagery

DTIC Science & Technology

2004-12-01

application of a suitable model like Gabor Jets in facial recognition is well motivated by the observation that some low level, spatial-frequency...set. This is a simplified form of the Gabor Jet procedure and will not require any elastic graph matching procedures used in facial recognition . Another...motivation for employing Gabor jets as a post processing clutter rejecter is attributed to the great deal of research in facial recognition , invariant

Combat Identification with Sequential Observations, Rejection Option, and Out-of-Library Targets

DTIC Science & Technology

2005-09-01

nature of the entities sharing the battlespace is unknown. Here CID characterizes those entities using information from a variety of sources. The goal...producing high-resolution returns with signif - icantly enhanced target to clutter (and noise) ratios through Doppler filtering and clutter...treat the subject from a natural science perspective. The following 43 subsections on the various model selection techniques are derived from these

Non-Rayleigh Sea Clutter: Properties and Detection of Targets

DTIC Science & Technology

1976-06-25

subject should consult Guinard and Daley [7], which provides an overview of the theory and references all the I______.... important work. 6 * .-- - - S...results for scattering from slightly rough surfaces and composite surfaces obtained by Rice [1], Wright [2,3], Valenzuela [4-6], Guinard and Daley [7], and...for vertical polarization. In 1970, Trunk and George [10] considered the log-normal and contaminated-normal descriptions of sea clutter and calculated

Radar returns from ground clutter in vicinity of airports

NASA Technical Reports Server (NTRS)

Raemer, H. R.; Rahgavan, R.; Bhattacharya, A.

1988-01-01

The objective of this project is to develop a dynamic simulation of the received signals from natural and man-made ground features in the vicinity of airports. The simulation is run during landing and takeoff stages of a flight. Vugraphs of noteworthy features of the simulation, ground clutter data bases, the development of algorithms for terrain features, typical wave theory results, and a gravity wave height profile are given.

Shallow Water UXO Technology Demonstration Site Scoring Record No. 5 (NAEVA/XTECH, EM61 MKII)

DTIC Science & Technology

2008-04-01

been fired or degaussed. Clutter items fit into one of three categories: ferrous, nonferrous , and mixed metals . The ferrous and nonferrous ...electromagnetic (EM) metal detectors . The system was relatively lightweight, requiring a small aluminum boat for towing. This configuration should...composed of ordnance components; however, industrial scrap metal and cultural items are present as well. The mixed- metals clutter is composed of

The effects of clutter-rejection filtering on estimating weather spectrum parameters

NASA Technical Reports Server (NTRS)

Davis, W. T.

1989-01-01

The effects of clutter-rejection filtering on estimating the weather parameters from pulse Doppler radar measurement data are investigated. The pulse pair method of estimating the spectrum mean and spectrum width of the weather is emphasized. The loss of sensitivity, a measure of the signal power lost due to filtering, is also considered. A flexible software tool developed to investigate these effects is described. It allows for simulated weather radar data, in which the user specifies an underlying truncated Gaussian spectrum, as well as for externally generated data which may be real or simulated. The filter may be implemented in either the time or the frequency domain. The software tool is validated by comparing unfiltered spectrum mean and width estimates to their true values, and by reproducing previously published results. The effects on the weather parameter estimates using simulated weather-only data are evaluated for five filters: an ideal filter, two infinite impulse response filters, and two finite impulse response filters. Results considering external data, consisting of weather and clutter data, are evaluated on a range cell by range cell basis. Finally, it is shown theoretically and by computer simulation that a linear phase response is not required for a clutter rejection filter preceeding pulse-pair parameter estimation.

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.

A New Conflict Resolution Method for Multiple Mobile Robots in Cluttered Environments With Motion-Liveness.

PubMed

Shahriari, Mohammadali; Biglarbegian, Mohammad

2018-01-01

This paper presents a new conflict resolution methodology for multiple mobile robots while ensuring their motion-liveness, especially for cluttered and dynamic environments. Our method constructs a mathematical formulation in a form of an optimization problem by minimizing the overall travel times of the robots subject to resolving all the conflicts in their motion. This optimization problem can be easily solved through coordinating only the robots' speeds. To overcome the computational cost in executing the algorithm for very cluttered environments, we develop an innovative method through clustering the environment into independent subproblems that can be solved using parallel programming techniques. We demonstrate the scalability of our approach through performing extensive simulations. Simulation results showed that our proposed method is capable of resolving the conflicts of 100 robots in less than 1.23 s in a cluttered environment that has 4357 intersections in the paths of the robots. We also developed an experimental testbed and demonstrated that our approach can be implemented in real time. We finally compared our approach with other existing methods in the literature both quantitatively and qualitatively. This comparison shows while our approach is mathematically sound, it is more computationally efficient, scalable for very large number of robots, and guarantees the live and smooth motion of robots.

Learning-dependent plasticity with and without training in the human brain.

PubMed

Zhang, Jiaxiang; Kourtzi, Zoe

2010-07-27

Long-term experience through development and evolution and shorter-term training in adulthood have both been suggested to contribute to the optimization of visual functions that mediate our ability to interpret complex scenes. However, the brain plasticity mechanisms that mediate the detection of objects in cluttered scenes remain largely unknown. Here, we combine behavioral and functional MRI (fMRI) measurements to investigate the human-brain mechanisms that mediate our ability to learn statistical regularities and detect targets in clutter. We show two different routes to visual learning in clutter with discrete brain plasticity signatures. Specifically, opportunistic learning of regularities typical in natural contours (i.e., collinearity) can occur simply through frequent exposure, generalize across untrained stimulus features, and shape processing in occipitotemporal regions implicated in the representation of global forms. In contrast, learning to integrate discontinuities (i.e., elements orthogonal to contour paths) requires task-specific training (bootstrap-based learning), is stimulus-dependent, and enhances processing in intraparietal regions implicated in attention-gated learning. We propose that long-term experience with statistical regularities may facilitate opportunistic learning of collinear contours, whereas learning to integrate discontinuities entails bootstrap-based training for the detection of contours in clutter. These findings provide insights in understanding how long-term experience and short-term training interact to shape the optimization of visual recognition processes.

High-Power Radar Sounders for the Investigation of Jupiter Icy Moons

NASA Technical Reports Server (NTRS)

Safaeinili, A.; Ostro, S.; Rodriquez, E.; Blankenship, D.; Kurth, W.; Kirchner, D.

2005-01-01

The high power and high data rate capability made available by a Prometheus class spacecraft could significantly enhance our ability to probe the subsurface of the planets/moons and asteroid/comets. The main technology development driver for our radar is the proposed Jupiter Icy Moon Orbiter (or JIMO) mission due to its harsh radiation environment. We plan to develop a dual-band radar at 5 and 50 MHz in response to the two major science requirements identified by the JIMO Science Definition Team: studying the near subsurface (less than 2 km) at high resolution and detection of the ice/ocean interface for Europa (depth up to 30 km). The 50-MHz band is necessary to provide high spatial resolution (footprint and depth) as required by the JIMO mission science requirements as currently defined. Our preliminary assessment indicates that the 50-MHz system is not required to be as high-power as the 5-MHz system since it will be more limited by the surface clutter than the Jupiter or galactic background noise. The low frequency band (e.g. 5 MHz), which is the focus of this effort, would be necessary to mitigate the performance risks posed by the unknown subsurface structure both in terms of unknown attenuation due to volumetric scattering and also the detection of the interface through the attenuative transition region at the ice/ocean interface. Additionally, the 5-MHz band is less affected by the surface roughness that can cause loss of coherence and clutter noise. However, since the Signal-to-Noise-Ratio (SNR) of the 5-MHz radar band is reduced due to Jupiter noise when operating in the Jupiter side of the moon, it is necessary to increase the radiated power. Our challenge is to design a high-power HF radar that can hnction in Jupiter's high radiation environment, yet be able to fit into spacecraft resource constraints such as mass and thermal limits. Our effort to develop the JIMO radar sounder will rely on our team's experience with planetary radar sounder design gained during our participation in the MARSIS radar sounder implementation.

Sensory trait variation in an echolocating bat suggests roles for both selection and plasticity

PubMed Central

2014-01-01

Background Across heterogeneous environments selection and gene flow interact to influence the rate and extent of adaptive trait evolution. This complex relationship is further influenced by the rarely considered role of phenotypic plasticity in the evolution of adaptive population variation. Plasticity can be adaptive if it promotes colonization and survival in novel environments and in doing so may increase the potential for future population differentiation via selection. Gene flow between selectively divergent environments may favour the evolution of phenotypic plasticity or conversely, plasticity itself may promote gene flow, leading to a pattern of trait differentiation in the presence of gene flow. Variation in sensory traits is particularly informative in testing the role of environment in trait and population differentiation. Here we test the hypothesis of ‘adaptive differentiation with minimal gene flow’ in resting echolocation frequencies (RF) of Cape horseshoe bats (Rhinolophus capensis) across a gradient of increasingly cluttered habitats. Results Our analysis reveals a geographically structured pattern of increasing RF from open to highly cluttered habitats in R. capensis; however genetic drift appears to be a minor player in the processes influencing this pattern. Although Bayesian analysis of population structure uncovered a number of spatially defined mitochondrial groups and coalescent methods revealed regional-scale gene flow, phylogenetic analysis of mitochondrial sequences did not correlate with RF differentiation. Instead, habitat discontinuities between biomes, and not genetic and geographic distances, best explained echolocation variation in this species. We argue that both selection for increased detection distance in relatively less cluttered habitats and adaptive phenotypic plasticity may have influenced the evolution of matched echolocation frequencies and habitats across different populations. Conclusions Our study reveals significant sensory trait differentiation in the presence of historical gene flow and suggests roles for both selection and plasticity in the evolution of echolocation variation in R. capensis. These results highlight the importance of population level analyses to i) illuminate the subtle interplay between selection, plasticity and gene flow in the evolution of adaptive traits and ii) demonstrate that evolutionary processes may act simultaneously and that their relative influence may vary across different environments. PMID:24674227

Statistics for the Relative Detectability of Chemicals in Weak Gaseous Plumes in LWIR Hyperspectral Imagery

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

Metoyer, Candace N.; Walsh, Stephen J.; Tardiff, Mark F.

2008-10-30

The detection and identification of weak gaseous plumes using thermal imaging data is complicated by many factors. These include variability due to atmosphere, ground and plume temperature, and background clutter. This paper presents an analysis of one formulation of the physics-based model that describes the at-sensor observed radiance. The motivating question for the analyses performed in this paper is as follows. Given a set of backgrounds, is there a way to predict the background over which the probability of detecting a given chemical will be the highest? Two statistics were developed to address this question. These statistics incorporate data frommore » the long-wave infrared band to predict the background over which chemical detectability will be the highest. These statistics can be computed prior to data collection. As a preliminary exploration into the predictive ability of these statistics, analyses were performed on synthetic hyperspectral images. Each image contained one chemical (either carbon tetrachloride or ammonia) spread across six distinct background types. The statistics were used to generate predictions for the background ranks. Then, the predicted ranks were compared to the empirical ranks obtained from the analyses of the synthetic images. For the simplified images under consideration, the predicted and empirical ranks showed a promising amount of agreement. One statistic accurately predicted the best and worst background for detection in all of the images. Future work may include explorations of more complicated plume ingredients, background types, and noise structures.« less

Induced vibrations facilitate traversal of cluttered obstacles

NASA Astrophysics Data System (ADS)

Thoms, George; Yu, Siyuan; Kang, Yucheng; Li, Chen

When negotiating cluttered terrains such as grass-like beams, cockroaches and legged robots with rounded body shapes most often rolled their bodies to traverse narrow gaps between beams. Recent locomotion energy landscape modeling suggests that this locomotor pathway overcomes the lowest potential energy barriers. Here, we tested the hypothesis that body vibrations induced by intermittent leg-ground contact facilitate obstacle traversal by allowing exploration of locomotion energy landscape to find this lowest barrier pathway. To mimic a cockroach / legged robot pushing against two adjacent blades of grass, we developed an automated robotic system to move an ellipsoidal body into two adjacent beams, and varied body vibrations by controlling an oscillation actuator. A novel gyroscope mechanism allowed the body to freely rotate in response to interaction with the beams, and an IMU and cameras recorded the motion of the body and beams. We discovered that body vibrations facilitated body rolling, significantly increasing traversal probability and reducing traversal time (P <0.0001, ANOVA). Traversal probability increased with and traversal time decreased with beam separation. These results confirmed our hypothesis and support the plausibility of locomotion energy landscapes for understanding the formation of locomotor pathways in complex 3-D terrains.

Incorporating advanced EMI technologies in operational munitions characterization surveys

NASA Astrophysics Data System (ADS)

Miller, Jonathan S.; Shubiditze, Fridon; Pasion, Leonard; Schultz, Gregory; Chung, Heesoo

2011-06-01

The presence of unexploded ordnance (UXO), discarded military munitions (DMM), and munitions constituents (MC) at both active and formerly used defense sites (FUDS) has created a necessity for production-level efforts to remove these munitions and explosives of concern (MEC). Ordnance and explosives (OE) and UXO removal operations typically employ electromagnetic induction (EMI) or magnetometer surveys to identify potential MEC hazards in previously determined areas of interest. A major cost factor in these operations is the significant allocation of resources for the excavation of harmless objects associated with fragmentation, scrap, or geological clutter. Recent advances in classification and discrimination methodologies, as well as the development of sensor technologies that fully exploit physics-based analysis, have demonstrated promise for significantly reducing the false alarm rate due to MEC related clutter. This paper identifies some of the considerations for and the challenges associated with implementing these discrimination methodologies and advanced sensor technologies in production-level surveys. Specifically, we evaluate the implications of deploying an advanced multi-axis EMI sensor at a variety of MEC sites, the discrimination methodologies that leverage the data produced by this sensor, and the potential for productivity increase that could be realized by incorporating this advanced technology as part of production protocol.

Lessons learned in the execution of advanced x-ray material discrimination (Conference Presentation)

NASA Astrophysics Data System (ADS)

Young, Sharene

2017-05-01

Advanced X-ray Material Discrimination (AXMD) or BAA 13-05 was a broad agency announcement which was initiated in order to develop solutions to the following problem. The emergence of improvised explosive threats and their use by terrorists has placed many challenges on the aviation security screening layers. EDS and AT X-ray equipment have been presented with considerable challenges in developing a broad detection capability for improvised explosive threats during security screening of checked bags and carry-on items. Technologies are needed that increase the measurement or mathematical discrimination between improvised explosive threats and stream-of-commerce clutter in checked baggage and carry-on items. Conventional EDS utilizes two basic discriminating signatures: effective atomic number and density of screened objects. R and D is needed to identify additional discriminating signatures between improvised explosive threats and stream-of commerce clutter to improve detection capability with reduced false alarm rates. DHS S and T EXD along with stakeholders at the TSA, TSL, and the UK Home Office have been successful in funding efforts to address and potentially provide operational solutions which can be deployed as part of the Next Generation of X-ray Technologies.

Shape-assisted body reorientation enhances trafficability through cluttered terrain

NASA Astrophysics Data System (ADS)

Li, Chen; Pullin, Andrew; Haldane, Duncan; Fearing, Ronald; Full, Robert

2014-11-01

Many birds and fishes have slender, streamlined bodies that reduce fluid dynamic drag and allow fast and efficient locomotion. Similarly, numerous terrestrial animals run through cluttered terrain where 3-D, multi-component obstacles like grass, bushes, trees, walls, doors, and pillars also resist motion, but it is unknown whether their body shape plays a major role. Here, we challenged discoid cockroaches that possess a rounded, thin, nearly ellipsoidal body to run through tall, narrowly spaced, grass-like beams. The animals primarily rolled their body to the side to maneuver through the obstacle gaps. Reduction of body roundness by artificial shells inhibited this side roll maneuver, resulting in a lower traversal probability and a longer traversal time (P < 0.001, ANOVA). Inspired by this discovery, we added a cockroach-like, rounded exoskeleton shell to a legged robot of a nearly cuboidal body. The rounded shell enabled the robot to use passive side rolling to maneuver through beams. To explain the mechanism, we developed a simple physics model to construct an energy landscape of the body-terrain interaction, which allowed estimation of body forces and torques exerted by the beams. Our model revealed that, by passive interaction with the terrain, a rounded body (ellipsoid) rolled more easily than an angular body (cuboid) to access energy valleys between energy barriers caused by obstacles. Our study is the first to demonstrate that a terradynamically ``streamlined'' shape can reduce terrain resistance and enhance trafficability by assisting body reorientation.

Collision Avoidance W-Band FMCW Radars in an Altimeter Application

DTIC Science & Technology

2006-08-01

underground mining applications. Potentially, a small low– powered downward looking aerial radar employing Frequency Modulated Continuous Wave (FMCW) ranging...frequency [1]. 3 Figure 3: Epsilon Lambda ELF 171-1A radar. Model and System block diagram [2]. 4 Figure 4: Beam limited resolution cell (after [3]). 6...Figure 5: (black curves) Projected SNR variation of clutter return with range for ELF 171-1A type system in different weather conditions. Clutter-to

Specification for a standard radar sea clutter model

NASA Astrophysics Data System (ADS)

Paulus, Richard A.

1990-09-01

A model for the average sea clutter radar cross section is proposed for the Oceanographic and Atmospheric Master Library. This model is a function of wind speed (or sea state), wind direction relative to the antenna, refractive conditions, radar antenna height, frequency, polarization, horizontal beamwidth, and compressed pulse length. The model is fully described, a FORTRAN 77 computer listing is provided, and test cases are given to demonstrate the proper operation of the program.

Mid-Frequency Reverberation Measurements with Full Companion Environmental Support

DTIC Science & Technology

2014-12-30

acoustic modeling is based on measured stratification and observed wave amplitudes on the New Jersey shelf during the SWARM experiment.3 Ray tracing is...wave model then gives quantitative results for the clutter. 2. Swarm NLIW model and ray tracing Nonlinear internal waves are very common on the...receiver in order to give quantitative clutter to reverberation. To picture the mechanism, a set of rays was launched from a source at range zero and

RCS Matrix Studies of Sea Clutter

DTIC Science & Technology

1981-03-01

boat. The sea conditions were fairly calm and the return from the targets was in gen - eral well above the clutter level, especially since the targets...pta, I I FAll Aut PONit 0 1 4S aaaiit 114 FIUR 6b Fanc Poaiaioul Dat Pont 251-450i 5 SNI)28 #A.p I A-7 w Ft it I 0 F 114A iI ~~ I o W VVs 0 U IVi

Shallow Water UXO Technology Demonstration Site Scoring Record No. 7

DTIC Science & Technology

2007-05-01

categories: ferrous, nonferrous , and mixed metals . The ferrous and nonferrous items are further divided into the three weight zones as presented in... nonferrous component and could reasonably be encountered in a range area. The mixed- metals clutter was placed in the open water area only. TABLE 1-3...Table 1-4, and distributed throughout all test areas. Most of this clutter is composed of ordnance components; however, industrial scrap metal and

An Investigation of the Pareto Distribution as a Model for High Grazing Angle Clutter

DTIC Science & Technology

2011-03-01

radar detection schemes under controlled conditions. Complicated clutter models result in mathematical difficulties in the determination of optimal and...a population [7]. It has been used in the modelling of actuarial data; an example is in excess of loss quotations in insurance [8]. Its usefulness as...UNCLASSIFIED modified Bessel functions, making it difficult to employ in radar detection schemes. The Pareto Distribution is amenable to mathematical

Documentation of incidental factors affecting the home healthcare work environment.

PubMed

Sitzman, Kathleen L; Leiss, Jack K

2009-10-01

Working conditions related to unrestrained pets, unruly children, clutter, and poor lighting during home healthcare visits are considered normal aspects of care providers' jobs. To date, there has been no documentation related to how often these factors are present in the home healthcare setting during home visits. In this study, 833 home healthcare nurses practicing in North Carolina answered a questionnaire that included items related to how often unrestrained pets, unruly children, poor lighting, and clutter existed in the homes they visited. Results showed that one-third to one-half of the respondents usually or always visited homes with unrestrained pets, clutter, or poor lighting and few nurses usually or always visited homes with uncontrolled children. Better understanding of the prevalence of these factors will facilitate further study related to their effects on safety, efficiency, and job satisfaction for home healthcare workers.

Clutter modeling of the Denver Airport and surrounding areas

NASA Technical Reports Server (NTRS)

Harrah, Steven D.; Delmore, Victor E.; Onstott, Robert G.

1991-01-01

To accurately simulate and evaluate an airborne Doppler radar as a wind shear detection and avoidance sensor, the ground clutter surrounding a typical airport must be quantified. To do this, an imaging airborne Synthetic Aperture Radar (SAR) was employed to investigate and map the normalized radar cross sections (NRCS) of the ground terrain surrounding the Denver Stapleton Airport during November of 1988. Images of the Stapleton ground clutter scene were obtained at a variety of aspect and elevation angles (extending to near-grazing) at both HH and VV polarizations. Presented here, in viewgraph form with commentary, are the method of data collection, the specific observations obtained of the Denver area, a summary of the quantitative analysis performed on the SAR images to date, and the statistical modeling of several of the more interesting stationary targets in the SAR database. Additionally, the accompanying moving target database, containing NRCS and velocity information, is described.

Millimeter wave backscatter measurements in support of collision avoidance applications

NASA Astrophysics Data System (ADS)

Narayanan, Ram M.; Snuttjer, Brett R. J.

1997-11-01

Millimeter-wave short range radar systems have unique advantages in surface navigation applications, such as military vehicle mobility, aircraft landing assistance, and automotive collision avoidance. In collision avoidance applications, characterization of clutter due to terrain and roadside objects is necessary in order to maximize the signal-to-clutter ratio (SCR) and to minimize false alarms. The results of two types of radar cross section (RCS) measurements at 95 GHz are reported in this paper. The first set of measurements presents data on the normalized RCS (NRCS) as well as clutter distributions of various terrain types at low grazing angles of 5° and 7.5°. The second set of measurements presents RCS data and statistics on various types of roadside objects, such as metallic and wooden sign posts. These results are expected to be useful for designers of short-range millimeter-wave collision avoidance radar systems.

Experimental Comparison of High Duty Cycle and Pulsed Active Sonars in a Littoral Environment

DTIC Science & Technology

2014-09-30

A series of metrics (eg. number of detections, matched-filter gain, false alarm rates, track purity, track latency, etc.) will be used to quantify...for QA. These data were used to generate spectrograms, ambient noise and reverberation decay plots, and clutter images, all of which helped...Perhaps the most useful of these for QA were the clutter images which provided a rapid visual assessment to estimate SNR, identify at what range the

Maximum Likelihood Shift Estimation Using High Resolution Polarimetric SAR Clutter Model

NASA Astrophysics Data System (ADS)

Harant, Olivier; Bombrun, Lionel; Vasile, Gabriel; Ferro-Famil, Laurent; Gay, Michel

2011-03-01

This paper deals with a Maximum Likelihood (ML) shift estimation method in the context of High Resolution (HR) Polarimetric SAR (PolSAR) clutter. Texture modeling is exposed and the generalized ML texture tracking method is extended to the merging of various sensors. Some results on displacement estimation on the Argentiere glacier in the Mont Blanc massif using dual-pol TerraSAR-X (TSX) and quad-pol RADARSAT-2 (RS2) sensors are finally discussed.

Multi-contact Variable-Compliance Manipulation in Extreme Clutter

DTIC Science & Technology

2014-06-16

house to find eggs and young. (b) When noodling , people find catfish holes from which to pull fish out. (c)-(d) A person makes contact along his...Figure 7: Haptic Map of detected rigid contacts. by mapping all the rigid taxels at every time- instant . For visualizing the haptic map, we use point...the environment while reaching into clutter. (a) A raccoon reaches into a bird house to find eggs and young. (b) When noodling , people find catfish

Characterization of Sea Clutter Amplitude and Doppler Bin PDFs

DTIC Science & Technology

2014-05-30

range- cells that are processed have their maximum difference of grazing angle be less than 0.1 degrees. The following parameters shall be reported...FFT of varying lengths over a range cell time-series as explained in [5]. However this is optional data reporting t is beyond the minimum baseline...Simulation of Coherent Sea Clutter", IEEE transactions on aerospace and electronic systems vol. 48, no. 4 October 2012. [6] Rosenberg, L., D. J. Crisp

Automated Hand-Held UXO Detection, Classification & Discrimination Sensor

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

Bell, Thomas H.

2000-06-12

The research focused on procedures for target discrimination and classification using hand-held EMI sensors. The idea is to have a small, portable sensor that can be operated in a sweep or similar pattern in front of the operator, and that is capable of distinguishing between buried UXO and clutter on the spot. Curing Phase 1, we developed the processing techniques for distinguishing between buried UXO and clutter using the EM61-HH hand-held metal detector.

