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Sample records for radar target classification

  1. Polarimetric laser radar target classification.

    PubMed

    Chun, Cornell S L; Sadjadi, Firooz A

    2005-07-15

    Imaging laser radar (ladar) systems have been developed for automatic target identification in surveillance systems. Ladar uses the range value at the target pixels to estimate the target's 3-D shape and identify the target. For targets in clutter and partially hidden targets, there are ambiguities in determining which pixels are on target that lead to uncertainties in determining the target's 3-D shape. An improvement is to use the polarization components of the reflected light. We describe the operation and preliminary evaluation of a polarization diverse imaging ladar system. Using a combination of intensity, range, and degree of polarization, we are better able to identify and distinguish the target from other objects of the same class.

  2. Radar target classification using compressively sensed features

    NASA Astrophysics Data System (ADS)

    Jouny, Ismail

    2017-05-01

    The paper focuses on extracting scattering centers of radar targets using compressive sensing and using them as features in a target recognition system. It has been shown that a target's high resolution range profile (HRRP) is sparse in time corresponding to few scatterers that can be associated with target geometry. The recognition system is tested using real radar data of commercial aircraft models. Classification is carried out using distance based and correlation based techniques. Scenarios where the target aspect angle is unknown or known to be within a certain range are also examined.

  3. Feature analysis for indoor radar target classification

    NASA Astrophysics Data System (ADS)

    Bufler, Travis D.; Narayanan, Ram M.

    2016-05-01

    This paper analyzes the spectral features from human beings and indoor clutter for building and tuning Support Vector Machines (SVMs) classifiers for the purpose of classifying stationary human targets. The spectral characteristics were obtained through simulations using Finite Difference Time Domain (FDTD) techniques where the radar cross section (RCS) of humans and indoor clutter objects were captured over a wide range of frequencies, polarizations, aspect angles, and materials. Additionally, experimental data was obtained using a vector network analyzer. Two different feature sets for class discrimination are used from the acquired target and clutter RCS spectral data sets. The first feature vectors consist of the raw spectral characteristics, while the second set of feature vectors are statistical features extracted over a set frequency interval. Utilizing variables of frequency and polarization, a SVM classifier can be trained to classify unknown targets as a human or clutter. Classification accuracy over 80% can be effectively achieved given appropriate features.

  4. Vector quantization and learning vector quantization for radar target classification

    NASA Astrophysics Data System (ADS)

    Stewart, Clayton V.; Lu, Yi-Chuan; Larson, Victor J.

    1993-10-01

    Radar target classification performance is greatly dependent on how the classifier represents the strongly angle dependent radar target signatures. This paper compares the performance of classifiers that represent radar target signatures using vector quantization (VQ) and learning vector quantization (LVQ). The classifier performance is evaluated with a set of high resolution millimeter-wave radar data from four ground vehicles (Camaro, van, pickup, and bulldozer). LVQ explicitly includes classification performance in its data representation criterion, whereas VQ only makes use of a distortion measure such as mean square distance. The classifier that uses LVQ to represent the radar data has a much higher probability of correct classification than VQ.

  5. Classification of Radar Targets Using Invariant Features

    DTIC Science & Technology

    2007-11-02

    deployed for a stationary target to extract scattering centers from the raw SAR radar data (also known as the Video Phase History or VPH ), and these...center on the target. These scattering center tracks are subtracted from the VPH to generate the residual VPH , and more scattering centers are...successively extracted until an acceptable amount of the VPH is characterized. The multiple sensors generate multiple two-dimensional views, and the 3D MAGI

  6. Target Classification for the Installation Security Radar System

    DTIC Science & Technology

    1981-11-01

    NUMBER 2. GOVT ACCESSION No. 3. RECIPIENT’S CATALOG NUMBER 4. TITLE (and Subtitle) 5. TYPE OF REPORT & PERIOD COVERED Target Classification for the...INSECTS MEASURED != .,EE FLIGHT (ref 10) L-band radarInsect target cross section (dBsm) Wingless Hawkmoth -60 Honeybee -63 Dragonfly -67 Since no studies

  7. Radar tracking and classification of littoral targets

    NASA Astrophysics Data System (ADS)

    Silvious, Jerry; Tahmoush, Dave

    2012-06-01

    Radar can provide inexpensive wide-area surveillance of river and port traffic for both security and emergency response. We demonstrate the tracking of multiple vessels as well as the micro-Doppler signatures of different classes of small vessels, including kayaks and zodiacs. The pattern of life of a river is analyzed over several days and can be used to easily identify suspicious or unusual cases.

  8. Radar target identification using probabilistic classification vector machines

    NASA Astrophysics Data System (ADS)

    Jouny, I.

    2016-05-01

    Radar target identification using probabilistic