High Grazing Angle and High Resolution Sea Clutter: Correlation and Polarisation Analyses

DTIC Science & Technology

2007-03-01

the azimuthal correlation. The correlation between the HH and VV sea clutter data is low. A CA-CFAR ( cell average constant false-alarm rate...to calculate the power spectra of correlation profiles. The frequency interval of the traditional Discrete Fourier Transform is NT1 Hz, where N and...sea spikes, the Entropy-Alpha decomposition of sea spikes is shown in Figure 30. The process first locates spikes using a cell -average constant false

Saberliner flight test for airborne wind shear forward looking detection and avoidance radar systems

NASA Technical Reports Server (NTRS)

Mathews, Bruce D.

1991-01-01

Westinghouse conducted a flight test with its Sabreliner AN/APG-68 instrumented radar to assess the urban discrete/ground moving vehicle clutter environment. Glideslope approaches were flown into Washington National, BWI, and Georgetown, Delaware, airports employing radar mode timing, waveform, and processing configurations plausible for microburst windshear avoidance. The perceptions, both general and specific, of the clutter environment furnish an empirical foundation for beginning low false alarm detection algorithm development.

Shallow Water UXO Technology Demonstration Site Scoring Record Number 4 (CTC, FEREX, DLG-GPS, MAG)

DTIC Science & Technology

2007-01-01

into one of three categories: ferrous, nonferrous , and mixed- metals . The ferrous and nonferrous items have been further divided into three weight...ferrous and nonferrous component and could reasonably be encountered in a range area. The mixed- metals clutter was placed in the open water area...also industrial scrap metal and cultural items as well. The mixed- metals clutter is comprised of scrap ordnance items or fragments that have both a

Broadband Acoustic Clutter

DTIC Science & Technology

2006-09-30

DRDC-A, and the NATO Undersea Research Centre, La Spezia Italy (this is ongoing). Under these main topics, accomplishments included: a...associated with clutter from an undersea ridge and mud volcano cluster. RESULTS A constrained comparison of waveguide reverberation theory and...1000 Hz c) 0 10 20 −70 −60 −50 −40 −30 −20 −10 Angle (deg) S ca tte rin g S tr en gt h (d B ) 900 Hz a) Figure 1. Measured (x) seabed a

Multichannel Doppler Processing for an Experimental Low-Angle Tracking System

DTIC Science & Technology

1990-05-01

estimation techniques at sea. Because of clutter and noise, it is necessary to use a number of different processing algorithms to extract the required...a number of different processing algorithms to extract the required information. Consequently, the ELAT radar system is composed of multiple...corresponding to RF frequencies, f, and f2. For mode 3, the ambiguities occur at vbi = 15.186 knots and vb2 = 16.96 knots. The sea clutter, with a spectrum

Measured Changes in C-Band Radar Reflectivity of Clear Air Caused by Aircraft Wake Vortices

NASA Technical Reports Server (NTRS)

Mackenzie, Anne I.

1997-01-01

Wake vortices from a C-130 airplane were observed at the NASA Wallops Flight Facility with a ground-based, monostatic C-band radar and an antenna-mounted boresight video camera. The airplane wake was viewed from a distance of approximately 1 km, and radar scanning was adjusted to cross a pair of marker smoke trails generated by the C-130. For each airplane pass, changes in radar reflectivity were calculated by subtracting the signal magnitudes during an initial clutter scan from the signal magnitudes during vortex-plus-clutter scans. The results showed both increases and decreases in reflectivity on and near the smoke trails in a characteristic sinusoidal pattern of heightened reflectivity in the center and lessened reflectivity at the sides. Reflectivity changes in either direction varied from -131 to -102 dBm(exp -1); the vortex-plus-clutter to noise ratio varied from 20 to 41 dB. The radar recordings lasted 2.5 min each; evidence of wake vortices was found for up to 2 min after the passage of the airplane. Ground and aircraft clutter were eliminated as possible sources of the disturbance by noting the occurrence of vortex signatures at different positions relative to the ground and the airplane. This work supports the feasibility of vortex detection by radar, and it is recommended that future radar vortex detection be done with Doppler systems.

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.

Image classification using multiscale information fusion based on saliency driven nonlinear diffusion filtering.

PubMed

Hu, Weiming; Hu, Ruiguang; Xie, Nianhua; Ling, Haibin; Maybank, Stephen

2014-04-01

In this paper, we propose saliency driven image multiscale nonlinear diffusion filtering. The resulting scale space in general preserves or even enhances semantically important structures such as edges, lines, or flow-like structures in the foreground, and inhibits and smoothes clutter in the background. The image is classified using multiscale information fusion based on the original image, the image at the final scale at which the diffusion process converges, and the image at a midscale. Our algorithm emphasizes the foreground features, which are important for image classification. The background image regions, whether considered as contexts of the foreground or noise to the foreground, can be globally handled by fusing information from different scales. Experimental tests of the effectiveness of the multiscale space for the image classification are conducted on the following publicly available datasets: 1) the PASCAL 2005 dataset; 2) the Oxford 102 flowers dataset; and 3) the Oxford 17 flowers dataset, with high classification rates.

Detection of gas plumes in cluttered environments using long-wave infrared hyperspectral sensors

NASA Astrophysics Data System (ADS)

Broadwater, Joshua B.; Spisz, Thomas S.; Carr, Alison K.

2008-04-01

Long-wave infrared hyperspectral sensors provide the ability to detect gas plumes at stand-off distances. A number of detection algorithms have been developed for such applications, but in situations where the gas is released in a complex background and is at air temperature, these detectors can generate a considerable amount of false alarms. To make matters more difficult, the gas tends to have non-uniform concentrations throughout the plume making it spatially similar to the false alarms. Simple post-processing using median filters can remove a number of the false alarms, but at the cost of removing a significant amount of the gas plume as well. We approach the problem using an adaptive subpixel detector and morphological processing techniques. The adaptive subpixel detection algorithm is able to detect the gas plume against the complex background. We then use morphological processing techniques to isolate the gas plume while simultaneously rejecting nearly all false alarms. Results will be demonstrated on a set of ground-based long-wave infrared hyperspectral image sequences.

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

Automatic Focusing for a 675 GHz Imaging Radar with Target Standoff Distances from 14 to 34 Meters

NASA Technical Reports Server (NTRS)

Tang, Adrian; Cooper, Ken B.; Dengler, Robert J.; Llombart, Nuria; Siegel, Peter H.

2013-01-01

This paper dicusses the issue of limited focal depth for high-resolution imaging radar operating over a wide range of standoff distances. We describe a technique for automatically focusing a THz imaging radar system using translational optics combined with range estimation based on a reduced chirp bandwidth setting. The demonstarted focusing algorithm estimates the correct focal depth for desired targets in the field of view at unknown standoffs and in the presence of clutter to provide good imagery at 14 to 30 meters of standoff.

Wavelet detection of singularities in the presence of fractal noise

NASA Astrophysics Data System (ADS)

Noel, Steven E.; Gohel, Yogesh J.; Szu, Harold H.

1997-04-01

Here we detect singularities with generalized quadrature processing using the recently developed Hermitian Hat wavelet. Our intended application is radar target detection for the optimal fuzzing of ship self-defense munitions. We first develop a wavelet-based fractal noise model to represent sea clutter. We then investigate wavelet shrinkage as a way to reduce and smooth the noise before attempting wavelet detection. Finally, we use the complex phase of the Hermitian Hat wavelet to detect a simulated target singularity in the presence of our fractal noise.

Pacific Sardine Characteristics Affecting the Conduct of an Acoustic Clutter Experiment off the West Coast of the United States

DTIC Science & Technology

2012-05-15

P. Cotel, "Three-dimensional structure and avoidance behavior of anchovy and common sardine schools in central southern Chile ," ICES J. Mar. Sei. 61...the most abundant species of schooling fish off the West Coast Therefore, sardines are the best candidates to be clutter targets. In preparation for...fish and to interpret the results, pertinent characteristics of the major fish species in the region must be known. The best source of that knowledge

Signal Processing Algorithms for the Terminal Doppler Weather Radar: Build 2

DTIC Science & Technology

2010-04-30

the various TDWR base data quality issues, range-velocity (RV) ambiguity was deemed to be the most severe challenge nationwide. Compared to S - band ... power is computed as PN = median(|5«| 2)/(ln 2), where s is the complex I&Q signal, k is the range gate number, and / is the pulse time index. The...frequencies to the ground-clutter band around zero, the clutter filtering also removes power from the aliased frequencies and distorts the phase response

Development of Genuine Neural Network Prototype Chip

DTIC Science & Technology

1991-01-28

priori distribution is equivalent, and more readily visualized with a rank curve . The sonar signal data consisted of approximately 85% class Target and...15% class Clutter. For this reason, the rank curves for the class Clutter were used for device parameter analysis. R & D STATUS REPORT 1/28/91 N00014...the signal CLASSLD#. Four 10-bit class probabilities are available on the output bus (C0-C9, C16-C25, C32-C41 and C48- C57 ) at each clock cycle. A

Advancement of High Resolution Radar Polarimetry in Target Verses Clutter Detection, Discrimination, Classification: A. Basic Theory and Modeling of Polarimetric Clutter Phenomenology.

DTIC Science & Technology

1988-07-15

the interim period, polarimetLic measurement data collected at other DOD/NATO/Industrial R/D/M facilities will be used. These basic studies will be...the polarization sphere and its spread can he related either to the coherency factor or the depolarization factor plus descriptive parameters of the...careful study of the concluding sections outlining the overall scenario of solved and unsolved problems. Here, we also refer to the recent report (Dec

The Effects of Better Environmental Inputs in Estimating Sea Clutter

DTIC Science & Technology

1988-01-01

3.2 A Spectral Ocean Wave Model: DWAVE 11 3.3 Limitations of DWAVE 11 4. HYBRID MODEL DEVELOPMENT 12 4.1 Overall Plan 12 4.2 High Resolution...intensive. 10 3.2 A Spectral Ocean Wave Model: DWAVE Most of the spectral ocean wave models give essentially the same type of outputs, for example, the...sea clutter estimation. A deep ocean wave model DWAVE by Offshore & Coastal Technologies, Inc. (OCTI) has been chosen because it can be run on a

Integration of Irma tactical scene generator into directed-energy weapon system simulation

NASA Astrophysics Data System (ADS)

Owens, Monte A.; Cole, Madison B., III; Laine, Mark R.

2003-08-01

Integrated high-fidelity physics-based simulations that include engagement models, image generation, electro-optical hardware models and control system algorithms have previously been developed by Boeing-SVS for various tracking and pointing systems. These simulations, however, had always used images with featureless or random backgrounds and simple target geometries. With the requirement to engage tactical ground targets in the presence of cluttered backgrounds, a new type of scene generation tool was required to fully evaluate system performance in this challenging environment. To answer this need, Irma was integrated into the existing suite of Boeing-SVS simulation tools, allowing scene generation capabilities with unprecedented realism. Irma is a US Air Force research tool used for high-resolution rendering and prediction of target and background signatures. The MATLAB/Simulink-based simulation achieves closed-loop tracking by running track algorithms on the Irma-generated images, processing the track errors through optical control algorithms, and moving simulated electro-optical elements. The geometry of these elements determines the sensor orientation with respect to the Irma database containing the three-dimensional background and target models. This orientation is dynamically passed to Irma through a Simulink S-function to generate the next image. This integrated simulation provides a test-bed for development and evaluation of tracking and control algorithms against representative images including complex background environments and realistic targets calibrated using field measurements.

Comparing object recognition from binary and bipolar edge images for visual prostheses.

PubMed

Jung, Jae-Hyun; Pu, Tian; Peli, Eli

2016-11-01

Visual prostheses require an effective representation method due to the limited display condition which has only 2 or 3 levels of grayscale in low resolution. Edges derived from abrupt luminance changes in images carry essential information for object recognition. Typical binary (black and white) edge images have been used to represent features to convey essential information. However, in scenes with a complex cluttered background, the recognition rate of the binary edge images by human observers is limited and additional information is required. The polarity of edges and cusps (black or white features on a gray background) carries important additional information; the polarity may provide shape from shading information missing in the binary edge image. This depth information may be restored by using bipolar edges. We compared object recognition rates from 16 binary edge images and bipolar edge images by 26 subjects to determine the possible impact of bipolar filtering in visual prostheses with 3 or more levels of grayscale. Recognition rates were higher with bipolar edge images and the improvement was significant in scenes with complex backgrounds. The results also suggest that erroneous shape from shading interpretation of bipolar edges resulting from pigment rather than boundaries of shape may confound the recognition.

Ellipsoids for anomaly detection in remote sensing imagery

NASA Astrophysics Data System (ADS)

Grosklos, Guenchik; Theiler, James

2015-05-01

For many target and anomaly detection algorithms, a key step is the estimation of a centroid (relatively easy) and a covariance matrix (somewhat harder) that characterize the background clutter. For a background that can be modeled as a multivariate Gaussian, the centroid and covariance lead to an explicit probability density function that can be used in likelihood ratio tests for optimal detection statistics. But ellipsoidal contours can characterize a much larger class of multivariate density function, and the ellipsoids that characterize the outer periphery of the distribution are most appropriate for detection in the low false alarm rate regime. Traditionally the sample mean and sample covariance are used to estimate ellipsoid location and shape, but these quantities are confounded both by large lever-arm outliers and non-Gaussian distributions within the ellipsoid of interest. This paper compares a variety of centroid and covariance estimation schemes with the aim of characterizing the periphery of the background distribution. In particular, we will consider a robust variant of the Khachiyan algorithm for minimum-volume enclosing ellipsoid. The performance of these different approaches is evaluated on multispectral and hyperspectral remote sensing imagery using coverage plots of ellipsoid volume versus false alarm rate.

Heuristic automation for decluttering tactical displays.

PubMed

St John, Mark; Smallman, Harvey S; Manes, Daniel I; Feher, Bela A; Morrison, Jeffrey G

2005-01-01

Tactical displays can quickly become cluttered with large numbers of symbols that can compromise effective monitoring. Here, we studied how heuristic automation can aid users by intelligently "decluttering" the display. In a realistic simulated naval air defense task, 27 experienced U.S. Navy users monitored a cluttered airspace and executed defensive responses against significant threats. An algorithm continuously evaluated aircraft for their levels of threat and decluttered the less threatening ones by dimming their symbols. Users appropriately distrusted and spot-checked the automation's assessments, and decluttering had very little effect on which aircraft were judged as significantly threatening. Nonetheless, decluttering improved the timeliness of responses to threatening aircraft by 25% as compared with a baseline display with no decluttering; it was especially beneficial for threats in more peripheral locations, and 25 of 27 participants preferred decluttering. Heuristic automation, when properly designed to guide users' attention by decluttering less important objects, may prove valuable in many cluttered monitoring situations, including air traffic management, crisis team management, and tactical situation awareness in general.

Differences in the effects of crowding on size perception and grip scaling in densely cluttered 3-D scenes.

PubMed

Chen, Juan; Sperandio, Irene; Goodale, Melvyn Alan

2015-01-01

Objects rarely appear in isolation in natural scenes. Although many studies have investigated how nearby objects influence perception in cluttered scenes (i.e., crowding), none has studied how nearby objects influence visually guided action. In Experiment 1, we found that participants could scale their grasp to the size of a crowded target even when they could not perceive its size, demonstrating for the first time that neurologically intact participants can use visual information that is not available to conscious report to scale their grasp to real objects in real scenes. In Experiments 2 and 3, we found that changing the eccentricity of the display and the orientation of the flankers had no effect on grasping but strongly affected perception. The differential effects of eccentricity and flanker orientation on perception and grasping show that the known differences in retinotopy between the ventral and dorsal streams are reflected in the way in which people deal with targets in cluttered scenes. © The Author(s) 2014.

Using Virtual Reality in the Inference-Based Treatment of Compulsive Hoarding

PubMed Central

St-Pierre-Delorme, Marie-Eve; O’Connor, Kieron

2016-01-01

The present study evaluated the efficacy of adding a virtual reality (VR) component to the treatment of compulsive hoarding (CH), following inference-based therapy (IBT). Participants were randomly assigned to either an experimental or a control condition. Seven participants received the experimental and seven received the control condition. Five sessions of 1 h were administered weekly. A significant difference indicated that the level of clutter in the bedroom tended to diminish more in the experimental group as compared to the control group F(2,24) = 2.28, p = 0.10. In addition, the results demonstrated that both groups were immersed and present in the environment. The results on posttreatment measures of CH (Saving Inventory revised, Saving Cognition Inventory and Clutter Image Rating scale) demonstrate the efficacy of IBT in terms of symptom reduction. Overall, these results suggest that the creation of a virtual environment may be effective in the treatment of CH by helping the compulsive hoarders take action over their clutter. PMID:27486574

Evaluation of the maximum-likelihood adaptive neural system (MLANS) applications to noncooperative IFF

NASA Astrophysics Data System (ADS)

Chernick, Julian A.; Perlovsky, Leonid I.; Tye, David M.

1994-06-01

This paper describes applications of maximum likelihood adaptive neural system (MLANS) to the characterization of clutter in IR images and to the identification of targets. The characterization of image clutter is needed to improve target detection and to enhance the ability to compare performance of different algorithms using diverse imagery data. Enhanced unambiguous IFF is important for fratricide reduction while automatic cueing and targeting is becoming an ever increasing part of operations. We utilized MLANS which is a parametric neural network that combines optimal statistical techniques with a model-based approach. This paper shows that MLANS outperforms classical classifiers, the quadratic classifier and the nearest neighbor classifier, because on the one hand it is not limited to the usual Gaussian distribution assumption and can adapt in real time to the image clutter distribution; on the other hand MLANS learns from fewer samples and is more robust than the nearest neighbor classifiers. Future research will address uncooperative IFF using fused IR and MMW data.

Wind Turbine Clutter Mitigation in Coastal UHF Radar

PubMed Central

Wang, Caijun; Jiang, Dapeng; Wen, Biyang

2014-01-01

Coastal UHF radar provides a unique capability to measure the sea surface dynamic parameters and detect small moving targets, by exploiting the low energy loss of electromagnetic waves propagating along the salty and good conducting ocean surface. It could compensate the blind zone of HF surface wave radar at close range and reach further distance than microwave radars. However, its performance is susceptible to wind turbines which are usually installed on the shore. The size of a wind turbine is much larger than the wavelength of radio waves at UHF band, which results in large radar cross section. Furthermore, the rotation of blades adds time-varying Doppler frequency to the clutter and makes the suppression difficult. This paper proposes a mitigation method which is based on the specific periodicity of wind turbine clutter and performed mainly in the time-frequency domain. Field experimental data of a newly developed UHF radar are used to verify this method, and the results prove its effectiveness. PMID:24550709

Wind turbine clutter mitigation in coastal UHF radar.

PubMed

Yang, Jing; Pan, Chao; Wang, Caijun; Jiang, Dapeng; Wen, Biyang

2014-01-01

Coastal UHF radar provides a unique capability to measure the sea surface dynamic parameters and detect small moving targets, by exploiting the low energy loss of electromagnetic waves propagating along the salty and good conducting ocean surface. It could compensate the blind zone of HF surface wave radar at close range and reach further distance than microwave radars. However, its performance is susceptible to wind turbines which are usually installed on the shore. The size of a wind turbine is much larger than the wavelength of radio waves at UHF band, which results in large radar cross section. Furthermore, the rotation of blades adds time-varying Doppler frequency to the clutter and makes the suppression difficult. This paper proposes a mitigation method which is based on the specific periodicity of wind turbine clutter and performed mainly in the time-frequency domain. Field experimental data of a newly developed UHF radar are used to verify this method, and the results prove its effectiveness.

Low-rank matrix decomposition and spatio-temporal sparse recovery for STAP radar

DOE PAGES

Sen, Satyabrata

2015-08-04

We develop space-time adaptive processing (STAP) methods by leveraging the advantages of sparse signal processing techniques in order to detect a slowly-moving target. We observe that the inherent sparse characteristics of a STAP problem can be formulated as the low-rankness of clutter covariance matrix when compared to the total adaptive degrees-of-freedom, and also as the sparse interference spectrum on the spatio-temporal domain. By exploiting these sparse properties, we propose two approaches for estimating the interference covariance matrix. In the first approach, we consider a constrained matrix rank minimization problem (RMP) to decompose the sample covariance matrix into a low-rank positivemore » semidefinite and a diagonal matrix. The solution of RMP is obtained by applying the trace minimization technique and the singular value decomposition with matrix shrinkage operator. Our second approach deals with the atomic norm minimization problem to recover the clutter response-vector that has a sparse support on the spatio-temporal plane. We use convex relaxation based standard sparse-recovery techniques to find the solutions. With extensive numerical examples, we demonstrate the performances of proposed STAP approaches with respect to both the ideal and practical scenarios, involving Doppler-ambiguous clutter ridges, spatial and temporal decorrelation effects. As a result, the low-rank matrix decomposition based solution requires secondary measurements as many as twice the clutter rank to attain a near-ideal STAP performance; whereas the spatio-temporal sparsity based approach needs a considerably small number of secondary data.« less

Compound Radar Approach for Breast Imaging.

PubMed

Byrne, Dallan; Sarafianou, Mantalena; Craddock, Ian J

2017-01-01

Multistatic radar apertures record scattering at a number of receivers when the target is illuminated by a single transmitter, providing more scattering information than its monostatic counterpart per transmission angle. This paper considers the well-known problem of detecting tumor targets within breast phantoms using multistatic radar. To accurately image potentially cancerous targets size within the breast, a significant number of multistatic channels are required in order to adequately calibrate-out unwanted skin reflections, increase the immunity to clutter, and increase the dynamic range of a breast radar imaging system. However, increasing the density of antennas within a physical array is inevitably limited by the geometry of the antenna elements designed to operate with biological tissues at microwave frequencies. A novel compound imaging approach is presented to overcome these physical constraints and improve the imaging capabilities of a multistatic radar imaging modality for breast scanning applications. The number of transmit-receive (TX-RX) paths available for imaging are increased by performing a number of breast scans with varying array positions. A skin calibration method is presented to reduce the influence of skin reflections from each channel. Calibrated signals are applied to receive a beamforming method, compounding the data from each scan to produce a microwave radar breast profile. The proposed imaging method is evaluated with experimental data obtained from constructed phantoms of varying complexity, skin contour asymmetries, and challenging tumor positions and sizes. For each imaging scenario outlined in this study, the proposed compound imaging technique improves skin calibration, clearly detects small targets, and substantially reduces the level of undesirable clutter within the profile.

GMTI Direction of Arrival Measurements from Multiple Phase Centers.

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

Doerry, Armin W.; Bickel, Douglas L.

2015-03-01

Ground Moving Target Indicator (GMTI) radar attempts to detect and locate targets with unknown motion. Very slow-moving targets are difficult to locate in the presence of surrounding clutter. This necessitates multiple antenna phase centers (or equivalent) to offer independent Direction of Arrival (DOA) measurements. DOA accuracy and precision generally remains dependent on target Signal-to-Noise Ratio (SNR), Clutter-toNoise Ratio (CNR), scene topography, interfering signals, and a number of antenna parameters. This is true even for adaptive techniques like Space-Time-AdaptiveProcessing (STAP) algorithms.

Combining High Dynamic Range Photography and High Range Resolution RADAR for Pre-discharge Threat Cues

DTIC Science & Technology

2011-08-16

Munitions • Dragunov • AK47 • RPG • AR10 Confusers • Person with Tripod • Person with Broom Results • Dragunov, AK47 , RPG, and AR10 detected as...weapons • Person+Tripod declared as clutter • Person+Broom declared as clutter Notes • AK47 and Dragunov in same room Demo April 2010 Detection Results...tp9042 AK47 + Dragunov RPG Person + Tripod Person + Broom AR10 R an g e Sweep Number Sweep Number Declarations RADAR Data UNCLASSIFIED Summary

Applications of independent component analysis in SAR images

NASA Astrophysics Data System (ADS)

Huang, Shiqi; Cai, Xinhua; Hui, Weihua; Xu, Ping

2009-07-01

The detection of faint, small and hidden targets in synthetic aperture radar (SAR) image is still an issue for automatic target recognition (ATR) system. How to effectively separate these targets from the complex background is the aim of this paper. Independent component analysis (ICA) theory can enhance SAR image targets and improve signal clutter ratio (SCR), which benefits to detect and recognize faint targets. Therefore, this paper proposes a new SAR image target detection algorithm based on ICA. In experimental process, the fast ICA (FICA) algorithm is utilized. Finally, some real SAR image data is used to test the method. The experimental results verify that the algorithm is feasible, and it can improve the SCR of SAR image and increase the detection rate for the faint small targets.

Nanoantenna harmonic sensor: theoretical analysis of contactless detection of molecules with light

NASA Astrophysics Data System (ADS)

Farhat, Mohamed; Cheng, Mark M. C.; Le, Khai Q.; Chen, Pai-Yen

2015-10-01

The nonlinear harmonic sensor is a popular wireless sensor and radiofrequency identification (RFID) technique, which allows high-performance sensing in a severe interference/clutter background by transmitting a radio wave and detecting its modulated higher-order harmonics. Here we introduce the concept and design of optical harmonic tags based on nonlinear nanoantennas that can contactlessly detect electronic (e.g. electron affinity) and optical (e.g. relative permittivity) characteristics of molecules. By using a dual-resonance gold-molecule-silver nanodipole antenna within the quantum mechanical realm, the spectral form of the second-harmonic scattering can sensitively reveal the physical properties of molecules, paving a new route towards optical molecular sensors and optical identification (OPID) of biological, genetic, and medical events for the ‘Internet of Nano-Things’.

A new airborne laser rangefinder dynamic target simulator for non-stationary environment

NASA Astrophysics Data System (ADS)

Ma, Pengge; Pang, Dongdong; Yi, Yang

2017-11-01

For the non-stationary environment simulation in laser range finder product testing, a new dynamic target simulation system is studied. First of all, the three-pulsed laser ranging principle, laser target signal composition and mathematical representation are introduced. Then, the actual nonstationary working environment of laser range finder is analyzed, and points out that the real sunshine background light clutter and target shielding effect in laser echo become the main influencing factors. After that, the dynamic laser target signal simulation method is given. Eventlly, the implementation of automatic test system based on arbitrary waveform generator is described. Practical application shows that the new echo signal automatic test system can simulate the real laser ranging environment of laser range finder, and is suitable for performance test of products.

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

NASA Astrophysics Data System (ADS)

Zhu, Aichun; Wang, Tian; Snoussi, Hichem

2018-03-01

This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN). Firstly, a Relative Mixture Deformable Model (RMDM) is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN) is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Nanoantenna harmonic sensor: theoretical analysis of contactless detection of molecules with light.

PubMed

Farhat, Mohamed; Cheng, Mark M C; Le, Khai Q; Chen, Pai-Yen

2015-10-16

The nonlinear harmonic sensor is a popular wireless sensor and radiofrequency identification (RFID) technique, which allows high-performance sensing in a severe interference/clutter background by transmitting a radio wave and detecting its modulated higher-order harmonics. Here we introduce the concept and design of optical harmonic tags based on nonlinear nanoantennas that can contactlessly detect electronic (e.g. electron affinity) and optical (e.g. relative permittivity) characteristics of molecules. By using a dual-resonance gold-molecule-silver nanodipole antenna within the quantum mechanical realm, the spectral form of the second-harmonic scattering can sensitively reveal the physical properties of molecules, paving a new route towards optical molecular sensors and optical identification (OPID) of biological, genetic, and medical events for the 'Internet of Nano-Things'.

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.

Improved relocatable over-the-horizon radar detection and tracking using the maximum likelihood adaptive neural system algorithm

NASA Astrophysics Data System (ADS)

Perlovsky, Leonid I.; Webb, Virgil H.; Bradley, Scott R.; Hansen, Christopher A.

1998-07-01

An advanced detection and tracking system is being developed for the U.S. Navy's Relocatable Over-the-Horizon Radar (ROTHR) to provide improved tracking performance against small aircraft typically used in drug-smuggling activities. The development is based on the Maximum Likelihood Adaptive Neural System (MLANS), a model-based neural network that combines advantages of neural network and model-based algorithmic approaches. The objective of the MLANS tracker development effort is to address user requirements for increased detection and tracking capability in clutter and improved track position, heading, and speed accuracy. The MLANS tracker is expected to outperform other approaches to detection and tracking for the following reasons. It incorporates adaptive internal models of target return signals, target tracks and maneuvers, and clutter signals, which leads to concurrent clutter suppression, detection, and tracking (track-before-detect). It is not combinatorial and thus does not require any thresholding or peak picking and can track in low signal-to-noise conditions. It incorporates superresolution spectrum estimation techniques exceeding the performance of conventional maximum likelihood and maximum entropy methods. The unique spectrum estimation method is based on the Einsteinian interpretation of the ROTHR received energy spectrum as a probability density of signal frequency. The MLANS neural architecture and learning mechanism are founded on spectrum models and maximization of the "Einsteinian" likelihood, allowing knowledge of the physical behavior of both targets and clutter to be injected into the tracker algorithms. The paper describes the addressed requirements and expected improvements, theoretical foundations, engineering methodology, and results of the development effort to date.

Dynamic adjustment of echolocation pulse structure of big-footed myotis (Myotis macrodactylus) in response to different habitats.

PubMed

Wang, Lei; Luo, Jinhong; Wang, Hongna; Ou, Wei; Jiang, Tinglei; Liu, Ying; Lyle, Dennis; Feng, Jiang

2014-02-01

Studying relationships between characteristics of sonar pulses and habitat clutter level is important for the understanding of signal design in bat echolocation. However, most studies have focused on overall spectral and temporal parameters of such vocalizations, with focus less on potential variation in frequency modulation rates (MRs) occurring within each pulse. In the current study, frequency modulation (FM) characteristics were examined in echolocation pulses recorded from big-footed myotis (Myotis macrodactylus) bats as these animals searched for prey in five habitats differing in relative clutter level. Pulses were analyzed using ten parameters, including four structure-related characters which were derived by dividing each pulse into three elements based on two knees in the FM sweep. Results showed that overall frequency, pulse duration, and MR all varied across habitat. The strongest effects were found for MR in the body of the pulse, implying that this particular component plays a major role as M. macrodactylus, and potentially other bat species, adjust to varying clutter levels in their foraging habitats.

Road-Aided Ground Slowly Moving Target 2D Motion Estimation for Single-Channel Synthetic Aperture Radar.

PubMed

Wang, Zhirui; Xu, Jia; Huang, Zuzhen; Zhang, Xudong; Xia, Xiang-Gen; Long, Teng; Bao, Qian

2016-03-16

To detect and estimate ground slowly moving targets in airborne single-channel synthetic aperture radar (SAR), a road-aided ground moving target indication (GMTI) algorithm is proposed in this paper. First, the road area is extracted from a focused SAR image based on radar vision. Second, after stationary clutter suppression in the range-Doppler domain, a moving target is detected and located in the image domain via the watershed method. The target's position on the road as well as its radial velocity can be determined according to the target's offset distance and traffic rules. Furthermore, the target's azimuth velocity is estimated based on the road slope obtained via polynomial fitting. Compared with the traditional algorithms, the proposed method can effectively cope with slowly moving targets partly submerged in a stationary clutter spectrum. In addition, the proposed method can be easily extended to a multi-channel system to further improve the performance of clutter suppression and motion estimation. Finally, the results of numerical experiments are provided to demonstrate the effectiveness of the proposed algorithm.

Evaluation of appropriate sensor specifications for space based ballistic missile detection

NASA Astrophysics Data System (ADS)

Schweitzer, Caroline; Stein, Karin; Wendelstein, Norbert

2012-10-01

The detection and tracking of ballistic missiles (BMs) during launch or cloud break using satellite based electro-optical (EO) sensors is a promising possibility for pre-instructing early warning and fire control radars. However, the successful detection of a BM is depending on the applied infrared (IR)-channel, as emission and reflection of threat and background vary in different spectral (IR-) bands and for different observation scenarios. In addition, the spatial resolution of the satellite based system also conditions the signal-to-clutter-ratio (SCR) and therefore the predictability of the flight path. Generally available satellite images provide data in spectral bands, which are suitable for remote sensing applications and earth surface observations. However, in the fields of BM early warning, these bands are not of interest making the simulation of background data essential. The paper focuses on the analysis of IR-bands suitable for missile detection by trading off the suppression of background signature against threat signal strength. This comprises a radiometric overview of the background radiation in different spectral bands for different climates and seasons as well as for various cloud types and covers. A brief investigation of the BM signature and its trajectory within a threat scenario is presented. Moreover, the influence on the SCR caused by different observation scenarios and varying spatial resolution are pointed out. The paper also introduces the software used for simulating natural background spectral radiance images, MATISSE ("Advanced Modeling of the Earth for Environment and Scenes Simulation") by ONERA [1].

PTBS segmentation scheme for synthetic aperture radar

NASA Astrophysics Data System (ADS)

Friedland, Noah S.; Rothwell, Brian J.

1995-07-01

The Image Understanding Group at Martin Marietta Technologies in Denver, Colorado has developed a model-based synthetic aperture radar (SAR) automatic target recognition (ATR) system using an integrated resource architecture (IRA). IRA, an adaptive Markov random field (MRF) environment, utilizes information from image, model, and neighborhood resources to create a discrete, 2D feature-based world description (FBWD). The IRA FBWD features are peak, target, background and shadow (PTBS). These features have been shown to be very useful for target discrimination. The FBWD is used to accrue evidence over a model hypothesis set. This paper presents the PTBS segmentation process utilizing two IRA resources. The image resource (IR) provides generic (the physics of image formation) and specific (the given image input) information. The neighborhood resource (NR) provides domain knowledge of localized FBWD site behaviors. A simulated annealing optimization algorithm is used to construct a `most likely' PTBS state. Results on simulated imagery illustrate the power of this technique to correctly segment PTBS features, even when vehicle signatures are immersed in heavy background clutter. These segmentations also suppress sidelobe effects and delineate shadows.

Probabilistic multi-resolution human classification

NASA Astrophysics Data System (ADS)

Tu, Jun; Ran, H.

2006-02-01

Recently there has been some interest in using infrared cameras for human detection because of the sharply decreasing prices of infrared cameras. The training data used in our work for developing the probabilistic template consists images known to contain humans in different poses and orientation but having the same height. Multiresolution templates are performed. They are based on contour and edges. This is done so that the model does not learn the intensity variations among the background pixels and intensity variations among the foreground pixels. Each template at every level is then translated so that the centroid of the non-zero pixels matches the geometrical center of the image. After this normalization step, for each pixel of the template, the probability of it being pedestrian is calculated based on the how frequently it appears as 1 in the training data. We also use periodicity gait to verify the pedestrian in a Bayesian manner for the whole blob in a probabilistic way. The videos had quite a lot of variations in the scenes, sizes of people, amount of occlusions and clutter in the backgrounds as is clearly evident. Preliminary experiments show the robustness.

A real-time tracking system of infrared dim and small target based on FPGA and DSP

NASA Astrophysics Data System (ADS)

Rong, Sheng-hui; Zhou, Hui-xin; Qin, Han-lin; Wang, Bing-jian; Qian, Kun

2014-11-01

A core technology in the infrared warning system is the detection tracking of dim and small targets with complicated background. Consequently, running the detection algorithm on the hardware platform has highly practical value in the military field. In this paper, a real-time detection tracking system of infrared dim and small target which is used FPGA (Field Programmable Gate Array) and DSP (Digital Signal Processor) as the core was designed and the corresponding detection tracking algorithm and the signal flow is elaborated. At the first stage, the FPGA obtain the infrared image sequence from the sensor, then it suppresses background clutter by mathematical morphology method and enhances the target intensity by Laplacian of Gaussian operator. At the second stage, the DSP obtain both the original image and the filtered image form the FPGA via the video port. Then it segments the target from the filtered image by an adaptive threshold segmentation method and gets rid of false target by pipeline filter. Experimental results show that our system can achieve higher detection rate and lower false alarm rate.

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.

Regularized learning of linear ordered-statistic constant false alarm rate filters (Conference Presentation)

NASA Astrophysics Data System (ADS)

Havens, Timothy C.; Cummings, Ian; Botts, Jonathan; Summers, Jason E.

2017-05-01

The linear ordered statistic (LOS) is a parameterized ordered statistic (OS) that is a weighted average of a rank-ordered sample. LOS operators are useful generalizations of aggregation as they can represent any linear aggregation, from minimum to maximum, including conventional aggregations, such as mean and median. In the fuzzy logic field, these aggregations are called ordered weighted averages (OWAs). Here, we present a method for learning LOS operators from training data, viz., data for which you know the output of the desired LOS. We then extend the learning process with regularization, such that a lower complexity or sparse LOS can be learned. Hence, we discuss what 'lower complexity' means in this context and how to represent that in the optimization procedure. Finally, we apply our learning methods to the well-known constant-false-alarm-rate (CFAR) detection problem, specifically for the case of background levels modeled by long-tailed distributions, such as the K-distribution. These backgrounds arise in several pertinent imaging problems, including the modeling of clutter in synthetic aperture radar and sonar (SAR and SAS) and in wireless communications.

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.

Littoral assessment of mine burial signatures (LAMBS): buried landmine/background spectral-signature analyses

NASA Astrophysics Data System (ADS)

Kenton, Arthur C.; Geci, Duane M.; Ray, Kristofer J.; Thomas, Clayton M.; Salisbury, John W.; Mars, John C.; Crowley, James K.; Witherspoon, Ned H.; Holloway, John H., Jr.

2004-09-01

The objective of the Office of Naval Research (ONR) Rapid Overt Reconnaissance (ROR) program and the Airborne Littoral Reconnaissance Technologies (ALRT) project's LAMBS effort is to determine if electro-optical spectral discriminants exist that are useful for the detection of land mines in littoral regions. Statistically significant buried mine overburden and background signature data were collected over a wide spectral range (0.35 to 14 μm) to identify robust spectral features that might serve as discriminants for new airborne sensor concepts. LAMBS has expanded previously collected databases to littoral areas - primarily dry and wet sandy soils - where tidal, surf, and wind conditions can severely modify spectral signatures. At AeroSense 2003, we reported completion of three buried mine collections at an inland bay, Atlantic and Gulf of Mexico beach sites. We now report LAMBS spectral database analyses results using metrics which characterize the detection performance of general types of spectral detection algorithms. These metrics include mean contrast, spectral signal-to-clutter, covariance, information content, and spectral matched filter analyses. Detection performance of the buried land mines was analyzed with regard to burial age, background type, and environmental conditions. These analyses considered features observed due to particle size differences, surface roughness, surface moisture, and compositional differences.

Comparing object recognition from binary and bipolar edge images for visual prostheses

PubMed Central

Jung, Jae-Hyun; Pu, Tian; Peli, Eli

2017-01-01

Visual prostheses require an effective representation method due to the limited display condition which has only 2 or 3 levels of grayscale in low resolution. Edges derived from abrupt luminance changes in images carry essential information for object recognition. Typical binary (black and white) edge images have been used to represent features to convey essential information. However, in scenes with a complex cluttered background, the recognition rate of the binary edge images by human observers is limited and additional information is required. The polarity of edges and cusps (black or white features on a gray background) carries important additional information; the polarity may provide shape from shading information missing in the binary edge image. This depth information may be restored by using bipolar edges. We compared object recognition rates from 16 binary edge images and bipolar edge images by 26 subjects to determine the possible impact of bipolar filtering in visual prostheses with 3 or more levels of grayscale. Recognition rates were higher with bipolar edge images and the improvement was significant in scenes with complex backgrounds. The results also suggest that erroneous shape from shading interpretation of bipolar edges resulting from pigment rather than boundaries of shape may confound the recognition. PMID:28458481

Detecting and visualizing weak signatures in hyperspectral data

NASA Astrophysics Data System (ADS)

MacPherson, Duncan James

This thesis evaluates existing techniques for detecting weak spectral signatures from remotely sensed hyperspectral data. Algorithms are presented that successfully detect hard-to-find 'mystery' signatures in unknown cluttered backgrounds. The term 'mystery' is used to describe a scenario where the spectral target and background endmembers are unknown. Sub-Pixel analysis and background suppression are used to find deeply embedded signatures which can be less than 10% of the total signal strength. Existing 'mystery target' detection algorithms are derived and compared. Several techniques are shown to be superior both visually and quantitatively. Detection performance is evaluated using confidence metrics that are developed. A multiple algorithm approach is shown to improve detection confidence significantly. Although the research focuses on remote sensing applications, the algorithms presented can be applied to a wide variety of diverse fields such as medicine, law enforcement, manufacturing, earth science, food production, and astrophysics. The algorithms are shown to be general and can be applied to both the reflective and emissive parts of the electromagnetic spectrum. The application scope is a broad one and the final results open new opportunities for many specific applications including: land mine detection, pollution and hazardous waste detection, crop abundance calculations, volcanic activity monitoring, detecting diseases in food, automobile or airplane target recognition, cancer detection, mining operations, extracting galactic gas emissions, etc.

Littoral Assessment of Mine Burial Signatures (LAMBS) buried land mine/background spectral signature analyses

USGS Publications Warehouse

Kenton, A.C.; Geci, D.M.; Ray, K.J.; Thomas, C.M.; Salisbury, J.W.; Mars, J.C.; Crowley, J.K.; Witherspoon, N.H.; Holloway, J.H.; Harmon R.S.Broach J.T.Holloway, Jr. J.H.

2004-01-01

The objective of the Office of Naval Research (ONR) Rapid Overt Reconnaissance (ROR) program and the Airborne Littoral Reconnaissance Technologies (ALRT) project's LAMBS effort is to determine if electro-optical spectral discriminants exist that are useful for the detection of land mines in littoral regions. Statistically significant buried mine overburden and background signature data were collected over a wide spectral range (0.35 to 14 ??m) to identify robust spectral features that might serve as discriminants for new airborne sensor concepts. LAMBS has expanded previously collected databases to littoral areas - primarily dry and wet sandy soils - where tidal, surf, and wind conditions can severely modify spectral signatures. At AeroSense 2003, we reported completion of three buried mine collections at an inland bay, Atlantic and Gulf of Mexico beach sites.1 We now report LAMBS spectral database analyses results using metrics which characterize the detection performance of general types of spectral detection algorithms. These metrics include mean contrast, spectral signal-to-clutter, covariance, information content, and spectral matched filter analyses. Detection performance of the buried land mines was analyzed with regard to burial age, background type, and environmental conditions. These analyses considered features observed due to particle size differences, surface roughness, surface moisture, and compositional differences.

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.

Tile-based parallel coordinates and its application in financial visualization

NASA Astrophysics Data System (ADS)

Alsakran, Jamal; Zhao, Ye; Zhao, Xinlei

2010-01-01

Parallel coordinates technique has been widely used in information visualization applications and it has achieved great success in visualizing multivariate data and perceiving their trends. Nevertheless, visual clutter usually weakens or even diminishes its ability when the data size increases. In this paper, we first propose a tile-based parallel coordinates, where the plotting area is divided into rectangular tiles. Each tile stores an intersection density that counts the total number of polylines intersecting with that tile. Consequently, the intersection density is mapped to optical attributes, such as color and opacity, by interactive transfer functions. The method visualizes the polylines efficiently and informatively in accordance with the density distribution, and thus, reduces visual cluttering and promotes knowledge discovery. The interactivity of our method allows the user to instantaneously manipulate the tiles distribution and the transfer functions. Specifically, the classic parallel coordinates rendering is a special case of our method when each tile represents only one pixel. A case study on a real world data set, U.S. stock mutual fund data of year 2006, is presented to show the capability of our method in visually analyzing financial data. The presented visual analysis is conducted by an expert in the domain of finance. Our method gains the support from professionals in the finance field, they embrace it as a potential investment analysis tool for mutual fund managers, financial planners, and investors.

Multiresolution wavelet analysis for efficient analysis, compression and remote display of long-term physiological signals.

PubMed

Khuan, L Y; Bister, M; Blanchfield, P; Salleh, Y M; Ali, R A; Chan, T H

2006-06-01

Increased inter-equipment connectivity coupled with advances in Web technology allows ever escalating amounts of physiological data to be produced, far too much to be displayed adequately on a single computer screen. The consequence is that large quantities of insignificant data will be transmitted and reviewed. This carries an increased risk of overlooking vitally important transients. This paper describes a technique to provide an integrated solution based on a single algorithm for the efficient analysis, compression and remote display of long-term physiological signals with infrequent short duration, yet vital events, to effect a reduction in data transmission and display cluttering and to facilitate reliable data interpretation. The algorithm analyses data at the server end and flags significant events. It produces a compressed version of the signal at a lower resolution that can be satisfactorily viewed in a single screen width. This reduced set of data is initially transmitted together with a set of 'flags' indicating where significant events occur. Subsequent transmissions need only involve transmission of flagged data segments of interest at the required resolution. Efficient processing and code protection with decomposition alone is novel. The fixed transmission length method ensures clutter-less display, irrespective of the data length. The flagging of annotated events in arterial oxygen saturation, electroencephalogram and electrocardiogram illustrates the generic property of the algorithm. Data reduction of 87% to 99% and improved displays are demonstrated.

Biomimetic Signal Processing Using the Biosonar Measurement Tool (BMT)

NASA Astrophysics Data System (ADS)

Abawi, Ahmad T.; Hursky, Paul; Porter, Michael B.; Tiemann, Chris; Martin, Stephen

2004-11-01

In this paper data recorded on the Biosonar Measurement Tool (BMT) during a target echolocation experiment are used to 1) find ways to separate target echoes from clutter echoes, 2) analyze target returns and 3) find features in target returns that distinguish them from clutter returns. The BMT is an instrumentation package used in dolphin echolocation experiments developed at SPAWARSYSCEN. It can be held by the dolphin using a bite-plate during echolocation experiments and records the movement and echolocation strategy of a target-hunting dolphin without interfering with its motion through the search field. The BMT was developed to record a variety of data from a free-swimming dolphin engaged in a bottom target detection task. These data include the three dimensional location of the dolphin, including its heading, pitch roll and velocity as well as passive acoustic data recorded on three channels. The outgoing dolphin click is recorded on one channel and the resulting echoes are recorded on the two remaining channels. For each outgoing click the BMT records a large number of echoes that come from the entire ensonified field. Given the large number of transmitted clicks and the returned echoes, it is almost impossible to find a target return from the recorded data on the BMT. As a means of separating target echoes from those of clutter, an echo-mapping tool was developed. This tool produces an echomap on which echoes from targets (and other regular objects such as surface buoys, the side of a boat and so on) stack together as tracks, while echoes from clutter are scattered. Once these tracks are identified, the retuned echoes can easily be extracted for further analysis.

Autonomous UAV-Based Mapping of Large-Scale Urban Firefights

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

Snarski, S; Scheibner, K F; Shaw, S

2006-03-09

This paper describes experimental results from a live-fire data collect designed to demonstrate the ability of IR and acoustic sensing systems to detect and map high-volume gunfire events from tactical UAVs. The data collect supports an exploratory study of the FightSight concept in which an autonomous UAV-based sensor exploitation and decision support capability is being proposed to provide dynamic situational awareness for large-scale battalion-level firefights in cluttered urban environments. FightSight integrates IR imagery, acoustic data, and 3D scene context data with prior time information in a multi-level, multi-step probabilistic-based fusion process to reliably locate and map the array of urbanmore » firing events and firepower movements and trends associated with the evolving urban battlefield situation. Described here are sensor results from live-fire experiments involving simultaneous firing of multiple sub/super-sonic weapons (2-AK47, 2-M16, 1 Beretta, 1 Mortar, 1 rocket) with high optical and acoustic clutter at ranges up to 400m. Sensor-shooter-target configurations and clutter were designed to simulate UAV sensing conditions for a high-intensity firefight in an urban environment. Sensor systems evaluated were an IR bullet tracking system by Lawrence Livermore National Laboratory (LLNL) and an acoustic gunshot detection system by Planning Systems, Inc. (PSI). The results demonstrate convincingly the ability for the LLNL and PSI sensor systems to accurately detect, separate, and localize multiple shooters and the associated shot directions during a high-intensity firefight (77 rounds in 5 sec) in a high acoustic and optical clutter environment with no false alarms. Preliminary fusion processing was also examined that demonstrated an ability to distinguish co-located shooters (shooter density), range to <0.5 m accuracy at 400m, and weapon type.« less

Ground Clutter as a Monitor of Radar Stability at Kwajalein,RMI

NASA Technical Reports Server (NTRS)

Silberstein, David S.; Wolff, David B.; Marks, David A.; Atlas, David; Pippitt, Jason L.

2007-01-01

There are many applications in which the absolute and day-to-day calibration of radar sensitivity is necessary. This is particularly so in the case of quantitative radar measurements of precipitation. While absolute calibrations can be done periodically using solar radiation, variations that occur between such absolute checks are required to maintain the accuracy of the data. The authors have developed a method for h s purpose using the radar on Kwajalein Atoll, which has been used to provide a baseline calibration for control of measurements of rainfall made by the Tropical Rainfall Measuring Mission 0T.he method u ses echoes from a multiplicity of ground targets. The average clutter echoes at the lowest elevation scan have been found to be remarkably stable from hour to hour, day to day, and month to month within better than +1 dB. They vary significantly only after either deliberate system modifications, equipment failure or unknown causes. A cumulative probability distribution of echo reflectivities (Ze in dBZ) is obtained on a daily basis. This CDF includes both the precipitation and clutter echoes. Because the precipitation echoes at Kwajalein rarely exceed 45 dBZ, selecting an upper percentile of the CDF associated with intense clutter reflectivities permits monitoring of radar stability. The reflectivity level at which the CDF attains 95% is our reference. Daily measurements of the CDFs have been made since August 1999 and have been used to correct the 7 M years of measurements and thus enhance the integrity of the global record of precipitation observed by TRMM. The method also has potential applicability to other pound radar sites.

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.

An autonomous robot inspired by insect neurophysiology pursues moving features in natural environments

NASA Astrophysics Data System (ADS)

Bagheri, Zahra M.; Cazzolato, Benjamin S.; Grainger, Steven; O'Carroll, David C.; Wiederman, Steven D.

2017-08-01

Objective. Many computer vision and robotic applications require the implementation of robust and efficient target-tracking algorithms on a moving platform. However, deployment of a real-time system is challenging, even with the computational power of modern hardware. Lightweight and low-powered flying insects, such as dragonflies, track prey or conspecifics within cluttered natural environments, illustrating an efficient biological solution to the target-tracking problem. Approach. We used our recent recordings from ‘small target motion detector’ neurons in the dragonfly brain to inspire the development of a closed-loop target detection and tracking algorithm. This model exploits facilitation, a slow build-up of response to targets which move along long, continuous trajectories, as seen in our electrophysiological data. To test performance in real-world conditions, we implemented this model on a robotic platform that uses active pursuit strategies based on insect behaviour. Main results. Our robot performs robustly in closed-loop pursuit of targets, despite a range of challenging conditions used in our experiments; low contrast targets, heavily cluttered environments and the presence of distracters. We show that the facilitation stage boosts responses to targets moving along continuous trajectories, improving contrast sensitivity and detection of small moving targets against textured backgrounds. Moreover, the temporal properties of facilitation play a useful role in handling vibration of the robotic platform. We also show that the adoption of feed-forward models which predict the sensory consequences of self-movement can significantly improve target detection during saccadic movements. Significance. Our results provide insight into the neuronal mechanisms that underlie biological target detection and selection (from a moving platform), as well as highlight the effectiveness of our bio-inspired algorithm in an artificial visual system.

Stochastic-Constraints Method in Nonstationary Hot-Clutter Cancellation Part II: Unsupervised Training Applications

DTIC Science & Technology

2003-04-01

N (1) j =1 would lead to effective cold-clutter mitigation within the output snapshot ikt, ie. eir irl - lbJO 2 IMQ kt = T RoJi~ + j - 1 2 R2 + 󈨑...I 4k-2, t j i k-.., t ] (10) Note that the particular parameters used- in [9, 2] to simulate HF scattering from the sea K=2, bo= 1, b6 =-1.9359, b2=0.998...the construction of R,+I and R,c+ 2. The system of r stochastic constraints corresponding to Wk - j , t k.lt zik- j , t for j = l,..., . (12) may then be

Comparison of simulated and actual wind shear radar data products

NASA Technical Reports Server (NTRS)

Britt, Charles L.; Crittenden, Lucille H.

1992-01-01

Prior to the development of the NASA experimental wind shear radar system, extensive computer simulations were conducted to determine the performance of the radar in combined weather and ground clutter environments. The simulation of the radar used analytical microburst models to determine weather returns and synthetic aperture radar (SAR) maps to determine ground clutter returns. These simulations were used to guide the development of hazard detection algorithms and to predict their performance. The structure of the radar simulation is reviewed. Actual flight data results from the Orlando and Denver tests are compared with simulated results. Areas of agreement and disagreement of actual and simulated results are shown.

Clutter isolation and cardiac monitoring using harmonic doppler radar with heterodyne receiver and passive RF tags.

PubMed

Singh, Aditya; Lubecke, Victor

2010-01-01

A harmonic radar employing the use of harmonic passive RF tags can be successfully used to isolate the human respiration from environmental clutter. This paper describes the successful use of heterodyne receiver architecture with Doppler radar to track the heart-rate of a human being using passive body-worn harmonic tags in presence of a controlled noise generator at distances up to 120 cm. The heterodyne system results have been compared with those of a conventional Doppler radar for cardiopulmonary monitoring that fails to isolate the noise from heart-rate in presence of a noise source.

Analysis and improved design considerations for airborne pulse Doppler radar signal processing in the detection of hazardous windshear

NASA Technical Reports Server (NTRS)

Lee, Jonggil

1990-01-01

High resolution windspeed profile measurements are needed to provide reliable detection of hazardous low altitude windshear with an airborne pulse Doppler radar. The system phase noise in a Doppler weather radar may degrade the spectrum moment estimation quality and the clutter cancellation capability which are important in windshear detection. Also the bias due to weather return Doppler spectrum skewness may cause large errors in pulse pair spectral parameter estimates. These effects are analyzed for the improvement of an airborne Doppler weather radar signal processing design. A method is presented for the direct measurement of windspeed gradient using low pulse repetition frequency (PRF) radar. This spatial gradient is essential in obtaining the windshear hazard index. As an alternative, the modified Prony method is suggested as a spectrum mode estimator for both the clutter and weather signal. Estimation of Doppler spectrum modes may provide the desired windshear hazard information without the need of any preliminary processing requirement such as clutter filtering. The results obtained by processing a NASA simulation model output support consideration of mode identification as one component of a windshear detection algorithm.

Close-range radar rainfall estimation and error analysis

NASA Astrophysics Data System (ADS)

van de Beek, C. Z.; Leijnse, H.; Hazenberg, P.; Uijlenhoet, R.

2016-08-01

Quantitative precipitation estimation (QPE) using ground-based weather radar is affected by many sources of error. The most important of these are (1) radar calibration, (2) ground clutter, (3) wet-radome attenuation, (4) rain-induced attenuation, (5) vertical variability in rain drop size distribution (DSD), (6) non-uniform beam filling and (7) variations in DSD. This study presents an attempt to separate and quantify these sources of error in flat terrain very close to the radar (1-2 km), where (4), (5) and (6) only play a minor role. Other important errors exist, like beam blockage, WLAN interferences and hail contamination and are briefly mentioned, but not considered in the analysis. A 3-day rainfall event (25-27 August 2010) that produced more than 50 mm of precipitation in De Bilt, the Netherlands, is analyzed using radar, rain gauge and disdrometer data. Without any correction, it is found that the radar severely underestimates the total rain amount (by more than 50 %). The calibration of the radar receiver is operationally monitored by analyzing the received power from the sun. This turns out to cause a 1 dB underestimation. The operational clutter filter applied by KNMI is found to incorrectly identify precipitation as clutter, especially at near-zero Doppler velocities. An alternative simple clutter removal scheme using a clear sky clutter map improves the rainfall estimation slightly. To investigate the effect of wet-radome attenuation, stable returns from buildings close to the radar are analyzed. It is shown that this may have caused an underestimation of up to 4 dB. Finally, a disdrometer is used to derive event and intra-event specific Z-R relations due to variations in the observed DSDs. Such variations may result in errors when applying the operational Marshall-Palmer Z-R relation. Correcting for all of these effects has a large positive impact on the radar-derived precipitation estimates and yields a good match between radar QPE and gauge measurements, with a difference of 5-8 %. This shows the potential of radar as a tool for rainfall estimation, especially at close ranges, but also underlines the importance of applying radar correction methods as individual errors can have a large detrimental impact on the QPE performance of the radar.

The Neural Dynamics of Attentional Selection in Natural Scenes.

PubMed

Kaiser, Daniel; Oosterhof, Nikolaas N; Peelen, Marius V

2016-10-12

The human visual system can only represent a small subset of the many objects present in cluttered scenes at any given time, such that objects compete for representation. Despite these processing limitations, the detection of object categories in cluttered natural scenes is remarkably rapid. How does the brain efficiently select goal-relevant objects from cluttered scenes? In the present study, we used multivariate decoding of magneto-encephalography (MEG) data to track the neural representation of within-scene objects as a function of top-down attentional set. Participants detected categorical targets (cars or people) in natural scenes. The presence of these categories within a scene was decoded from MEG sensor patterns by training linear classifiers on differentiating cars and people in isolation and testing these classifiers on scenes containing one of the two categories. The presence of a specific category in a scene could be reliably decoded from MEG response patterns as early as 160 ms, despite substantial scene clutter and variation in the visual appearance of each category. Strikingly, we find that these early categorical representations fully depend on the match between visual input and top-down attentional set: only objects that matched the current attentional set were processed to the category level within the first 200 ms after scene onset. A sensor-space searchlight analysis revealed that this early attention bias was localized to lateral occipitotemporal cortex, reflecting top-down modulation of visual processing. These results show that attention quickly resolves competition between objects in cluttered natural scenes, allowing for the rapid neural representation of goal-relevant objects. Efficient attentional selection is crucial in many everyday situations. For example, when driving a car, we need to quickly detect obstacles, such as pedestrians crossing the street, while ignoring irrelevant objects. How can humans efficiently perform such tasks, given the multitude of objects contained in real-world scenes? Here we used multivariate decoding of magnetoencephalogaphy data to characterize the neural underpinnings of attentional selection in natural scenes with high temporal precision. We show that brain activity quickly tracks the presence of objects in scenes, but crucially only for those objects that were immediately relevant for the participant. These results provide evidence for fast and efficient attentional selection that mediates the rapid detection of goal-relevant objects in real-world environments. Copyright © 2016 the authors 0270-6474/16/3610522-07$15.00/0.

A hyperspectral imagery anomaly detection algorithm based on local three-dimensional orthogonal subspace projection

NASA Astrophysics Data System (ADS)

Zhang, Xing; Wen, Gongjian

2015-10-01

Anomaly detection (AD) becomes increasingly important in hyperspectral imagery analysis with many practical applications. Local orthogonal subspace projection (LOSP) detector is a popular anomaly detector which exploits local endmembers/eigenvectors around the pixel under test (PUT) to construct background subspace. However, this subspace only takes advantage of the spectral information, but the spatial correlat ion of the background clutter is neglected, which leads to the anomaly detection result sensitive to the accuracy of the estimated subspace. In this paper, a local three dimensional orthogonal subspace projection (3D-LOSP) algorithm is proposed. Firstly, under the jointly use of both spectral and spatial information, three directional background subspaces are created along the image height direction, the image width direction and the spectral direction, respectively. Then, the three corresponding orthogonal subspaces are calculated. After that, each vector along three direction of the local cube is projected onto the corresponding orthogonal subspace. Finally, a composite score is given through the three direction operators. In 3D-LOSP, the anomalies are redefined as the target not only spectrally different to the background, but also spatially distinct. Thanks to the addition of the spatial information, the robustness of the anomaly detection result has been improved greatly by the proposed 3D-LOSP algorithm. It is noteworthy that the proposed algorithm is an expansion of LOSP and this ideology can inspire many other spectral-based anomaly detection methods. Experiments with real hyperspectral images have proved the stability of the detection result.

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.

Estimation of contour motion and deformation for nonrigid object tracking

NASA Astrophysics Data System (ADS)

Shao, Jie; Porikli, Fatih; Chellappa, Rama

2007-08-01

We present an algorithm for nonrigid contour tracking in heavily cluttered background scenes. Based on the properties of nonrigid contour movements, a sequential framework for estimating contour motion and deformation is proposed. We solve the nonrigid contour tracking problem by decomposing it into three subproblems: motion estimation, deformation estimation, and shape regulation. First, we employ a particle filter to estimate the global motion parameters of the affine transform between successive frames. Then we generate a probabilistic deformation map to deform the contour. To improve robustness, multiple cues are used for deformation probability estimation. Finally, we use a shape prior model to constrain the deformed contour. This enables us to retrieve the occluded parts of the contours and accurately track them while allowing shape changes specific to the given object types. Our experiments show that the proposed algorithm significantly improves the tracker performance.

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.

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.

From Awareness to Action: Determining the climate sensitivities that influence decision makers

NASA Astrophysics Data System (ADS)

Brown, C.

2017-12-01

Through the growth of computing power and analytical methods, a range of valuable and innovative tools allow the exhaustive exploration of a water system's response to a limitless set of scenarios. Similarly, possible adaptive actions can be evaluated across this broad set of possible futures. Finally, an ever increasing set of performance indicators is available to judge the relative value of a particular action over others. However, it's unclear whether this is improving the flow of actionable information or further cluttering it. This presentation will share lessons learned and other intuitions from a set of experiences engaging with public and private water managers and investors in the use of robustness-based climate vulnerability and adaptation analysis. Based on this background, a case for reductionism and focus on financial vulnerability will be forwarded. In addition, considerations for simpler, practical approaches for smaller water utilities will be discussed.

Toward transparent and self-activated graphene harmonic transponder sensors

NASA Astrophysics Data System (ADS)

Huang, Haiyu Harry; Sakhdari, Maryam; Hajizadegan, Mehdi; Shahini, Ali; Akinwande, Deji; Chen, Pai-Yen

2016-04-01

We propose the concept and design of a transparent, flexible, and self-powered wireless sensor comprising a graphene-based sensor/frequency-modulator circuitry and a graphene antenna. In this all-graphene device, the multilayered-graphene antenna receives the fundamental tone at C band and retransmits the frequency-modulated sensed signal (harmonic tone) at X band. The frequency orthogonality between the received/re-transmitted signals may enable high-performance sensing in severe interference/clutter background. Here, a fully passive, quad-ring frequency multiplier is proposed using graphene field-effect transistors, of which the unique ambipolar charge transports render a frequency doubling effect with conversion gain being chemically sensitive to exposed gas/molecular/chemical/infectious agents. This transparent, light-weight, and self-powered system may potentially benefit a number of wireless sensing and diagnosis applications, particularly for smart contact lenses/glasses and microscope slides that require high optical transparency.

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.

Human body segmentation via data-driven graph cut.

PubMed

Li, Shifeng; Lu, Huchuan; Shao, Xingqing

2014-11-01

Human body segmentation is a challenging and important problem in computer vision. Existing methods usually entail a time-consuming training phase for prior knowledge learning with complex shape matching for body segmentation. In this paper, we propose a data-driven method that integrates top-down body pose information and bottom-up low-level visual cues for segmenting humans in static images within the graph cut framework. The key idea of our approach is first to exploit human kinematics to search for body part candidates via dynamic programming for high-level evidence. Then, by using the body parts classifiers, obtaining bottom-up cues of human body distribution for low-level evidence. All the evidence collected from top-down and bottom-up procedures are integrated in a graph cut framework for human body segmentation. Qualitative and quantitative experiment results demonstrate the merits of the proposed method in segmenting human bodies with arbitrary poses from cluttered backgrounds.

Universal explosive detection system for homeland security applications

NASA Astrophysics Data System (ADS)

Lee, Vincent Y.; Bromberg, Edward E. A.

2010-04-01

L-3 Communications CyTerra Corporation has developed a high throughput universal explosive detection system (PassPort) to automatically screen the passengers in airports without requiring them to remove their shoes. The technical approach is based on the patented energetic material detection (EMD) technology. By analyzing the results of sample heating with an infrared camera, one can distinguish the deflagration or decomposition of an energetic material from other clutters such as flammables and general background substances. This becomes the basis of a universal explosive detection system that does not require a library and is capable of detecting trace levels of explosives with a low false alarm rate. The PassPort is a simple turnstile type device and integrates a non-intrusive aerodynamic sampling scheme that has been shown capable of detecting trace levels of explosives on shoes. A detailed description of the detection theory and the automated sampling techniques, as well as the field test results, will be presented.

A visual tracking method based on deep learning without online model updating

NASA Astrophysics Data System (ADS)

Tang, Cong; Wang, Yicheng; Feng, Yunsong; Zheng, Chao; Jin, Wei

2018-02-01

The paper proposes a visual tracking method based on deep learning without online model updating. In consideration of the advantages of deep learning in feature representation, deep model SSD (Single Shot Multibox Detector) is used as the object extractor in the tracking model. Simultaneously, the color histogram feature and HOG (Histogram of Oriented Gradient) feature are combined to select the tracking object. In the process of tracking, multi-scale object searching map is built to improve the detection performance of deep detection model and the tracking efficiency. In the experiment of eight respective tracking video sequences in the baseline dataset, compared with six state-of-the-art methods, the method in the paper has better robustness in the tracking challenging factors, such as deformation, scale variation, rotation variation, illumination variation, and background clutters, moreover, its general performance is better than other six tracking methods.

A protocol for evaluating video trackers under real-world conditions.

PubMed

Nawaz, Tahir; Cavallaro, Andrea

2013-04-01

The absence of a commonly adopted performance evaluation framework is hampering advances in the design of effective video trackers. In this paper, we present a single-score evaluation measure and a protocol to objectively compare trackers. The proposed measure evaluates tracking accuracy and failure, and combines them for both summative and formative performance assessment. The proposed protocol is composed of a set of trials that evaluate the robustness of trackers on a range of test scenarios representing several real-world conditions. The protocol is validated on a set of sequences with a diversity of targets (head, vehicle and person) and challenges (occlusions, background clutter, pose changes and scale changes) using six state-of-the-art trackers, highlighting their strengths and weaknesses on more than 187000 frames. The software implementing the protocol and the evaluation results are made available online and new results can be included, thus facilitating the comparison of trackers.

Adaptive Shape Kernel-Based Mean Shift Tracker in Robot Vision System

PubMed Central

2016-01-01

This paper proposes an adaptive shape kernel-based mean shift tracker using a single static camera for the robot vision system. The question that we address in this paper is how to construct such a kernel shape that is adaptive to the object shape. We perform nonlinear manifold learning technique to obtain the low-dimensional shape space which is trained by training data with the same view as the tracking video. The proposed kernel searches the shape in the low-dimensional shape space obtained by nonlinear manifold learning technique and constructs the adaptive kernel shape in the high-dimensional shape space. It can improve mean shift tracker performance to track object position and object contour and avoid the background clutter. In the experimental part, we take the walking human as example to validate that our method is accurate and robust to track human position and describe human contour. PMID:27379165

Flag-based detection of weak gas signatures in long-wave infrared hyperspectral image sequences

NASA Astrophysics Data System (ADS)

Marrinan, Timothy; Beveridge, J. Ross; Draper, Bruce; Kirby, Michael; Peterson, Chris

2016-05-01

We present a flag manifold based method for detecting chemical plumes in long-wave infrared hyperspectral movies. The method encodes temporal and spatial information related to a hyperspectral pixel into a flag, or nested sequence of linear subspaces. The technique used to create the flags pushes information about the background clutter, ambient conditions, and potential chemical agents into the leading elements of the flags. Exploiting this temporal information allows for a detection algorithm that is sensitive to the presence of weak signals. This method is compared to existing techniques qualitatively on real data and quantitatively on synthetic data to show that the flag-based algorithm consistently performs better on data when the SINRdB is low, and beats the ACE and MF algorithms in probability of detection for low probabilities of false alarm even when the SINRdB is high.

Ultrawideband radar; Proceedings of the Meeting, Los Angeles, CA, Jan. 22, 23, 1992

NASA Astrophysics Data System (ADS)

Lahaie, Ivan J.

1992-05-01

The present conference discusses a canonical representation of the radar range equation in the time domain, two-way beam patterns fron ultrawideband arrays, modeling of ultrawideband sea clutter, the analysis of time-domain ultrawideband radar signals, a frequency-agile ultrawideband microwave source, and the performance of ultrawideband antennas. Also discussed are the diffraction of ultrawideband radar pulses, sea-clutter measurements with an ultrawideband X-band radar having variable resolution, results from a VHF-impulse SAR, an ultrawideband differential radar, the development of 2D target images from ultrawideband radar systems, ultrawideband generators, and the radiated waveform of a monolithic photoconductive GaAs pulser. (For individual items see A93-28202 to A93-28223)

Simplified formulae for the estimation of offshore wind turbines clutter on marine radars.

PubMed

Grande, Olatz; Cañizo, Josune; Angulo, Itziar; Jenn, David; Danoon, Laith R; Guerra, David; de la Vega, David

2014-01-01

The potential impact that offshore wind farms may cause on nearby marine radars should be considered before the wind farm is installed. Strong radar echoes from the turbines may degrade radars' detection capability in the area around the wind farm. Although conventional computational methods provide accurate results of scattering by wind turbines, they are not directly implementable in software tools that can be used to conduct the impact studies. This paper proposes a simple model to assess the clutter that wind turbines may generate on marine radars. This method can be easily implemented in the system modeling software tools for the impact analysis of a wind farm in a real scenario.

Simplified Formulae for the Estimation of Offshore Wind Turbines Clutter on Marine Radars

PubMed Central

Grande, Olatz; Cañizo, Josune; Jenn, David; Danoon, Laith R.; Guerra, David

2014-01-01

The potential impact that offshore wind farms may cause on nearby marine radars should be considered before the wind farm is installed. Strong radar echoes from the turbines may degrade radars' detection capability in the area around the wind farm. Although conventional computational methods provide accurate results of scattering by wind turbines, they are not directly implementable in software tools that can be used to conduct the impact studies. This paper proposes a simple model to assess the clutter that wind turbines may generate on marine radars. This method can be easily implemented in the system modeling software tools for the impact analysis of a wind farm in a real scenario. PMID:24782682

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.

Operational space weather product development and validation at the joint SMC-AFRL Rapid Prototyping Center

NASA Astrophysics Data System (ADS)

Quigley, S.

The Air Force Research Laboratory (AFRL/VSB) and Detachment 11, Space &Missile Systems Center (SMC, Det 11/CIT) have combined efforts to design, develop, test, and implement graphical products for the Air Force's space weather operations center. These products are generated to analyze, specify, and forecast the effects of the near-earth space environment on Department of Defense systems and communications. Jointly-developed products that have been, or will soon be added to real-time operations include: 1) the Operational Space Environment Network Display (OpSEND) suit - a set of four products that address HF communication, UHF satellite communication scintillation, radar auroral clutter, and GP S single- frequency errors; 2) a solar radio background and burst effects (SoRBE) product suite; and C) a meteor effects (ME) product suite. The RPC is also involved in a rather substantial "V&V" effort to produce multiple operational product verifications and validations, with an added end goal of a generalized validation software package. The presentation will provide a general overview of the RPC and each of the products mentioned above, to include background science, operational history, inputs, outputs, dissemination, and customer uses for each.

NIR small arms muzzle flash

NASA Astrophysics Data System (ADS)

Montoya, Joseph; Kennerly, Stephen; Rede, Edward

2010-04-01

Utilization of Near-Infrared (NIR) spectral features in a muzzle flash will allow for small arms detection using low cost silicon (Si)-based imagers. Detection of a small arms muzzle flash in a particular wavelength region is dependent on the intensity of that emission, the efficiency of source emission transmission through the atmosphere, and the relative intensity of the background scene. The NIR muzzle flash signature exists in the relatively large Si spectral response wavelength region of 300 nm-1100 nm, which allows for use of commercial-off-the-shelf (COTS) Si-based detectors. The alkali metal origin of the NIR spectral features in the 7.62 × 39-mm round muzzle flash is discussed, and the basis for the spectral bandwidth is examined, using a calculated Voigt profile. This report will introduce a model of the 7.62 × 39-mm NIR muzzle flash signature based on predicted source characteristics. Atmospheric limitations based on NIR spectral regions are investigated in relation to the NIR muzzle flash signature. A simple signal-to-clutter ratio (SCR) metric is used to predict sensor performance based on a model of radiance for the source and solar background and pixel registered image subtraction.

Two-stage perceptual learning to break visual crowding.

PubMed

Zhu, Ziyun; Fan, Zhenzhi; Fang, Fang

2016-01-01

When a target is presented with nearby flankers in the peripheral visual field, it becomes harder to identify, which is referred to as crowding. Crowding sets a fundamental limit of object recognition in peripheral vision, preventing us from fully appreciating cluttered visual scenes. We trained adult human subjects on a crowded orientation discrimination task and investigated whether crowding could be completely eliminated by training. We discovered a two-stage learning process with this training task. In the early stage, when the target and flankers were separated beyond a certain distance, subjects acquired a relatively general ability to break crowding, as evidenced by the fact that the breaking of crowding could transfer to another crowded orientation, even a crowded motion stimulus, although the transfer to the opposite visual hemi-field was weak. In the late stage, like many classical perceptual learning effects, subjects' performance gradually improved and showed specificity to the trained orientation. We also found that, when the target and flankers were spaced too finely, training could only reduce, rather than completely eliminate, the crowding effect. This two-stage learning process illustrates a learning strategy for our brain to deal with the notoriously difficult problem of identifying peripheral objects in clutter. The brain first learned to solve the "easy and general" part of the problem (i.e., improving the processing resolution and segmenting the target and flankers) and then tackle the "difficult and specific" part (i.e., refining the representation of the target).

Measurements of scene spectral radiance variability

NASA Astrophysics Data System (ADS)

Seeley, Juliette A.; Wack, Edward C.; Mooney, Daniel L.; Muldoon, Michael; Shey, Shen; Upham, Carolyn A.; Harvey, John M.; Czerwinski, Richard N.; Jordan, Michael P.; Vallières, Alexandre; Chamberland, Martin

2006-05-01

Detection performance of LWIR passive standoff chemical agent sensors is strongly influenced by various scene parameters, such as atmospheric conditions, temperature contrast, concentration-path length product (CL), agent absorption coefficient, and scene spectral variability. Although temperature contrast, CL, and agent absorption coefficient affect the detected signal in a predictable manner, fluctuations in background scene spectral radiance have less intuitive consequences. The spectral nature of the scene is not problematic in and of itself; instead it is spatial and temporal fluctuations in the scene spectral radiance that cannot be entirely corrected for with data processing. In addition, the consequence of such variability is a function of the spectral signature of the agent that is being detected and is thus different for each agent. To bracket the performance of background-limited (low sensor NEDN), passive standoff chemical sensors in the range of relevant conditions, assessment of real scene data is necessary1. Currently, such data is not widely available2. To begin to span the range of relevant scene conditions, we have acquired high fidelity scene spectral radiance measurements with a Telops FTIR imaging spectrometer 3. We have acquired data in a variety of indoor and outdoor locations at different times of day and year. Some locations include indoor office environments, airports, urban and suburban scenes, waterways, and forest. We report agent-dependent clutter measurements for three of these backgrounds.

Perception of silent and motionless prey on vegetation by echolocation in the gleaning bat Micronycteris microtis.

PubMed

Geipel, Inga; Jung, Kirsten; Kalko, Elisabeth K V

2013-03-07

Gleaning insectivorous bats that forage by using echolocation within dense forest vegetation face the sensorial challenge of acoustic masking effects. Active perception of silent and motionless prey in acoustically cluttered environments by echolocation alone has thus been regarded impossible. The gleaning insectivorous bat Micronycteris microtis however, forages in dense understory vegetation and preys on insects, including dragonflies, which rest silent and motionless on vegetation. From behavioural experiments, we show that M. microtis uses echolocation as the sole sensorial modality for successful prey perception within a complex acoustic environment. All individuals performed a stereotypical three-dimensional hovering flight in front of prey items, while continuously emitting short, multi-harmonic, broadband echolocation calls. We observed a high precision in target localization which suggests that M. microtis perceives a detailed acoustic image of the prey based on shape, surface structure and material. Our experiments provide, to our knowledge, the first evidence that a gleaning bat uses echolocation alone for successful detection, classification and precise localization of silent and motionless prey in acoustic clutter. Overall, we conclude that the three-dimensional hovering flight of M. microtis in combination with a frequent emission of short, high-frequency echolocation calls is the key for active prey perception in acoustically highly cluttered environments.

Perception of silent and motionless prey on vegetation by echolocation in the gleaning bat Micronycteris microtis

PubMed Central

Geipel, Inga; Jung, Kirsten; Kalko, Elisabeth K. V.

2013-01-01

Gleaning insectivorous bats that forage by using echolocation within dense forest vegetation face the sensorial challenge of acoustic masking effects. Active perception of silent and motionless prey in acoustically cluttered environments by echolocation alone has thus been regarded impossible. The gleaning insectivorous bat Micronycteris microtis however, forages in dense understory vegetation and preys on insects, including dragonflies, which rest silent and motionless on vegetation. From behavioural experiments, we show that M. microtis uses echolocation as the sole sensorial modality for successful prey perception within a complex acoustic environment. All individuals performed a stereotypical three-dimensional hovering flight in front of prey items, while continuously emitting short, multi-harmonic, broadband echolocation calls. We observed a high precision in target localization which suggests that M. microtis perceives a detailed acoustic image of the prey based on shape, surface structure and material. Our experiments provide, to our knowledge, the first evidence that a gleaning bat uses echolocation alone for successful detection, classification and precise localization of silent and motionless prey in acoustic clutter. Overall, we conclude that the three-dimensional hovering flight of M. microtis in combination with a frequent emission of short, high-frequency echolocation calls is the key for active prey perception in acoustically highly cluttered environments. PMID:23325775

Using an Improved SIFT Algorithm and Fuzzy Closed-Loop Control Strategy for Object Recognition in Cluttered Scenes

PubMed Central

Nie, Haitao; Long, Kehui; Ma, Jun; Yue, Dan; Liu, Jinguo

2015-01-01

Partial occlusions, large pose variations, and extreme ambient illumination conditions generally cause the performance degradation of object recognition systems. Therefore, this paper presents a novel approach for fast and robust object recognition in cluttered scenes based on an improved scale invariant feature transform (SIFT) algorithm and a fuzzy closed-loop control method. First, a fast SIFT algorithm is proposed by classifying SIFT features into several clusters based on several attributes computed from the sub-orientation histogram (SOH), in the feature matching phase only features that share nearly the same corresponding attributes are compared. Second, a feature matching step is performed following a prioritized order based on the scale factor, which is calculated between the object image and the target object image, guaranteeing robust feature matching. Finally, a fuzzy closed-loop control strategy is applied to increase the accuracy of the object recognition and is essential for autonomous object manipulation process. Compared to the original SIFT algorithm for object recognition, the result of the proposed method shows that the number of SIFT features extracted from an object has a significant increase, and the computing speed of the object recognition processes increases by more than 40%. The experimental results confirmed that the proposed method performs effectively and accurately in cluttered scenes. PMID:25714094

Single vs. dual color fire detection systems: operational tradeoffs

NASA Astrophysics Data System (ADS)

Danino, Meir; Danan, Yossef; Sinvani, Moshe

2017-10-01

In attempt to supply a reasonable fire plume detection, multinational cooperation with significant capital is invested in the development of two major Infra-Red (IR) based fire detection alternatives, single-color IR (SCIR) and dual-color IR (DCIR). False alarm rate was expected to be high not only as a result of real heat sources but mainly due to the IR natural clutter especially solar reflections clutter. SCIR uses state-of-the-art technology and sophisticated algorithms to filter out threats from clutter. On the other hand, DCIR are aiming at using additional spectral band measurements (acting as a guard), to allow the implementation of a simpler and more robust approach for performing the same task. In this paper we present the basics of SCIR & DCIR architecture and the main differences between them. In addition, we will present the results from a thorough study conducted for the purpose of learning about the added value of the additional data available from the second spectral band. Here we consider the two CO2 bands of 4-5 micron and of 2.5-3 micron band as well as off peak band (guard). The findings of this study refer also to Missile warning systems (MWS) efficacy, in terms of operational value. We also present a new approach for tunable filter to such sensor.

Feature aided Monte Carlo probabilistic data association filter for ballistic missile tracking

NASA Astrophysics Data System (ADS)

Ozdemir, Onur; Niu, Ruixin; Varshney, Pramod K.; Drozd, Andrew L.; Loe, Richard

2011-05-01

The problem of ballistic missile tracking in the presence of clutter is investigated. Probabilistic data association filter (PDAF) is utilized as the basic filtering algorithm. We propose to use sequential Monte Carlo methods, i.e., particle filters, aided with amplitude information (AI) in order to improve the tracking performance of a single target in clutter when severe nonlinearities exist in the system. We call this approach "Monte Carlo probabilistic data association filter with amplitude information (MCPDAF-AI)." Furthermore, we formulate a realistic problem in the sense that we use simulated radar cross section (RCS) data for a missile warhead and a cylinder chaff using Lucernhammer1, a state of the art electromagnetic signature prediction software, to model target and clutter amplitude returns as additional amplitude features which help to improve data association and tracking performance. A performance comparison is carried out between the extended Kalman filter (EKF) and the particle filter under various scenarios using single and multiple sensors. The results show that, when only one sensor is used, the MCPDAF performs significantly better than the EKF in terms of tracking accuracy under severe nonlinear conditions for ballistic missile tracking applications. However, when the number of sensors is increased, even under severe nonlinear conditions, the EKF performs as well as the MCPDAF.

Acquisition and processing of advanced sensor data for ERW and UXO detection and classification

NASA Astrophysics Data System (ADS)

Schultz, Gregory M.; Keranen, Joe; Miller, Jonathan S.; Shubitidze, Fridon

2014-06-01

The remediation of explosive remnants of war (ERW) and associated unexploded ordnance (UXO) has seen improvements through the injection of modern technological advances and streamlined standard operating procedures. However, reliable and cost-effective detection and geophysical mapping of sites contaminated with UXO such as cluster munitions, abandoned ordnance, and improvised explosive devices rely on the ability to discriminate hazardous items from metallic clutter. In addition to anthropogenic clutter, handheld and vehicle-based metal detector systems are plagued by natural geologic and environmental noise in many post conflict areas. We present new and advanced electromagnetic induction (EMI) technologies including man-portable and towed EMI arrays and associated data processing software. While these systems feature vastly different form factors and transmit-receive configurations, they all exhibit several fundamental traits that enable successful classification of EMI anomalies. Specifically, multidirectional sampling of scattered magnetic fields from targets and corresponding high volume of unique data provide rich information for extracting useful classification features for clutter rejection analysis. The quality of classification features depends largely on the extent to which the data resolve unique physics-based parameters. To date, most of the advanced sensors enable high quality inversion by producing data that are extremely rich in spatial content through multi-angle illumination and multi-point reception.

Efficient Strategies for Estimating the Spatial Coherence of Backscatter

PubMed Central

Hyun, Dongwoon; Crowley, Anna Lisa C.; Dahl, Jeremy J.

2017-01-01

The spatial coherence of ultrasound backscatter has been proposed to reduce clutter in medical imaging, to measure the anisotropy of the scattering source, and to improve the detection of blood flow. These techniques rely on correlation estimates that are obtained using computationally expensive strategies. In this study, we assess existing spatial coherence estimation methods and propose three computationally efficient modifications: a reduced kernel, a downsampled receive aperture, and the use of an ensemble correlation coefficient. The proposed methods are implemented in simulation and in vivo studies. Reducing the kernel to a single sample improved computational throughput and improved axial resolution. Downsampling the receive aperture was found to have negligible effect on estimator variance, and improved computational throughput by an order of magnitude for a downsample factor of 4. The ensemble correlation estimator demonstrated lower variance than the currently used average correlation. Combining the three methods, the throughput was improved 105-fold in simulation with a downsample factor of 4 and 20-fold in vivo with a downsample factor of 2. PMID:27913342

Fast ℓ1-regularized space-time adaptive processing using alternating direction method of multipliers

NASA Astrophysics Data System (ADS)

Qin, Lilong; Wu, Manqing; Wang, Xuan; Dong, Zhen

2017-04-01

Motivated by the sparsity of filter coefficients in full-dimension space-time adaptive processing (STAP) algorithms, this paper proposes a fast ℓ1-regularized STAP algorithm based on the alternating direction method of multipliers to accelerate the convergence and reduce the calculations. The proposed algorithm uses a splitting variable to obtain an equivalent optimization formulation, which is addressed with an augmented Lagrangian method. Using the alternating recursive algorithm, the method can rapidly result in a low minimum mean-square error without a large number of calculations. Through theoretical analysis and experimental verification, we demonstrate that the proposed algorithm provides a better output signal-to-clutter-noise ratio performance than other algorithms.

Assessment of C-band Polarimetric Radar Rainfall Measurements During Strong Attenuation.

NASA Astrophysics Data System (ADS)

Paredes-Victoria, P. N.; Rico-Ramirez, M. A.; Pedrozo-Acuña, A.

2016-12-01

In the modern hydrological modelling and their applications on flood forecasting systems and climate modelling, reliable spatiotemporal rainfall measurements are the keystone. Raingauges are the foundation in hydrology to collect rainfall data, however they are prone to errors (e.g. systematic, malfunctioning, and instrumental errors). Moreover rainfall data from gauges is often used to calibrate and validate weather radar rainfall, which is distributed in space. Therefore, it is important to apply techniques to control the quality of the raingauge data in order to guarantee a high level of confidence in rainfall measurements for radar calibration and numerical weather modelling. Also, the reliability of radar data is often limited because of the errors in the radar signal (e.g. clutter, variation of the vertical reflectivity profile, beam blockage, attenuation, etc) which need to be corrected in order to increase the accuracy of the radar rainfall estimation. This paper presents a method for raingauge-measurement quality-control correction based on the inverse distance weighted as a function of correlated climatology (i.e. performed by using the reflectivity from weather radar). Also a Clutter Mitigation Decision (CMD) algorithm is applied for clutter filtering process, finally three algorithms based on differential phase measurements are applied for radar signal attenuation correction. The quality-control method proves that correlated climatology is very sensitive in the first 100 kilometres for this area. The results also showed that ground clutter affects slightly the radar measurements due to the low gradient of the terrain in the area. However, strong radar signal attenuation is often found in this data set due to the heavy storms that take place in this region and the differential phase measurements are crucial to correct for attenuation at C-band frequencies. The study area is located in Sabancuy-Campeche, Mexico (Latitude 18.97 N, Longitude 91.17º W) and the radar rainfall measurements are obtained from a C-band polarimetric radar whereas raingauge measurements come from stations with 10-min and 24-hr time resolutions.

Autonomous UAV-based mapping of large-scale urban firefights

NASA Astrophysics Data System (ADS)

Snarski, Stephen; Scheibner, Karl; Shaw, Scott; Roberts, Randy; LaRow, Andy; Breitfeller, Eric; Lupo, Jasper; Nielson, Darron; Judge, Bill; Forren, Jim

2006-05-01

This paper describes experimental results from a live-fire data collect designed to demonstrate the ability of IR and acoustic sensing systems to detect and map high-volume gunfire events from tactical UAVs. The data collect supports an exploratory study of the FightSight concept in which an autonomous UAV-based sensor exploitation and decision support capability is being proposed to provide dynamic situational awareness for large-scale battalion-level firefights in cluttered urban environments. FightSight integrates IR imagery, acoustic data, and 3D scene context data with prior time information in a multi-level, multi-step probabilistic-based fusion process to reliably locate and map the array of urban firing events and firepower movements and trends associated with the evolving urban battlefield situation. Described here are sensor results from live-fire experiments involving simultaneous firing of multiple sub/super-sonic weapons (2-AK47, 2-M16, 1 Beretta, 1 Mortar, 1 rocket) with high optical and acoustic clutter at ranges up to 400m. Sensor-shooter-target configurations and clutter were designed to simulate UAV sensing conditions for a high-intensity firefight in an urban environment. Sensor systems evaluated were an IR bullet tracking system by Lawrence Livermore National Laboratory (LLNL) and an acoustic gunshot detection system by Planning Systems, Inc. (PSI). The results demonstrate convincingly the ability for the LLNL and PSI sensor systems to accurately detect, separate, and localize multiple shooters and the associated shot directions during a high-intensity firefight (77 rounds in 5 sec) in a high acoustic and optical clutter environment with very low false alarms. Preliminary fusion processing was also examined that demonstrated an ability to distinguish co-located shooters (shooter density), range to <0.5 m accuracy at 400m, and weapon type. The combined results of the high-intensity firefight data collect and a detailed systems study demonstrate the readiness of the FightSight concept for full system development and integration.

Comparison of mechanisms involved in image enhancement of Tissue Harmonic Imaging

NASA Astrophysics Data System (ADS)

Cleveland, Robin O.; Jing, Yuan

2006-05-01

Processes that have been suggested as responsible for the improved imaging in Tissue Harmonic Imaging (THI) include: 1) reduced sensitivity to reverberation, 2) reduced sensitivity to aberration, and 3) reduction in the amplitude of diffraction side lobes. A three-dimensional model of the forward propagation of nonlinear sound beams in media with arbitrary spatial properties (a generalized KZK equation) was developed and solved using a time-domain code. The numerical simulations were validated through experiments with tissue mimicking phantoms. The impact of aberration from tissue-like media was determined through simulations using three-dimensional maps of tissue properties derived from datasets available through the Visible Female Project. The experiments and simulations demonstrated that second harmonic imaging suffers less clutter from reverberation and side-lobes but is not immune to aberration effects. The results indicate that side lobe suppression is the most significant reason for the improvement of second harmonic imaging.

The estimation of pointing angle and normalized surface scattering cross section from GEOS-3 radar altimeter measurements

NASA Technical Reports Server (NTRS)

Brown, G. S.; Curry, W. J.

1977-01-01

The statistical error of the pointing angle estimation technique is determined as a function of the effective receiver signal to noise ratio. Other sources of error are addressed and evaluated with inadequate calibration being of major concern. The impact of pointing error on the computation of normalized surface scattering cross section (sigma) from radar and the waveform attitude induced altitude bias is considered and quantitative results are presented. Pointing angle and sigma processing algorithms are presented along with some initial data. The intensive mode clean vs. clutter AGC calibration problem is analytically resolved. The use clutter AGC data in the intensive mode is confirmed as the correct calibration set for the sigma computations.

Fractal active contour model for segmenting the boundary of man-made target in nature scenes

NASA Astrophysics Data System (ADS)

Li, Min; Tang, Yandong; Wang, Lidi; Shi, Zelin

2006-02-01

In this paper, a novel geometric active contour model based on the fractal dimension feature to extract the boundary of man-made target in nature scenes is presented. In order to suppress the nature clutters, an adaptive weighting function is defined using the fractal dimension feature. Then the weighting function is introduced into the geodesic active contour model to detect the boundary of man-made target. Curve driven by our proposed model can evolve gradually from the initial position to the boundary of man-made target without being disturbed by nature clutters, even if the initial curve is far away from the true boundary. Experimental results validate the effectiveness and feasibility of our model.

Fast iterative censoring CFAR algorithm for ship detection from SAR images

NASA Astrophysics Data System (ADS)

Gu, Dandan; Yue, Hui; Zhang, Yuan; Gao, Pengcheng

2017-11-01

Ship detection is one of the essential techniques for ship recognition from synthetic aperture radar (SAR) images. This paper presents a fast iterative detection procedure to eliminate the influence of target returns on the estimation of local sea clutter distributions for constant false alarm rate (CFAR) detectors. A fast block detector is first employed to extract potential target sub-images; and then, an iterative censoring CFAR algorithm is used to detect ship candidates from each target blocks adaptively and efficiently, where parallel detection is available, and statistical parameters of G0 distribution fitting local sea clutter well can be quickly estimated based on an integral image operator. Experimental results of TerraSAR-X images demonstrate the effectiveness of the proposed technique.

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

Timing matters: sonar call groups facilitate target localization in bats.

PubMed

Kothari, Ninad B; Wohlgemuth, Melville J; Hulgard, Katrine; Surlykke, Annemarie; Moss, Cynthia F

2014-01-01

To successfully negotiate a cluttered environment, an echolocating bat must control the timing of motor behaviors in response to dynamic sensory information. Here we detail the big brown bat's adaptive temporal control over sonar call production for tracking prey, moving predictably or unpredictably, under different experimental conditions. We studied the adaptive control of vocal-motor behaviors in free-flying big brown bats, Eptesicus fuscus, as they captured tethered and free-flying insects, in open and cluttered environments. We also studied adaptive sonar behavior in bats trained to track moving targets from a resting position. In each of these experiments, bats adjusted the features of their calls to separate target and clutter. Under many task conditions, flying bats produced prominent sonar sound groups identified as clusters of echolocation pulses with relatively stable intervals, surrounded by longer pulse intervals. In experiments where bats tracked approaching targets from a resting position, bats also produced sonar sound groups, and the prevalence of these sonar sound groups increased when motion of the target was unpredictable. We hypothesize that sonar sound groups produced during flight, and the sonar call doublets produced by a bat tracking a target from a resting position, help the animal resolve dynamic target location and represent the echo scene in greater detail. Collectively, our data reveal adaptive temporal control over sonar call production that allows the bat to negotiate a complex and dynamic environment.

Timing matters: sonar call groups facilitate target localization in bats

PubMed Central

Kothari, Ninad B.; Wohlgemuth, Melville J.; Hulgard, Katrine; Surlykke, Annemarie; Moss, Cynthia F.

2014-01-01

To successfully negotiate a cluttered environment, an echolocating bat must control the timing of motor behaviors in response to dynamic sensory information. Here we detail the big brown bat's adaptive temporal control over sonar call production for tracking prey, moving predictably or unpredictably, under different experimental conditions. We studied the adaptive control of vocal-motor behaviors in free-flying big brown bats, Eptesicus fuscus, as they captured tethered and free-flying insects, in open and cluttered environments. We also studied adaptive sonar behavior in bats trained to track moving targets from a resting position. In each of these experiments, bats adjusted the features of their calls to separate target and clutter. Under many task conditions, flying bats produced prominent sonar sound groups identified as clusters of echolocation pulses with relatively stable intervals, surrounded by longer pulse intervals. In experiments where bats tracked approaching targets from a resting position, bats also produced sonar sound groups, and the prevalence of these sonar sound groups increased when motion of the target was unpredictable. We hypothesize that sonar sound groups produced during flight, and the sonar call doublets produced by a bat tracking a target from a resting position, help the animal resolve dynamic target location and represent the echo scene in greater detail. Collectively, our data reveal adaptive temporal control over sonar call production that allows the bat to negotiate a complex and dynamic environment. PMID:24860509

Segmentation of vessels cluttered with cells using a physics based model.

PubMed

Schmugge, Stephen J; Keller, Steve; Nguyen, Nhat; Souvenir, Richard; Huynh, Toan; Clemens, Mark; Shin, Min C

2008-01-01

Segmentation of vessels in biomedical images is important as it can provide insight into analysis of vascular morphology, topology and is required for kinetic analysis of flow velocity and vessel permeability. Intravital microscopy is a powerful tool as it enables in vivo imaging of both vasculature and circulating cells. However, the analysis of vasculature in those images is difficult due to the presence of cells and their image gradient. In this paper, we provide a novel method of segmenting vessels with a high level of cell related clutter. A set of virtual point pairs ("vessel probes") are moved reacting to forces including Vessel Vector Flow (VVF) and Vessel Boundary Vector Flow (VBVF) forces. Incorporating the cell detection, the VVF force attracts the probes toward the vessel, while the VBVF force attracts the virtual points of the probes to localize the vessel boundary without being distracted by the image features of the cells. The vessel probes are moved according to Newtonian Physics reacting to the net of forces applied on them. We demonstrate the results on a set of five real in vivo images of liver vasculature cluttered by white blood cells. When compared against the ground truth prepared by the technician, the Root Mean Squared Error (RMSE) of segmentation with VVF and VBVF was 55% lower than the method without VVF and VBVF.

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

Clipboard

ERIC Educational Resources Information Center

Timmons, Virginia G.

1977-01-01

Thorough advance planning will eliminate much of the clutter and the mud hazards associated with the introduction of ceramics. Provides some helpful suggestions for teaching ceramics in an efficient and tidy fashion. (Author/RK)

Orbital radar evidence for lunar subsurface layering in Maria Serenitatis and Crisium

NASA Technical Reports Server (NTRS)

Peeples, W. J.; Sill, W. R.; May, T. W.; Ward, S. H.; Phillips, R. J.; Jordan, R. L.; Abbott, E. A.; Killpack, T. J.

1978-01-01

Data from the lunar-orbiting Apollo 17 radar sounding experiment (60-m wavelength) have been examined in both digital and holographic formats, and it is concluded that there are two subsurface radar reflectors below the surface in Mare Serenitatis and one reflector below the surface in Mare Crisium. The mean apparent depths of the reflectors below the surface of the former Mare are 0.9 and 1.6 km, while the reflector below the surface of the latter Mare has a mean depth of 1.4 km. These reflectors represent basin-wide subsurface interfaces. Techniques for reducing surface backscatter (clutter) in the data are described, and reasons for thinking that the distinct alignments in radar returns represent subsurface reflecting horizons are explained

Performance limits for exo-clutter Ground Moving Target Indicator (GMTI) radar.

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

Doerry, Armin Walter

2010-09-01

The performance of a Ground Moving Target Indicator (GMTI) radar system depends on a variety of factors, many which are interdependent in some manner. It is often difficult to 'get your arms around' the problem of ascertaining achievable performance limits, and yet those limits exist and are dictated by physics. This report identifies and explores those limits, and how they depend on hardware system parameters and environmental conditions. Ultimately, this leads to a characterization of parameters that offer optimum performance for the overall GMTI radar system. While the information herein is not new to the literature, its collection into amore » single report hopes to offer some value in reducing the 'seek time'.« less

Hoarding disorder

MedlinePlus

... of items, gradual buildup of clutter in living spaces and difficulty discarding things are usually the first ... for which there is no immediate need or space. By middle age, symptoms are often severe and ...

Multifrequency Measurements of Radar Ground Clutter at 42 Sites. Volume 3: Appendix E

DTIC Science & Technology

1991-11-15

pulse, horizontal polarization. E-33 76260-22 0 0 -10 + + X.0 Ox + IL 0 tD -20 0 U. 0 4w + RANGE POL. RES. (m) 150 H e -30 + 150 V 0so 0 15/36 H + 15/36...10 _ +. x U- 0 tD - 00. 2 Z + 4 0 x0 w 0 0+ 0 -30 VHF UHF L -X-BAND FREQUENCY (MHz) Figure E-53. Mean clutter strength versus frequency at Woking. For...76260-3 -10 RANGE POL. RES. (in) 150 H . 150 V 0 15/36 H + 15/36 V X -20 x ’U0 + U. 0 tD -30- 0 0+ IL.0 0 2 0 4w + x -40- VHF UHF L- S- X-BAND FREQUENCY

Real-time obstacle avoidance using harmonic potential functions

NASA Technical Reports Server (NTRS)

Kim, Jin-Oh; Khosla, Pradeep K.

1992-01-01

This paper presents a new formulation of the artificial potential approach to the obstacle avoidance problem for a mobile robot or a manipulator in a known environment. Previous formulations of artificial potentials for obstacle avoidance have exhibited local minima in a cluttered environment. To build an artificial potential field, harmonic functions that completely eliminate local minima even for a cluttered environment are used. The panel method is employed to represent arbitrarily shaped obstacles and to derive the potential over the whole space. Based on this potential function, an elegant control strategy is proposed for the real-time control of a robot. The harmonic potential, the panel method, and the control strategy are tested with a bar-shaped mobile robot and a three-degree-of-freedom planar redundant manipulator.

Ring-push metric learning for person reidentification

NASA Astrophysics Data System (ADS)

He, Botao; Yu, Shaohua

2017-05-01

Person reidentification (re-id) has been widely studied because of its extensive use in video surveillance and forensics applications. It aims to search a specific person among a nonoverlapping camera network, which is highly challenging due to large variations in the cluttered background, human pose, and camera viewpoint. We present a metric learning algorithm for learning a Mahalanobis distance for re-id. Generally speaking, there exist two forces in the conventional metric learning process, one pulling force that pulls points of the same class closer and the other pushing force that pushes points of different classes as far apart as possible. We argue that, when only a limited number of training data are given, forcing interclass distances to be as large as possible may drive the metric to overfit the uninformative part of the images, such as noises and backgrounds. To alleviate overfitting, we propose the ring-push metric learning algorithm. Different from other metric learning methods that only punish too small interclass distances, in the proposed method, both too small and too large inter-class distances are punished. By introducing the generalized logistic function as the loss, we formulate the ring-push metric learning as a convex optimization problem and utilize the projected gradient descent method to solve it. The experimental results on four public datasets demonstrate the effectiveness of the proposed algorithm.

Deconstructing Visual Scenes in Cortex: Gradients of Object and Spatial Layout Information

PubMed Central

Kravitz, Dwight J.; Baker, Chris I.

2013-01-01

Real-world visual scenes are complex cluttered, and heterogeneous stimuli engaging scene- and object-selective cortical regions including parahippocampal place area (PPA), retrosplenial complex (RSC), and lateral occipital complex (LOC). To understand the unique contribution of each region to distributed scene representations, we generated predictions based on a neuroanatomical framework adapted from monkey and tested them using minimal scenes in which we independently manipulated both spatial layout (open, closed, and gradient) and object content (furniture, e.g., bed, dresser). Commensurate with its strong connectivity with posterior parietal cortex, RSC evidenced strong spatial layout information but no object information, and its response was not even modulated by object presence. In contrast, LOC, which lies within the ventral visual pathway, contained strong object information but no background information. Finally, PPA, which is connected with both the dorsal and the ventral visual pathway, showed information about both objects and spatial backgrounds and was sensitive to the presence or absence of either. These results suggest that 1) LOC, PPA, and RSC have distinct representations, emphasizing different aspects of scenes, 2) the specific representations in each region are predictable from their patterns of connectivity, and 3) PPA combines both spatial layout and object information as predicted by connectivity. PMID:22473894

Human tracking in thermal images using adaptive particle filters with online random forest learning

NASA Astrophysics Data System (ADS)

Ko, Byoung Chul; Kwak, Joon-Young; Nam, Jae-Yeal

2013-11-01

This paper presents a fast and robust human tracking method to use in a moving long-wave infrared thermal camera under poor illumination with the existence of shadows and cluttered backgrounds. To improve the human tracking performance while minimizing the computation time, this study proposes an online learning of classifiers based on particle filters and combination of a local intensity distribution (LID) with oriented center-symmetric local binary patterns (OCS-LBP). Specifically, we design a real-time random forest (RF), which is the ensemble of decision trees for confidence estimation, and confidences of the RF are converted into a likelihood function of the target state. First, the target model is selected by the user and particles are sampled. Then, RFs are generated using the positive and negative examples with LID and OCS-LBP features by online learning. The learned RF classifiers are used to detect the most likely target position in the subsequent frame in the next stage. Then, the RFs are learned again by means of fast retraining with the tracked object and background appearance in the new frame. The proposed algorithm is successfully applied to various thermal videos as tests and its tracking performance is better than those of other methods.

Low-Rank Matrix Recovery Approach for Clutter Rejection in Real-Time IR-UWB Radar-Based Moving Target Detection

PubMed Central

Sabushimike, Donatien; Na, Seung You; Kim, Jin Young; Bui, Ngoc Nam; Seo, Kyung Sik; Kim, Gil Gyeom

2016-01-01

The detection of a moving target using an IR-UWB Radar involves the core task of separating the waves reflected by the static background and by the moving target. This paper investigates the capacity of the low-rank and sparse matrix decomposition approach to separate the background and the foreground in the trend of UWB Radar-based moving target detection. Robust PCA models are criticized for being batched-data-oriented, which makes them inconvenient in realistic environments where frames need to be processed as they are recorded in real time. In this paper, a novel method based on overlapping-windows processing is proposed to cope with online processing. The method consists of processing a small batch of frames which will be continually updated without changing its size as new frames are captured. We prove that RPCA (via its Inexact Augmented Lagrange Multiplier (IALM) model) can successfully separate the two subspaces, which enhances the accuracy of target detection. The overlapping-windows processing method converges on the optimal solution with its batch counterpart (i.e., processing batched data with RPCA), and both methods prove the robustness and efficiency of the RPCA over the classic PCA and the commonly used exponential averaging method. PMID:27598159

State estimation for autonomous flight in cluttered environments

NASA Astrophysics Data System (ADS)

Langelaan, Jacob Willem

Safe, autonomous operation in complex, cluttered environments is a critical challenge facing autonomous mobile systems. The research described in this dissertation was motivated by a particularly difficult example of autonomous mobility: flight of a small Unmanned Aerial Vehicle (UAV) through a forest. In cluttered environments (such as forests or natural and urban canyons) signals from navigation beacons such as GPS may frequently be occluded. Direct measurements of vehicle position are therefore unavailable, and information required for flight control, obstacle avoidance, and navigation must be obtained using only on-board sensors. However, payload limitations of small UAVs restrict both the mass and physical dimensions of sensors that can be carried. This dissertation describes the development and proof-of-concept demonstration of a navigation system that uses only a low-cost inertial measurement unit and a monocular camera. Micro electromechanical inertial measurements units are well suited to small UAV applications and provide measurements of acceleration and angular rate. However, they do not provide information about nearby obstacles (needed for collision avoidance) and their noise and bias characteristics lead to unbounded growth in computed position. A monocular camera can provide bearings to nearby obstacles and landmarks. These bearings can be used both to enable obstacle avoidance and to aid navigation. Presented here is a solution to the problem of estimating vehicle state (position, orientation and velocity) as well as positions of obstacles in the environment using only inertial measurements and bearings to obstacles. This is a highly nonlinear estimation problem, and standard estimation techniques such as the Extended Kalman Filter are prone to divergence in this application. In this dissertation a Sigma Point Kalman Filter is implemented, resulting in an estimator which is able to cope with the significant nonlinearities in the system equations and uncertainty in state estimates while remaining tractable for real-time operation. In addition, the issues of data association and landmark initialization are addressed. Estimator performance is examined through Monte Carlo simulations in both two and three dimensions for scenarios involving UAV flight in cluttered environments. Hardware tests and simulations demonstrate navigation through an obstacle-strewn environment by a small Unmanned Ground Vehicle.

Sensitivity Analysis of Sampling Number on Quality of Polarmetric Measurements from S-band Dual-Polarization Radar

NASA Astrophysics Data System (ADS)

KIM, H.; Suk, M. K.; Jung, S. A.; Park, J. S.; Ko, J. S.

2016-12-01

The data quality of dual-polarimetric weather radar is subject to radar scanning strategies such as pulse length, pulse repetition frequency (PRF), antenna scan speed, and sampling number. In terms of sampling number, the quality of radar moment data increases with the increasing of sampling number at the given PRF and pulse length while the feasible number of elevation angles decreases for the given time or the time required for radar volume scan increases with the relatively high sampling number. For operational weather radar, the sampling number is subjectively determined by the proficient radar operator. The determination of suitable sampling number is still challengeable for operational dual-polarimetric weather radar.In this study, we analyzed the sensitivity of polarimetric measurements to sampling number based on special radar experiment for rainfall and snowfall events using S-band dual-polarimetric radar (YIT) at Yong-In test bed. For this experiment, YIT radar transmitted a simultaneously polarized beam in horizontal and vertical with pulse length of 1.0 μs and single PRF of 600Hz. The beam width and gate size were 1.0° and 250m, respectively. The volume scan was composed of three PPI scans with three sampling numbers (antenna scan speed) of 40 (15°s-1), 60(10°s-1), and 85(7°s-1) at same elevation angle (=0.2°). We first investigated the spatial fluctuation of the polarimetric measurements according to three sampling numbers using radial texture. As the sampling number increases, the radial fluctuations of polarimetric measurements decrease. Second, we also examined the sensitivity to fuzzy logic based quality control algorithm for dual-polarimetric radar (Ye et al. 2015). The probability density functions (PDFs) of fuzzy logic feature parameters between ground clutter and meteorological echo area were compared. For overlapping area in both PDFs between ground clutter and meteorological echo increases with decreasing the sampling number. As the overlapping area increases, the classification of ground clutter (or meteorological echo) in fuzzy logic classifier is more difficult due to similar characteristics between ground clutter and meteorological echoes.

Efficient Spatiotemporal Clutter Rejection and Nonlinear Filtering-based Dim Resolved and Unresolved Object Tracking Algorithms

NASA Astrophysics Data System (ADS)

Tartakovsky, A.; Tong, M.; Brown, A. P.; Agh, C.

2013-09-01

We develop efficient spatiotemporal image processing algorithms for rejection of non-stationary clutter and tracking of multiple dim objects using non-linear track-before-detect methods. For clutter suppression, we include an innovative image alignment (registration) algorithm. The images are assumed to contain elements of the same scene, but taken at different angles, from different locations, and at different times, with substantial clutter non-stationarity. These challenges are typical for space-based and surface-based IR/EO moving sensors, e.g., highly elliptical orbit or low earth orbit scenarios. The algorithm assumes that the images are related via a planar homography, also known as the projective transformation. The parameters are estimated in an iterative manner, at each step adjusting the parameter vector so as to achieve improved alignment of the images. Operating in the parameter space rather than in the coordinate space is a new idea, which makes the algorithm more robust with respect to noise as well as to large inter-frame disturbances, while operating at real-time rates. For dim object tracking, we include new advancements to a particle non-linear filtering-based track-before-detect (TrbD) algorithm. The new TrbD algorithm includes both real-time full image search for resolved objects not yet in track and joint super-resolution and tracking of individual objects in closely spaced object (CSO) clusters. The real-time full image search provides near-optimal detection and tracking of multiple extremely dim, maneuvering objects/clusters. The super-resolution and tracking CSO TrbD algorithm provides efficient near-optimal estimation of the number of unresolved objects in a CSO cluster, as well as the locations, velocities, accelerations, and intensities of the individual objects. We demonstrate that the algorithm is able to accurately estimate the number of CSO objects and their locations when the initial uncertainty on the number of objects is large. We demonstrate performance of the TrbD algorithm both for satellite-based and surface-based EO/IR surveillance scenarios.

Graphical derivations of radar, sonar, and communication signals

NASA Technical Reports Server (NTRS)

Altes, R. A.; Titlebaum, E. L.

1975-01-01

The designer of a communication system often has knowledge concerning the changes in distance between transmitter and receiver as a function of time. This information can be exploited to reduce multipath interference via proper signal design. A radar or sonar may also have good a priori information about possible target trajectories. Such knowledge can again be used to reduce the receiver's response to clutter (MTI), to enhance signal-to-noise ratio, or to simplify receiver design. There are also situations in which prior knowledge about trajectories is lacking. The system should then utilize a single-filter pair which is insensitive to the effects induced by relative motion between transmitter, receiver, and reflectors. For waveforms with large time-bandwidth products, such as long pulse trains, it is possible to graphically derive signal formats for both situations (trajectory known and unknown). Although the exact form of the signal is sometimes not specified by the graphical procedure, the problem in such cases is reduced to one which has already been solved, i.e., the generation of an impulse equivalent code.

Software algorithms for false alarm reduction in LWIR hyperspectral chemical agent detection

NASA Astrophysics Data System (ADS)

Manolakis, D.; Model, J.; Rossacci, M.; Zhang, D.; Ontiveros, E.; Pieper, M.; Seeley, J.; Weitz, D.

2008-04-01

The long-wave infrared (LWIR) hyperpectral sensing modality is one that is often used for the problem of detection and identification of chemical warfare agents (CWA) which apply to both military and civilian situations. The inherent nature and complexity of background clutter dictates a need for sophisticated and robust statistical models which are then used in the design of optimum signal processing algorithms that then provide the best exploitation of hyperspectral data to ultimately make decisions on the absence or presence of potentially harmful CWAs. This paper describes the basic elements of an automated signal processing pipeline developed at MIT Lincoln Laboratory. In addition to describing this signal processing architecture in detail, we briefly describe the key signal models that form the foundation of these algorithms as well as some spatial processing techniques used for false alarm mitigation. Finally, we apply this processing pipeline to real data measured by the Telops FIRST hyperspectral (FIRST) sensor to demonstrate its practical utility for the user community.

Hyperspectral anomaly detection using Sony PlayStation 3

NASA Astrophysics Data System (ADS)

Rosario, Dalton; Romano, João; Sepulveda, Rene

2009-05-01

We present a proof-of-principle demonstration using Sony's IBM Cell processor-based PlayStation 3 (PS3) to run-in near real-time-a hyperspectral anomaly detection algorithm (HADA) on real hyperspectral (HS) long-wave infrared imagery. The PS3 console proved to be ideal for doing precisely the kind of heavy computational lifting HS based algorithms require, and the fact that it is a relatively open platform makes programming scientific applications feasible. The PS3 HADA is a unique parallel-random sampling based anomaly detection approach that does not require prior spectra of the clutter background. The PS3 HADA is designed to handle known underlying difficulties (e.g., target shape/scale uncertainties) often ignored in the development of autonomous anomaly detection algorithms. The effort is part of an ongoing cooperative contribution between the Army Research Laboratory and the Army's Armament, Research, Development and Engineering Center, which aims at demonstrating performance of innovative algorithmic approaches for applications requiring autonomous anomaly detection using passive sensors.

Scene text detection by leveraging multi-channel information and local context

NASA Astrophysics Data System (ADS)

Wang, Runmin; Qian, Shengyou; Yang, Jianfeng; Gao, Changxin

2018-03-01

As an important information carrier, texts play significant roles in many applications. However, text detection in unconstrained scenes is a challenging problem due to cluttered backgrounds, various appearances, uneven illumination, etc.. In this paper, an approach based on multi-channel information and local context is proposed to detect texts in natural scenes. According to character candidate detection plays a vital role in text detection system, Maximally Stable Extremal Regions(MSERs) and Graph-cut based method are integrated to obtain the character candidates by leveraging the multi-channel image information. A cascaded false positive elimination mechanism are constructed from the perspective of the character and the text line respectively. Since the local context information is very valuable for us, these information is utilized to retrieve the missing characters for boosting the text detection performance. Experimental results on two benchmark datasets, i.e., the ICDAR 2011 dataset and the ICDAR 2013 dataset, demonstrate that the proposed method have achieved the state-of-the-art performance.

Recognizing characters of ancient manuscripts

NASA Astrophysics Data System (ADS)

Diem, Markus; Sablatnig, Robert

2010-02-01

Considering printed Latin text, the main issues of Optical Character Recognition (OCR) systems are solved. However, for degraded handwritten document images, basic preprocessing steps such as binarization, gain poor results with state-of-the-art methods. In this paper ancient Slavonic manuscripts from the 11th century are investigated. In order to minimize the consequences of false character segmentation, a binarization-free approach based on local descriptors is proposed. Additionally local information allows the recognition of partially visible or washed out characters. The proposed algorithm consists of two steps: character classification and character localization. Initially Scale Invariant Feature Transform (SIFT) features are extracted which are subsequently classified using Support Vector Machines (SVM). Afterwards, the interest points are clustered according to their spatial information. Thereby, characters are localized and finally recognized based on a weighted voting scheme of pre-classified local descriptors. Preliminary results show that the proposed system can handle highly degraded manuscript images with background clutter (e.g. stains, tears) and faded out characters.

Using Deep Learning Algorithm to Enhance Image-review Software for Surveillance Cameras

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

Cui, Yonggang; Thomas, Maikael A.

We propose the development of proven deep learning algorithms to flag objects and events of interest in Next Generation Surveillance System (NGSS) surveillance to make IAEA image review more efficient. Video surveillance is one of the core monitoring technologies used by the IAEA Department of Safeguards when implementing safeguards at nuclear facilities worldwide. The current image review software GARS has limited automated functions, such as scene-change detection, black image detection and missing scene analysis, but struggles with highly cluttered backgrounds. A cutting-edge algorithm to be developed in this project will enable efficient and effective searches in images and video streamsmore » by identifying and tracking safeguards relevant objects and detect anomalies in their vicinity. In this project, we will develop the algorithm, test it with the IAEA surveillance cameras and data sets collected at simulated nuclear facilities at BNL and SNL, and implement it in a software program for potential integration into the IAEA’s IRAP (Integrated Review and Analysis Program).« less

Long-term scale adaptive tracking with kernel correlation filters

NASA Astrophysics Data System (ADS)

Wang, Yueren; Zhang, Hong; Zhang, Lei; Yang, Yifan; Sun, Mingui

2018-04-01

Object tracking in video sequences has broad applications in both military and civilian domains. However, as the length of input video sequence increases, a number of problems arise, such as severe object occlusion, object appearance variation, and object out-of-view (some portion or the entire object leaves the image space). To deal with these problems and identify the object being tracked from cluttered background, we present a robust appearance model using Speeded Up Robust Features (SURF) and advanced integrated features consisting of the Felzenszwalb's Histogram of Oriented Gradients (FHOG) and color attributes. Since re-detection is essential in long-term tracking, we develop an effective object re-detection strategy based on moving area detection. We employ the popular kernel correlation filters in our algorithm design, which facilitates high-speed object tracking. Our evaluation using the CVPR2013 Object Tracking Benchmark (OTB2013) dataset illustrates that the proposed algorithm outperforms reference state-of-the-art trackers in various challenging scenarios.

Auditory Attentional Control and Selection during Cocktail Party Listening

PubMed Central

Hill, Kevin T.

2010-01-01

In realistic auditory environments, people rely on both attentional control and attentional selection to extract intelligible signals from a cluttered background. We used functional magnetic resonance imaging to examine auditory attention to natural speech under such high processing-load conditions. Participants attended to a single talker in a group of 3, identified by the target talker's pitch or spatial location. A catch-trial design allowed us to distinguish activity due to top-down control of attention versus attentional selection of bottom-up information in both the spatial and spectral (pitch) feature domains. For attentional control, we found a left-dominant fronto-parietal network with a bias toward spatial processing in dorsal precentral sulcus and superior parietal lobule, and a bias toward pitch in inferior frontal gyrus. During selection of the talker, attention modulated activity in left intraparietal sulcus when using talker location and in bilateral but right-dominant superior temporal sulcus when using talker pitch. We argue that these networks represent the sources and targets of selective attention in rich auditory environments. PMID:19574393

Attribution of soil information associated with modeling background clutter

NASA Astrophysics Data System (ADS)

Mason, George; Melloh, Rae

2006-05-01

This paper examines the attribution of data fields required to generate high resolution soil profiles for support of Computational Test Bed (CTB) used for countermine research. The countermine computational test bed is designed to realistically simulate the geo-environment to support the evaluation of sensors used to locate unexploded ordnance. The goal of the CTB is to derive expected moisture, chemical compounds, and measure heat migration over time, from which we expect to optimize sensor performance. Several tests areas were considered for the collection of soils data to populate the CTB. Collection of bulk soil properties has inherent spatial resolution limits. Novel techniques are therefore required to populate a high resolution model. This paper presents correlations between spatial variability in texture as related to hydraulic permeability and heat transfer properties of the soil. The extracted physical properties are used to exercise models providing a signature of subsurface media and support the simulation of detection by various sensors of buried and surface ordnance.

Part-based deep representation for product tagging and search

NASA Astrophysics Data System (ADS)

Chen, Keqing

2017-06-01

Despite previous studies, tagging and indexing the product images remain challenging due to the large inner-class variation of the products. In the traditional methods, the quantized hand-crafted features such as SIFTs are extracted as the representation of the product images, which are not discriminative enough to handle the inner-class variation. For discriminative image representation, this paper firstly presents a novel deep convolutional neural networks (DCNNs) architect true pre-trained on a large-scale general image dataset. Compared to the traditional features, our DCNNs representation is of more discriminative power with fewer dimensions. Moreover, we incorporate the part-based model into the framework to overcome the negative effect of bad alignment and cluttered background and hence the descriptive ability of the deep representation is further enhanced. Finally, we collect and contribute a well-labeled shoe image database, i.e., the TBShoes, on which we apply the part-based deep representation for product image tagging and search, respectively. The experimental results highlight the advantages of the proposed part-based deep representation.

Cross-Domain Shoe Retrieval with a Semantic Hierarchy of Attribute Classification Network.

PubMed

Zhan, Huijing; Shi, Boxin; Kot, Alex C

2017-08-04

Cross-domain shoe image retrieval is a challenging problem, because the query photo from the street domain (daily life scenario) and the reference photo in the online domain (online shop images) have significant visual differences due to the viewpoint and scale variation, self-occlusion, and cluttered background. This paper proposes the Semantic Hierarchy Of attributE Convolutional Neural Network (SHOE-CNN) with a three-level feature representation for discriminative shoe feature expression and efficient retrieval. The SHOE-CNN with its newly designed loss function systematically merges semantic attributes of closer visual appearances to prevent shoe images with the obvious visual differences being confused with each other; the features extracted from image, region, and part levels effectively match the shoe images across different domains. We collect a large-scale shoe dataset composed of 14341 street domain and 12652 corresponding online domain images with fine-grained attributes to train our network and evaluate our system. The top-20 retrieval accuracy improves significantly over the solution with the pre-trained CNN features.

Human-Computer Interaction Based on Hand Gestures Using RGB-D Sensors

PubMed Central

Palacios, José Manuel; Sagüés, Carlos; Montijano, Eduardo; Llorente, Sergio

2013-01-01

In this paper we present a new method for hand gesture recognition based on an RGB-D sensor. The proposed approach takes advantage of depth information to cope with the most common problems of traditional video-based hand segmentation methods: cluttered backgrounds and occlusions. The algorithm also uses colour and semantic information to accurately identify any number of hands present in the image. Ten different static hand gestures are recognised, including all different combinations of spread fingers. Additionally, movements of an open hand are followed and 6 dynamic gestures are identified. The main advantage of our approach is the freedom of the user's hands to be at any position of the image without the need of wearing any specific clothing or additional devices. Besides, the whole method can be executed without any initial training or calibration. Experiments carried out with different users and in different environments prove the accuracy and robustness of the method which, additionally, can be run in real-time. PMID:24018953

Learning to predict where human gaze is using quaternion DCT based regional saliency detection

NASA Astrophysics Data System (ADS)

Li, Ting; Xu, Yi; Zhang, Chongyang

2014-09-01

Many current visual attention approaches used semantic features to accurately capture human gaze. However, these approaches demand high computational cost and can hardly be applied to daily use. Recently, some quaternion-based saliency detection models, such as PQFT (phase spectrum of Quaternion Fourier Transform), QDCT (Quaternion Discrete Cosine Transform), have been proposed to meet real-time requirement of human gaze tracking tasks. However, current saliency detection methods used global PQFT and QDCT to locate jump edges of the input, which can hardly detect the object boundaries accurately. To address the problem, we improved QDCT-based saliency detection model by introducing superpixel-wised regional saliency detection mechanism. The local smoothness of saliency value distribution is emphasized to distinguish noises of background from salient regions. Our algorithm called saliency confidence can distinguish the patches belonging to the salient object and those of the background. It decides whether the image patches belong to the same region. When an image patch belongs to a region consisting of other salient patches, this patch should be salient as well. Therefore, we use saliency confidence map to get background weight and foreground weight to do the optimization on saliency map obtained by QDCT. The optimization is accomplished by least square method. The optimization approach we proposed unifies local and global saliency by combination of QDCT and measuring the similarity between each image superpixel. We evaluate our model on four commonly-used datasets (Toronto, MIT, OSIE and ASD) using standard precision-recall curves (PR curves), the mean absolute error (MAE) and area under curve (AUC) measures. In comparison with most state-of-art models, our approach can achieve higher consistency with human perception without training. It can get accurate human gaze even in cluttered background. Furthermore, it achieves better compromise between speed and accuracy.

Robonaut Mobile Autonomy: Initial Experiments

NASA Technical Reports Server (NTRS)

Diftler, M. A.; Ambrose, R. O.; Goza, S. M.; Tyree, K. S.; Huber, E. L.

2006-01-01

A mobile version of the NASA/DARPA Robonaut humanoid recently completed initial autonomy trials working directly with humans in cluttered environments. This compact robot combines the upper body of the Robonaut system with a Segway Robotic Mobility Platform yielding a dexterous, maneuverable humanoid ideal for interacting with human co-workers in a range of environments. This system uses stereovision to locate human teammates and tools and a navigation system that uses laser range and vision data to follow humans while avoiding obstacles. Tactile sensors provide information to grasping algorithms for efficient tool exchanges. The autonomous architecture utilizes these pre-programmed skills to form complex behaviors. The initial behavior demonstrates a robust capability to assist a human by acquiring a tool from a remotely located individual and then following the human in a cluttered environment with the tool for future use.

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.

Polarization differences in airborne ground penetrating radar performance for landmine detection

NASA Astrophysics Data System (ADS)

Dogaru, Traian; Le, Calvin

2016-05-01

The U.S. Army Research Laboratory (ARL) has investigated the ultra-wideband (UWB) radar technology for detection of landmines, improvised explosive devices and unexploded ordnance, for over two decades. This paper presents a phenomenological study of the radar signature of buried landmines in realistic environments and the performance of airborne synthetic aperture radar (SAR) in detecting these targets as a function of multiple parameters: polarization, depression angle, soil type and burial depth. The investigation is based on advanced computer models developed at ARL. The analysis includes both the signature of the targets of interest and the clutter produced by rough surface ground. Based on our numerical simulations, we conclude that low depression angles and H-H polarization offer the highest target-to-clutter ratio in the SAR images and therefore the best radar performance of all the scenarios investigated.

Adaptive polarization image fusion based on regional energy dynamic weighted average

NASA Astrophysics Data System (ADS)

Zhao, Yong-Qiang; Pan, Quan; Zhang, Hong-Cai

2005-11-01

According to the principle of polarization imaging and the relation between Stokes parameters and the degree of linear polarization, there are much redundant and complementary information in polarized images. Since man-made objects and natural objects can be easily distinguished in images of degree of linear polarization and images of Stokes parameters contain rich detailed information of the scene, the clutters in the images can be removed efficiently while the detailed information can be maintained by combining these images. An algorithm of adaptive polarization image fusion based on regional energy dynamic weighted average is proposed in this paper to combine these images. Through an experiment and simulations, most clutters are removed by this algorithm. The fusion method is used for different light conditions in simulation, and the influence of lighting conditions on the fusion results is analyzed.

Night vision: requirements and possible roadmap for FIR and NIR systems

NASA Astrophysics Data System (ADS)

Källhammer, Jan-Erik

2006-04-01

A night vision system must increase visibility in situations where only low beam headlights can be used today. As pedestrians and animals have the highest risk increase in night time traffic due to darkness, the ability of detecting those objects should be the main performance criteria, and the system must remain effective when facing the headlights of oncoming vehicles. Far infrared system has been shown to be superior to near infrared system in terms of pedestrian detection distance. Near infrared images were rated to have significantly higher visual clutter compared with far infrared images. Visual clutter has been shown to correlate with reduction in detection distance of pedestrians. Far infrared images are perceived as being more unusual and therefore more difficult to interpret, although the image appearance is likely related to the lower visual clutter. However, the main issue comparing the two technologies should be how well they solve the driver's problem with insufficient visibility under low beam conditions, especially of pedestrians and other vulnerable road users. With the addition of an automatic detection aid, a main issue will be whether the advantage of FIR systems will vanish given NIR systems with well performing automatic pedestrian detection functionality. The first night vision introductions did not generate the sales volumes initially expected. A renewed interest in night vision systems are however to be expected after the release of night vision systems by BMW, Mercedes and Honda, the latter with automatic pedestrian detection.

Executive Functioning in Participants Over Age of 50 with Hoarding Disorder.

PubMed

Ayers, Catherine R; Dozier, Mary E; Wetherell, Julie Loebach; Twamley, Elizabeth W; Schiehser, Dawn M

2016-05-01

The current investigation utilized mid-life and late-life participants diagnosed with hoarding disorder (HD) to explore the relationship between executive functioning and hoarding severity. Correlational analyses were used to investigate the associations between executive functioning and hoarding severity in nondemented participants. Multiple regression was used to determine if executive functioning had a unique association with HD severity when accounting for depressive symptoms. Participants were recruited from the San Diego area for HD intervention studies. Participants were 113 nondemented adults aged 50-86 years who met DSM-5 criteria for HD. The mean age of the sample utilized in the analyses was 63.76 years (SD, 7.2; range, 51-85 years). The sample was mostly female (72%), Caucasian (81.4%), and unmarried (78%). Hoarding severity was assessed using the Saving Inventory-Revised and the Clutter Image Rating and depression was assessed using the Hospital Anxiety and Depression Scale. Executive functioning was assessed using the Wisconsin Card Sorting Test (WCST-128) and the Trail Making and Verbal Fluency subtests of the Delis-Kaplan Executive Function System. Executive function (operationalized as perseveration on the WCST-128) was significantly associated with Clutter Image Ratings. In a multivariate context, executive function and depressive symptom severity were both significant predictors of variance in Clutter Image Rating. Our results suggest that executive function is related to severity of HD symptoms and should be considered as part of the conceptualization of HD. Published by Elsevier Inc.

Synthetic Aperture Radar Imagery of Airports and Surrounding Areas: Denver Stapleton International Airport

NASA Technical Reports Server (NTRS)

Onstott, Robert G.; Gineris, Denise J.

1990-01-01

This is the third in a series of three reports which address the statistical description of ground clutter at an airport and in the surrounding area. These data are being utilized in a program to detect microbursts. Synthetic aperture radar (SAR) data were collected at the Denver Stapleton Airport using a set of parameters which closely match those which are anticipated to be utilized by an aircraft on approach to an airport. These data and the results of the clutter study are described. Scenes of 13 x 10 km were imaged at 9.38 GHz and HH-, VV-, and HV-polarizations, and contain airport grounds and facilities (up to 14 percent), cultural areas (more than 50 percent), and rural areas (up to 6 percent). Incidence angles range from 40 to 84 deg. At the largest depression angles the distributed targets, such as forest, fields, water, and residential, rarely had mean scattering coefficients greater than -10 dB. From 30 to 80 percent of an image had scattering coefficients less than -20 dB. About 1 to 10 percent of the scattering coefficients exceeded 0 dB, and from 0 to 1 percent above 10 dB. In examining the average backscatter coefficients at large angles, the clutter types cluster according to the following groups: (1) terminals (-3 dB), (2) city and industrial (-7 dB), (3) warehouse (-10 dB), (4) urban and residential (-14 dB), and (5) grass (-24 dB).

Curing the noise epidemic

NASA Astrophysics Data System (ADS)

Mazer, Susan

2005-09-01

The argument is made that design does not stop when the fixed architectural and acoustical components are in place. Spaces live and breathe with the people who reside in them. Research and examples are presented that show that noise, auditory clutter, thrives on itself in hospitals. Application of the Lombard reflex studies fit into the hospital setting, but do not offer solutions as to how one might reduce the impact. In addition, the basis for looking at the noise component as a physical as well cultural dynamic will be addressed. Whether the result of the wrong conversation in the wrong place or the right conversation in an unfortunate place, talk mixed with sounds of technology is shown to cause its own symptoms. From heightened anxiety and stress to medical errors, staff burnout, or HIPAA violations, the case is made that noise is pandemic in hospitals and demands financial and operational investment. An explanation of how to reduce noise by design of the dynamic environment - equipment, technology, staff protocols is also provided.

Visualizing Spatially Varying Distribution Data

NASA Technical Reports Server (NTRS)

Kao, David; Luo, Alison; Dungan, Jennifer L.; Pang, Alex; Biegel, Bryan A. (Technical Monitor)

2002-01-01

Box plot is a compact representation that encodes the minimum, maximum, mean, median, and quarters information of a distribution. In practice, a single box plot is drawn for each variable of interest. With the advent of more accessible computing power, we are now facing the problem of visual icing data where there is a distribution at each 2D spatial location. Simply extending the box plot technique to distributions over 2D domain is not straightforward. One challenge is reducing the visual clutter if a box plot is drawn over each grid location in the 2D domain. This paper presents and discusses two general approaches, using parametric statistics and shape descriptors, to present 2D distribution data sets. Both approaches provide additional insights compared to the traditional box plot technique

Characterization of binary string statistics for syntactic landmine detection

NASA Astrophysics Data System (ADS)

Nasif, Ahmed O.; Mark, Brian L.; Hintz, Kenneth J.

2011-06-01

Syntactic landmine detection has been proposed to detect and classify non-metallic landmines using ground penetrating radar (GPR). In this approach, the GPR return is processed to extract characteristic binary strings for landmine and clutter discrimination. In our previous work, we discussed the preprocessing methodology by which the amplitude information of the GPR A-scan signal can be effectively converted into binary strings, which identify the impedance discontinuities in the signal. In this work, we study the statistical properties of the binary string space. In particular, we develop a Markov chain model to characterize the observed bit sequence of the binary strings. The state is defined as the number of consecutive zeros between two ones in the binarized A-scans. Since the strings are highly sparse (the number of zeros is much greater than the number of ones), defining the state this way leads to fewer number of states compared to the case where each bit is defined as a state. The number of total states is further reduced by quantizing the number of consecutive zeros. In order to identify the correct order of the Markov model, the mean square difference (MSD) between the transition matrices of mine strings and non-mine strings is calculated up to order four using training data. The results show that order one or two maximizes this MSD. The specification of the transition probabilities of the chain can be used to compute the likelihood of any given string. Such a model can be used to identify characteristic landmine strings during the training phase. These developments on modeling and characterizing the string statistics can potentially be part of a real-time landmine detection algorithm that identifies landmine and clutter in an adaptive fashion.

Two types of squalor: findings from a factor analysis of the Environmental Cleanliness and Clutter Scale (ECCS).

PubMed

Snowdon, John; Halliday, Graeme; Hunt, Glenn E

2013-07-01

Most people who collect and hoard, and then have difficulty discarding items, do not live in squalor, even though accumulation of hoarded items can make cleaning very difficult. Commonly, people living in squalor accumulate garbage, but relatively few fulfill proposed criteria for "hoarding disorder." We examined the overlap between hoarding and squalor among people referred because of unacceptable living conditions. Ongoing collection of data by a Squalor Project team, including ratings on the Environmental Cleanliness and Clutter Scale (ECCS), allowed (1) description of characteristics of cases and (2) examination of ratings of uncleanliness, and of the effect of accumulation of items or material on access within dwellings. Principal component analysis was used to examine latent variables underlying the ECCS. The mean age of the referred occupants (108 male, 95 female) was 61.9 years. The mean ECCS score in 186 rated cases was 18.5. Factor analysis of ECCS data showed a two-factor solution as the most plausible. Factor 1, comprising seven squalor items, accounted for 33.7% of the variance. Factor 2 comprised reduced accessibility and accumulation of items of little value (variance 17.6%). Accumulation of garbage loaded equally on the two factors. High levels of squalor and/or accumulation were recorded in 105 (56%) of the 186 dwellings. One-third scored high on accumulation/hoarding, while 38% scored high on squalor; 15% scored high on both squalor and accumulation. A quarter of those scoring high on squalor scored low on hoarding/accumulation. The ECCS is useful when describing whether referred cases show high levels of squalor, hoarding, or both.

Breast cancer detection using interferometric MUSIC: experimental and numerical assessment.

PubMed

Ruvio, Giuseppe; Solimene, Raffaele; Cuccaro, Antonio; Gaetano, Domenico; Browne, Jacinta E; Ammann, Max J

2014-10-01

In microwave breast cancer detection, it is often beneficial to arrange sensors in close proximity to the breast. The resultant coupling generally changes the antenna response. As an a priori characterization of the radio frequency system becomes difficult, this can lead to severe degradation of the detection efficacy. The purpose of this paper is to demonstrate the advantages of adopting an interferometric multiple signal classification (I-MUSIC) approach due to its limited dependence from a priori information on the antenna. The performance of I-MUSIC detection was measured in terms of signal-to-clutter ratio (SCR), signal-to-mean ratio (SMR), and spatial displacement (SD) and compared to other common linear noncoherent imaging methods, such as migration and the standard wideband MUSIC (WB-MUSIC) which also works when the antenna is not accounted for. The data were acquired by scanning a synthetic oil-in-gelatin phantom that mimics the dielectric properties of breast tissues across the spectrum 1-3 GHz using a proprietary breast microwave multi-monostatic radar system. The phantom is a multilayer structure that includes skin, adipose, fibroconnective, fibroglandular, and tumor tissue with an adipose component accounting for 60% of the whole structure. The detected tumor has a diameter of 5 mm and is inserted inside a fibroglandular region with a permittivity contrast εr-tumor/εr-fibroglandular < 1.5 over the operating band. Three datasets were recorded corresponding to three antennas with different coupling mechanisms. This was done to assess the independence of the I-MUSIC method from antenna characterizations. The datasets were processed by using I-MUSIC, noncoherent migration, and wideband MUSIC under equivalent conditions (i.e., operative bandwidth, frequency samples, and scanning positions). SCR, SMR, and SD figures were measured from all reconstructed images. In order to benchmark experimental results, numerical simulations of equivalent scenarios were carried out by using CST Microwave Studio. The three numerical datasets were then processed following the same procedure that was designed for the experimental case. Detection results are presented for both experimental and numerical phantoms, and higher performance of the I-MUSIC method in comparison with the WB-MUSIC and noncoherent migration is achieved. This finding is confirmed for the three different antennas in this study. Although a delocalization effect occurs, experimental datasets show that the signal-to-clutter ratio and the signal-to-mean performance with the I-MUSIC are at least 5 and 2.3 times better than the other methods, respectively. The numerical datasets calculated on an equivalent phantom for cross-testing confirm the improved performance of the I-MUSIC in terms of SCR and SMR. In numerical simulations, the delocalization effect is dramatically reduced up to an SD value of 1.61 achieved with the I-MUSIC in combination with the antipodal Vivaldi antenna. This shows that mechanical uncertainties are the main reason for the delocalization effect in the measurements. Experimental results show that the I-MUSIC generates images with signal-to-clutter levels higher than 5.46 dB across all working conditions and it reaches 7.84 dB in combination with the antipodal Vivaldi antenna. Numerical simulations confirm this trend and due to ideal mechanical conditions return a signal-to-clutter level higher than 7.61 dB. The I-MUSIC largely outperforms the methods under comparison and is able to detect a 5-mm tumor with a permittivity contrast of 1.5.

Clutter Identification Using Electromagnetic Survey Data

DTIC Science & Technology

2013-07-01

for failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE JUL 2013 2 . REPORT... 2 2.0 Technology... 2 2.1 Technology Description .................................................................................................. 2 2.2

View-Dependent Streamline Deformation and Exploration

PubMed Central

Tong, Xin; Edwards, John; Chen, Chun-Ming; Shen, Han-Wei; Johnson, Chris R.; Wong, Pak Chung

2016-01-01

Occlusion presents a major challenge in visualizing 3D flow and tensor fields using streamlines. Displaying too many streamlines creates a dense visualization filled with occluded structures, but displaying too few streams risks losing important features. We propose a new streamline exploration approach by visually manipulating the cluttered streamlines by pulling visible layers apart and revealing the hidden structures underneath. This paper presents a customized view-dependent deformation algorithm and an interactive visualization tool to minimize visual clutter in 3D vector and tensor fields. The algorithm is able to maintain the overall integrity of the fields and expose previously hidden structures. Our system supports both mouse and direct-touch interactions to manipulate the viewing perspectives and visualize the streamlines in depth. By using a lens metaphor of different shapes to select the transition zone of the targeted area interactively, the users can move their focus and examine the vector or tensor field freely. PMID:26600061

Model-based adaptive 3D sonar reconstruction in reverberating environments.

PubMed

Saucan, Augustin-Alexandru; Sintes, Christophe; Chonavel, Thierry; Caillec, Jean-Marc Le

2015-10-01

In this paper, we propose a novel model-based approach for 3D underwater scene reconstruction, i.e., bathymetry, for side scan sonar arrays in complex and highly reverberating environments like shallow water areas. The presence of multipath echoes and volume reverberation generates false depth estimates. To improve the resulting bathymetry, this paper proposes and develops an adaptive filter, based on several original geometrical models. This multimodel approach makes it possible to track and separate the direction of arrival trajectories of multiple echoes impinging the array. Echo tracking is perceived as a model-based processing stage, incorporating prior information on the temporal evolution of echoes in order to reject cluttered observations generated by interfering echoes. The results of the proposed filter on simulated and real sonar data showcase the clutter-free and regularized bathymetric reconstruction. Model validation is carried out with goodness of fit tests, and demonstrates the importance of model-based processing for bathymetry reconstruction.

Study to investigate and evaluate means of optimizing the Ku-band combined radar/communication functions for the space shuttle

NASA Technical Reports Server (NTRS)

Weber, C. L.; Udalov, S.; Alem, W.

1977-01-01

The performance of the space shuttle orbiter's Ku-Band integrated radar and communications equipment is analyzed for the radar mode of operation. The block diagram of the rendezvous radar subsystem is described. Power budgets for passive target detection are calculated, based on the estimated values of system losses. Requirements for processing of radar signals in the search and track modes are examined. Time multiplexed, single-channel, angle tracking of passive scintillating targets is analyzed. Radar performance in the presence of main lobe ground clutter is considered and candidate techniques for clutter suppression are discussed. Principal system parameter drivers are examined for the case of stationkeeping at ranges comparable to target dimension. Candidate ranging waveforms for short range operation are analyzed and compared. The logarithmic error discriminant utilized for range, range rate and angle tracking is formulated and applied to the quantitative analysis of radar subsystem tracking loops.

Flight investigation of cockpit-displayed traffic information utilizing coded symbology in an advanced operational environment

NASA Technical Reports Server (NTRS)

Abbott, T. S.; Moen, G. C.; Person, L. H., Jr.; Keyser, G. L., Jr.; Yenni, K. R.; Garren, J. F., Jr.

1980-01-01

Traffic symbology was encoded to provide additional information concerning the traffic, which was displayed on the pilot's electronic horizontal situation indicators (EHSI). A research airplane representing an advanced operational environment was used to assess the benefit of coded traffic symbology in a realistic work-load environment. Traffic scenarios, involving both conflict-free and conflict situations, were employed. Subjective pilot commentary was obtained through the use of a questionnaire and extensive pilot debriefings. These results grouped conveniently under two categories: display factors and task performance. A major item under the display factor category was the problem of display clutter. The primary contributors to clutter were the use of large map-scale factors, the use of traffic data blocks, and the presentation of more than a few airplanes. In terms of task performance, the cockpit-displayed traffic information was found to provide excellent overall situation awareness. Additionally, mile separation prescribed during these tests.

View-Dependent Streamline Deformation and Exploration

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

Tong, Xin; Edwards, John; Chen, Chun-Ming

Occlusion presents a major challenge in visualizing 3D flow and tensor fields using streamlines. Displaying too many streamlines creates a dense visualization filled with occluded structures, but displaying too few streams risks losing important features. We propose a new streamline exploration approach by visually manipulating the cluttered streamlines by pulling visible layers apart and revealing the hidden structures underneath. This paper presents a customized view-dependent deformation algorithm and an interactive visualization tool to minimize visual cluttering for visualizing 3D vector and tensor fields. The algorithm is able to maintain the overall integrity of the fields and expose previously hidden structures.more » Our system supports both mouse and direct-touch interactions to manipulate the viewing perspectives and visualize the streamlines in depth. By using a lens metaphor of different shapes to select the transition zone of the targeted area interactively, the users can move their focus and examine the vector or tensor field freely.« less

Geostationary microwave imagers detection criteria

NASA Technical Reports Server (NTRS)

Stacey, J. M.

1986-01-01

Geostationary orbit is investigated as a vantage point from which to sense remotely the surface features of the planet and its atmosphere, with microwave sensors. The geometrical relationships associated with geostationary altitude are developed to produce an efficient search pattern for the detection of emitting media and metal objects. Power transfer equations are derived from the roots of first principles and explain the expected values of the signal-to-clutter ratios for the detection of aircraft, ships, and buoys and for the detection of natural features where they are manifested as cold and warm eddies. The transport of microwave power is described for modeled detection where the direction of power flow is explained by the Zeroth and Second Laws of Thermodynamics. Mathematical expressions are derived that elucidate the detectability of natural emitting media and metal objects. Signal-to-clutter ratio comparisons are drawn among detectable objects that show relative detectability with a thermodynamic sensor and with a short-pulse radar.

Door recognition in cluttered building interiors using imagery and lidar data

NASA Astrophysics Data System (ADS)

Díaz-Vilariño, L.; Martínez-Sánchez, J.; Lagüela, S.; Armesto, J.; Khoshelham, K.

2014-06-01

Building indoors reconstruction is an active research topic due to the importance of the wide range of applications to which they can be subjected, from architecture and furniture design, to movies and video games editing, or even crime scene investigation. Among the constructive elements defining the inside of a building, doors are important entities in applications like routing and navigation, and their automated recognition is advantageous e.g. in case of large multi-storey buildings with many office rooms. The inherent complexity of the automation of the recognition process is increased by the presence of clutter and occlusions, difficult to avoid in indoor scenes. In this work, we present a pipeline of techniques used for the reconstruction and interpretation of building interiors using information acquired in the form of point clouds and images. The methodology goes in depth with door detection and labelling as either opened, closed or furniture (false positive)

View-Dependent Streamline Deformation and Exploration.

PubMed

Tong, Xin; Edwards, John; Chen, Chun-Ming; Shen, Han-Wei; Johnson, Chris R; Wong, Pak Chung

2016-07-01

Occlusion presents a major challenge in visualizing 3D flow and tensor fields using streamlines. Displaying too many streamlines creates a dense visualization filled with occluded structures, but displaying too few streams risks losing important features. We propose a new streamline exploration approach by visually manipulating the cluttered streamlines by pulling visible layers apart and revealing the hidden structures underneath. This paper presents a customized view-dependent deformation algorithm and an interactive visualization tool to minimize visual clutter in 3D vector and tensor fields. The algorithm is able to maintain the overall integrity of the fields and expose previously hidden structures. Our system supports both mouse and direct-touch interactions to manipulate the viewing perspectives and visualize the streamlines in depth. By using a lens metaphor of different shapes to select the transition zone of the targeted area interactively, the users can move their focus and examine the vector or tensor field freely.

Inversion for Refractivity Parameters Using a Dynamic Adaptive Cuckoo Search with Crossover Operator Algorithm

PubMed Central

Zhang, Zhihua; Sheng, Zheng; Shi, Hanqing; Fan, Zhiqiang

2016-01-01

Using the RFC technique to estimate refractivity parameters is a complex nonlinear optimization problem. In this paper, an improved cuckoo search (CS) algorithm is proposed to deal with this problem. To enhance the performance of the CS algorithm, a parameter dynamic adaptive operation and crossover operation were integrated into the standard CS (DACS-CO). Rechenberg's 1/5 criteria combined with learning factor were used to control the parameter dynamic adaptive adjusting process. The crossover operation of genetic algorithm was utilized to guarantee the population diversity. The new hybrid algorithm has better local search ability and contributes to superior performance. To verify the ability of the DACS-CO algorithm to estimate atmospheric refractivity parameters, the simulation data and real radar clutter data are both implemented. The numerical experiments demonstrate that the DACS-CO algorithm can provide an effective method for near-real-time estimation of the atmospheric refractivity profile from radar clutter. PMID:27212938

Tumor response estimation in radar-based microwave breast cancer detection.

PubMed

Kurrant, Douglas J; Fear, Elise C; Westwick, David T

2008-12-01

Radar-based microwave imaging techniques have been proposed for early stage breast cancer detection. A considerable challenge for the successful implementation of these techniques is the reduction of clutter, or components of the signal originating from objects other than the tumor. In particular, the reduction of clutter from the late-time scattered fields is required in order to detect small (subcentimeter diameter) tumors. In this paper, a method to estimate the tumor response contained in the late-time scattered fields is presented. The method uses a parametric function to model the tumor response. A maximum a posteriori estimation approach is used to evaluate the optimal values for the estimates of the parameters. A pattern classification technique is then used to validate the estimation. The ability of the algorithm to estimate a tumor response is demonstrated by using both experimental and simulated data obtained with a tissue sensing adaptive radar system.

Doppler Radar Vital Signs Detection Method Based on Higher Order Cyclostationary.

PubMed

Yu, Zhibin; Zhao, Duo; Zhang, Zhiqiang

2017-12-26

Due to the non-contact nature, using Doppler radar sensors to detect vital signs such as heart and respiration rates of a human subject is getting more and more attention. However, the related detection-method research meets lots of challenges due to electromagnetic interferences, clutter and random motion interferences. In this paper, a novel third-order cyclic cummulant (TOCC) detection method, which is insensitive to Gaussian interference and non-cyclic signals, is proposed to investigate the heart and respiration rate based on continuous wave Doppler radars. The k -th order cyclostationary properties of the radar signal with hidden periodicities and random motions are analyzed. The third-order cyclostationary detection theory of the heart and respiration rate is studied. Experimental results show that the third-order cyclostationary approach has better estimation accuracy for detecting the vital signs from the received radar signal under low SNR, strong clutter noise and random motion interferences.

Efficiency improvement by navigated safety inspection involving visual clutter based on the random search model.

PubMed

Sun, Xinlu; Chong, Heap-Yih; Liao, Pin-Chao

2018-06-25

Navigated inspection seeks to improve hazard identification (HI) accuracy. With tight inspection schedule, HI also requires efficiency. However, lacking quantification of HI efficiency, navigated inspection strategies cannot be comprehensively assessed. This work aims to determine inspection efficiency in navigated safety inspection, controlling for the HI accuracy. Based on a cognitive method of the random search model (RSM), an experiment was conducted to observe the HI efficiency in navigation, for a variety of visual clutter (VC) scenarios, while using eye-tracking devices to record the search process and analyze the search performance. The results show that the RSM is an appropriate instrument, and VC serves as a hazard classifier for navigation inspection in improving inspection efficiency. This suggests a new and effective solution for addressing the low accuracy and efficiency of manual inspection through navigated inspection involving VC and the RSM. It also provides insights into the inspectors' safety inspection ability.

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.

Color Vision in Color Display Night Vision Goggles.

PubMed

Liggins, Eric P; Serle, William P

2017-05-01

Aircrew viewing eyepiece-injected symbology on color display night vision goggles (CDNVGs) are performing a visual task involving color under highly unnatural viewing conditions. Their performance in discriminating different colors and responding to color cues is unknown. Experimental laboratory measurements of 1) color discrimination and 2) visual search performance are reported under adaptation conditions representative of a CDNVG. Color discrimination was measured using a two-alternative forced choice (2AFC) paradigm that probes color space uniformly around a white point. Search times in the presence of different degrees of clutter (distractors in the scene) are measured for different potential symbology colors. The discrimination data support previous data suggesting that discrimination is best for colors close to the adapting point in color space (P43 phosphor in this case). There were highly significant effects of background adaptation (white or green) and test color. The search time data show that saturated colors with the greatest chromatic contrast with respect to the background lead to the shortest search times, associated with the greatest saliency. Search times for the green background were around 150 ms longer than for the white. Desaturated colors, along with those close to a typical CDNVG display phosphor in color space, should be avoided by CDNVG designers if the greatest conspicuity of symbology is desired. The results can be used by CDNVG symbology designers to optimize aircrew performance subject to wider constraints arising from the way color is used in the existing conventional cockpit instruments and displays.Liggins EP, Serle WP. Color vision in color display night vision goggles. Aerosp Med Hum Perform. 2017; 88(5):448-456.

Temporal binding of neural responses for focused attention in biosonar

PubMed Central

Simmons, James A.

2014-01-01

Big brown bats emit biosonar sounds and perceive their surroundings from the delays of echoes received by the ears. Broadcasts are frequency modulated (FM) and contain two prominent harmonics sweeping from 50 to 25 kHz (FM1) and from 100 to 50 kHz (FM2). Individual frequencies in each broadcast and each echo evoke single-spike auditory responses. Echo delay is encoded by the time elapsed between volleys of responses to broadcasts and volleys of responses to echoes. If echoes have the same spectrum as broadcasts, the volley of neural responses to FM1 and FM2 is internally synchronized for each sound, which leads to sharply focused delay images. Because of amplitude–latency trading, disruption of response synchrony within the volleys occurs if the echoes are lowpass filtered, leading to blurred, defocused delay images. This effect is consistent with the temporal binding hypothesis for perceptual image formation. Bats perform inexplicably well in cluttered surroundings where echoes from off-side objects ought to cause masking. Off-side echoes are lowpass filtered because of the shape of the broadcast beam, and they evoke desynchronized auditory responses. The resulting defocused images of clutter do not mask perception of focused images for targets. Neural response synchronization may select a target to be the focus of attention, while desynchronization may impose inattention on the surroundings by defocusing perception of clutter. The formation of focused biosonar images from synchronized neural responses, and the defocusing that occurs with disruption of synchrony, quantitatively demonstrates how temporal binding may control attention and bring a perceptual object into existence. PMID:25122915

Technology Applications Report

DTIC Science & Technology

1995-01-01

The HFA technology also has some important transportation applications, replacing camshafts and associated valve train components to open and close...illicit drug factories in the clutter of trees to searching through mug shot data banks at the police station, object identification systems have many

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.

Evolution of high duty cycle echolocation in bats.

PubMed

Fenton, M Brock; Faure, Paul A; Ratcliffe, John M

2012-09-01

Duty cycle describes the relative 'on time' of a periodic signal. In bats, we argue that high duty cycle (HDC) echolocation was selected for and evolved from low duty cycle (LDC) echolocation because increasing call duty cycle enhanced the ability of echolocating bats to detect, lock onto and track fluttering insects. Most echolocators (most bats and all birds and odontocete cetaceans) use LDC echolocation, separating pulse and echo in time to avoid forward masking. They emit short duration, broadband, downward frequency modulated (FM) signals separated by relatively long periods of silence. In contrast, bats using HDC echolocation emit long duration, narrowband calls dominated by a single constant frequency (CF) separated by relatively short periods of silence. HDC bats separate pulse and echo in frequency by exploiting information contained in Doppler-shifted echoes arising from their movements relative to background objects and their prey. HDC echolocators are particularly sensitive to amplitude and frequency glints generated by the wings of fluttering insects. We hypothesize that narrowband/CF calls produced at high duty cycle, and combined with neurobiological specializations for processing Doppler-shifted echoes, were essential to the evolution of HDC echolocation because they allowed bats to detect, lock onto and track fluttering targets. This advantage was especially important in habitats with dense vegetation that produce overlapping, time-smeared echoes (i.e. background acoustic clutter). We make four specific, testable predictions arising from this hypothesis.

Development of a machine vision system for automated structural assembly

NASA Technical Reports Server (NTRS)

Sydow, P. Daniel; Cooper, Eric G.

1992-01-01

Research is being conducted at the LaRC to develop a telerobotic assembly system designed to construct large space truss structures. This research program was initiated within the past several years, and a ground-based test-bed was developed to evaluate and expand the state of the art. Test-bed operations currently use predetermined ('taught') points for truss structural assembly. Total dependence on the use of taught points for joint receptacle capture and strut installation is neither robust nor reliable enough for space operations. Therefore, a machine vision sensor guidance system is being developed to locate and guide the robot to a passive target mounted on the truss joint receptacle. The vision system hardware includes a miniature video camera, passive targets mounted on the joint receptacles, target illumination hardware, and an image processing system. Discrimination of the target from background clutter is accomplished through standard digital processing techniques. Once the target is identified, a pose estimation algorithm is invoked to determine the location, in three-dimensional space, of the target relative to the robots end-effector. Preliminary test results of the vision system in the Automated Structural Assembly Laboratory with a range of lighting and background conditions indicate that it is fully capable of successfully identifying joint receptacle targets throughout the required operational range. Controlled optical bench test results indicate that the system can also provide the pose estimation accuracy to define the target position.

Autonomous terrain characterization and modelling for dynamic control of unmanned vehicles

NASA Technical Reports Server (NTRS)

Talukder, A.; Manduchi, R.; Castano, R.; Owens, K.; Matthies, L.; Castano, A.; Hogg, R.

2002-01-01

This end-to-end obstacle negotiation system is envisioned to be useful in optimized path planning and vehicle navigation in terrain conditions cluttered with vegetation, bushes, rocks, etc. Results on natural terrain with various natural materials are presented.

Metrics for Emitter Selection for Multistatic Synthetic Aperture Radar

DTIC Science & Technology

2013-09-01

the Faculty Department of Electrical and Computer Engineering Graduate School of Engineering and Management Air Force Insitute of Technology Air...130 5.2 Test Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 5.2.1 Weighting of Criteria...Ratio Test . . . . . . . . . . . . . . . . . . . . 20 CNR Clutter to Noise Ratio . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 QNR

Instrumentation for Infrared Airglow Clutter.

DTIC Science & Technology

1987-03-10

gain, and filter position to the Camera Head, and monitors these parameters as well as preamp video. GAZER is equipped with a Lenzar wide angle, low...Specifications/Parameters VIDEO SENSOR: Camera ...... . LENZAR Intensicon-8 LLLTV using 2nd gen * micro-channel intensifier and proprietary camera tube

Statistical characteristics of MST radar echoes and its interpretation

NASA Technical Reports Server (NTRS)

Woodman, Ronald F.

1989-01-01

Two concepts of fundamental importance are reviewed: the autocorrelation function and the frequency power spectrum. In addition, some turbulence concepts, the relationship between radar signals and atmospheric medium statistics, partial reflection, and the characteristics of noise and clutter interference are discussed.

Next generation miniature simultaneous multi-hyperspectral imaging systems

NASA Astrophysics Data System (ADS)

Hinnrichs, Michele; Gupta, Neelam

2014-03-01

The concept for a hyperspectral imaging system using a Fabry-Perot tunable filter (FPTF) array that is fabricated using "miniature optical electrical mechanical system" (MOEMS) technology. [1] Using an array of FPTF as an approach to hyperspectral imaging relaxes wavelength tuning requirements considerably because of the reduced portion of the spectrum that is covered by each element in the array. In this paper, Pacific Advanced Technology and ARL present the results of a concept design and performed analysis of a MOEMS based tunable Fabry-Perot array (FPTF) to perform simultaneous multispectral and hyperspectral imaging with relatively high spatial resolution. The concept design was developed with support of an Army SBIR Phase I program The Fabry-Perot tunable MOEMS filter array was combined with a miniature optics array and a focal plane array of 1024 x 1024 pixels to produce 16 colors every frame of the camera. Each color image has a spatial resolution of 256 x 256 pixels with an IFOV of 1.7 mrads and FOV of 25 degrees. The spectral images are collected simultaneously allowing high resolution spectral-spatial-temporal information in each frame of the camera, thus enabling the implementation of spectral-temporal-spatial algorithms in real-time to provide high sensitivity for the detection of weak signals in a high clutter background environment with low sensitivity to camera motion. The challenge in the design was the independent actuation of each Fabry Perot element in the array allowing for individual tuning. An additional challenge was the need to maximize the fill factor to improve the spatial coverage with minimal dead space. This paper will only address the concept design and analysis of the Fabry-Perot tunable filter array. A previous paper presented at SPIE DSS in 2012 explained the design of the optical array.

Hawk Eyes II: Diurnal Raptors Differ in Head Movement Strategies When Scanning from Perches

PubMed Central

O'Rourke, Colleen T.; Pitlik, Todd; Hoover, Melissa; Fernández-Juricic, Esteban

2010-01-01

Background Relatively little is known about the degree of inter-specific variability in visual scanning strategies in species with laterally placed eyes (e.g., birds). This is relevant because many species detect prey while perching; therefore, head movement behavior may be an indicator of prey detection rate, a central parameter in foraging models. We studied head movement strategies in three diurnal raptors belonging to the Accipitridae and Falconidae families. Methodology/Principal Findings We used behavioral recording of individuals under field and captive conditions to calculate the rate of two types of head movements and the interval between consecutive head movements. Cooper's Hawks had the highest rate of regular head movements, which can facilitate tracking prey items in the visually cluttered environment they inhabit (e.g., forested habitats). On the other hand, Red-tailed Hawks showed long intervals between consecutive head movements, which is consistent with prey searching in less visually obstructed environments (e.g., open habitats) and with detecting prey movement from a distance with their central foveae. Finally, American Kestrels have the highest rates of translational head movements (vertical or frontal displacements of the head keeping the bill in the same direction), which have been associated with depth perception through motion parallax. Higher translational head movement rates may be a strategy to compensate for the reduced degree of eye movement of this species. Conclusions Cooper's Hawks, Red-tailed Hawks, and American Kestrels use both regular and translational head movements, but to different extents. We conclude that these diurnal raptors have species-specific strategies to gather visual information while perching. These strategies may optimize prey search and detection with different visual systems in habitat types with different degrees of visual obstruction. PMID:20877650

Achievable Performance and Effective Interrogator Design for SAW RFID Sensor Tags

NASA Technical Reports Server (NTRS)

Barton, Richard J.

2011-01-01

For many NASA missions, remote sensing is a critical application that supports activities such as environmental monitoring, planetary science, structural shape and health monitoring, non-destructive evaluation, etc. The utility of the remote sensing devices themselves is greatly increased if they are passive that is, they do not require any on-board power supply such as batteries and if they can be identified uniquely during the sensor interrogation process. Additional passive sensor characteristics that enable greater utilization in space applications are small size and weight, long read ranges with low interrogator power, ruggedness, and operability in extreme environments (vacuum, extreme high/low temperature, high radiation, etc.) In this paper, we consider one very promising passive sensor technology, called surface acoustic wave (SAW) radio-frequency identification (RFID), that satisfies all of these criteria. Although SAW RFID tags have great potential for use in numerous space-based remote sensing applications, the limited collision resolution capability of current generation tags limits the performance in a cluttered sensing environment. That is, as more SAW-based sensors are added to the environment, numerous tag responses are superimposed at the receiver and decoding all or even a subset of the telemetry becomes increasingly difficult. Background clutter generated by reflectors other than the sensors themselves is also a problem, as is multipath interference and signal distortion, but the limiting factor in many remote sensing applications can be expected to be tag mutual interference. This problem may be greatly mitigated by proper design of the SAW tag waveform, but that remains an open research problem, and in the meantime, several other related questions remain to be answered including: What are the fundamental relationships between tag parameters such as bit-rate, time-bandwidth-product, SNR, and achievable collision resolution? What are the differences in optimal or near-optimal interrogator designs between noise-limited environments and interference-limited environments? What are the performance characteristics of different interrogator designs in term of parameters such as transmitter power level, range, and number of interfering tags? In this paper, we present the results of a research effort aimed at providing at least partial answers to all of these questions.

CRF-Based Model for Instrument Detection and Pose Estimation in Retinal Microsurgery.

PubMed

Alsheakhali, Mohamed; Eslami, Abouzar; Roodaki, Hessam; Navab, Nassir

2016-01-01

Detection of instrument tip in retinal microsurgery videos is extremely challenging due to rapid motion, illumination changes, the cluttered background, and the deformable shape of the instrument. For the same reason, frequent failures in tracking add the overhead of reinitialization of the tracking. In this work, a new method is proposed to localize not only the instrument center point but also its tips and orientation without the need of manual reinitialization. Our approach models the instrument as a Conditional Random Field (CRF) where each part of the instrument is detected separately. The relations between these parts are modeled to capture the translation, rotation, and the scale changes of the instrument. The tracking is done via separate detection of instrument parts and evaluation of confidence via the modeled dependence functions. In case of low confidence feedback an automatic recovery process is performed. The algorithm is evaluated on in vivo ophthalmic surgery datasets and its performance is comparable to the state-of-the-art methods with the advantage that no manual reinitialization is needed.

Using SPOT–5 HRG Data in Panchromatic Mode for Operational Detection of Small Ships in Tropical Area

PubMed Central

Corbane, Christina; Marre, Fabrice; Petit, Michel

2008-01-01

Nowadays, there is a growing interest in applications of space remote sensing systems for maritime surveillance which includes among others traffic surveillance, maritime security, illegal fisheries survey, oil discharge and sea pollution monitoring. Within the framework of several French and European projects, an algorithm for automatic ship detection from SPOT–5 HRG data was developed to complement existing fishery control measures, in particular the Vessel Monitoring System. The algorithm focused on feature–based analysis of satellite imagery. Genetic algorithms and Neural Networks were used to deal with the feature–borne information. Based on the described approach, a first prototype was designed to classify small targets such as shrimp boats and tested on panchromatic SPOT–5, 5–m resolution product taking into account the environmental and fishing context. The ability to detect shrimp boats with satisfactory detection rates is an indicator of the robustness of the algorithm. Still, the benchmark revealed problems related to increased false alarm rates on particular types of images with a high percentage of cloud cover and a sea cluttered background. PMID:27879859

Learning Compositional Shape Models of Multiple Distance Metrics by Information Projection.

PubMed

Luo, Ping; Lin, Liang; Liu, Xiaobai

2016-07-01

This paper presents a novel compositional contour-based shape model by incorporating multiple distance metrics to account for varying shape distortions or deformations. Our approach contains two key steps: 1) contour feature generation and 2) generative model pursuit. For each category, we first densely sample an ensemble of local prototype contour segments from a few positive shape examples and describe each segment using three different types of distance metrics. These metrics are diverse and complementary with each other to capture various shape deformations. We regard the parameterized contour segment plus an additive residual ϵ as a basic subspace, namely, ϵ -ball, in the sense that it represents local shape variance under the certain distance metric. Using these ϵ -balls as features, we then propose a generative learning algorithm to pursue the compositional shape model, which greedily selects the most representative features under the information projection principle. In experiments, we evaluate our model on several public challenging data sets, and demonstrate that the integration of multiple shape distance metrics is capable of dealing various shape deformations, articulations, and background clutter, hence boosting system performance.

Geographical topic learning for social images with a deep neural network

NASA Astrophysics Data System (ADS)

Feng, Jiangfan; Xu, Xin

2017-03-01

The use of geographical tagging in social-media images is becoming a part of image metadata and a great interest for geographical information science. It is well recognized that geographical topic learning is crucial for geographical annotation. Existing methods usually exploit geographical characteristics using image preprocessing, pixel-based classification, and feature recognition. How to effectively exploit the high-level semantic feature and underlying correlation among different types of contents is a crucial task for geographical topic learning. Deep learning (DL) has recently demonstrated robust capabilities for image tagging and has been introduced into geoscience. It extracts high-level features computed from a whole image component, where the cluttered background may dominate spatial features in the deep representation. Therefore, a method of spatial-attentional DL for geographical topic learning is provided and we can regard it as a special case of DL combined with various deep networks and tuning tricks. Results demonstrated that the method is discriminative for different types of geographical topic learning. In addition, it outperforms other sequential processing models in a tagging task for a geographical image dataset.

Real-time probabilistic covariance tracking with efficient model update.

PubMed

Wu, Yi; Cheng, Jian; Wang, Jinqiao; Lu, Hanqing; Wang, Jun; Ling, Haibin; Blasch, Erik; Bai, Li

2012-05-01

The recently proposed covariance region descriptor has been proven robust and versatile for a modest computational cost. The covariance matrix enables efficient fusion of different types of features, where the spatial and statistical properties, as well as their correlation, are characterized. The similarity between two covariance descriptors is measured on Riemannian manifolds. Based on the same metric but with a probabilistic framework, we propose a novel tracking approach on Riemannian manifolds with a novel incremental covariance tensor learning (ICTL). To address the appearance variations, ICTL incrementally learns a low-dimensional covariance tensor representation and efficiently adapts online to appearance changes of the target with only O(1) computational complexity, resulting in a real-time performance. The covariance-based representation and the ICTL are then combined with the particle filter framework to allow better handling of background clutter, as well as the temporary occlusions. We test the proposed probabilistic ICTL tracker on numerous benchmark sequences involving different types of challenges including occlusions and variations in illumination, scale, and pose. The proposed approach demonstrates excellent real-time performance, both qualitatively and quantitatively, in comparison with several previously proposed trackers.

Probability theory for 3-layer remote sensing radiative transfer model: univariate case.

PubMed

Ben-David, Avishai; Davidson, Charles E

2012-04-23

A probability model for a 3-layer radiative transfer model (foreground layer, cloud layer, background layer, and an external source at the end of line of sight) has been developed. The 3-layer model is fundamentally important as the primary physical model in passive infrared remote sensing. The probability model is described by the Johnson family of distributions that are used as a fit for theoretically computed moments of the radiative transfer model. From the Johnson family we use the SU distribution that can address a wide range of skewness and kurtosis values (in addition to addressing the first two moments, mean and variance). In the limit, SU can also describe lognormal and normal distributions. With the probability model one can evaluate the potential for detecting a target (vapor cloud layer), the probability of observing thermal contrast, and evaluate performance (receiver operating characteristics curves) in clutter-noise limited scenarios. This is (to our knowledge) the first probability model for the 3-layer remote sensing geometry that treats all parameters as random variables and includes higher-order statistics. © 2012 Optical Society of America

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.

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.

Robust Arm and Hand Tracking by Unsupervised Context Learning

PubMed Central

Spruyt, Vincent; Ledda, Alessandro; Philips, Wilfried

2014-01-01

Hand tracking in video is an increasingly popular research field due to the rise of novel human-computer interaction methods. However, robust and real-time hand tracking in unconstrained environments remains a challenging task due to the high number of degrees of freedom and the non-rigid character of the human hand. In this paper, we propose an unsupervised method to automatically learn the context in which a hand is embedded. This context includes the arm and any other object that coherently moves along with the hand. We introduce two novel methods to incorporate this context information into a probabilistic tracking framework, and introduce a simple yet effective solution to estimate the position of the arm. Finally, we show that our method greatly increases robustness against occlusion and cluttered background, without degrading tracking performance if no contextual information is available. The proposed real-time algorithm is shown to outperform the current state-of-the-art by evaluating it on three publicly available video datasets. Furthermore, a novel dataset is created and made publicly available for the research community. PMID:25004155

Vehicle monitoring under Vehicular Ad-Hoc Networks (VANET) parameters employing illumination invariant correlation filters for the Pakistan motorway police

NASA Astrophysics Data System (ADS)

Gardezi, A.; Umer, T.; Butt, F.; Young, R. C. D.; Chatwin, C. R.

2016-04-01

A spatial domain optimal trade-off Maximum Average Correlation Height (SPOT-MACH) filter has been previously developed and shown to have advantages over frequency domain implementations in that it can be made locally adaptive to spatial variations in the input image background clutter and normalised for local intensity changes. The main concern for using the SPOT-MACH is its computationally intensive nature. However in the past enhancements techniques were proposed for the SPOT-MACH to make its execution time comparable to its frequency domain counterpart. In this paper a novel approach is discussed which uses VANET parameters coupled with the SPOT-MACH in order to minimise the extensive processing of the large video dataset acquired from the Pakistan motorways surveillance system. The use of VANET parameters gives us an estimation criterion of the flow of traffic on the Pakistan motorway network and acts as a precursor to the training algorithm. The use of VANET in this scenario would contribute heavily towards the computational complexity minimization of the proposed monitoring system.

Salient contour extraction from complex natural scene in night vision image

NASA Astrophysics Data System (ADS)

Han, Jing; Yue, Jiang; Zhang, Yi; Bai, Lian-fa

2014-03-01

The theory of center-surround interaction in non-classical receptive field can be applied in night vision information processing. In this work, an optimized compound receptive field modulation method is proposed to extract salient contour from complex natural scene in low-light-level (LLL) and infrared images. The kernel idea is that multi-feature analysis can recognize the inhomogeneity in modulatory coverage more accurately and that center and surround with the grouping structure satisfying Gestalt rule deserves high connection-probability. Computationally, a multi-feature contrast weighted inhibition model is presented to suppress background and lower mutual inhibition among contour elements; a fuzzy connection facilitation model is proposed to achieve the enhancement of contour response, the connection of discontinuous contour and the further elimination of randomly distributed noise and texture; a multi-scale iterative attention method is designed to accomplish dynamic modulation process and extract contours of targets in multi-size. This work provides a series of biologically motivated computational visual models with high-performance for contour detection from cluttered scene in night vision images.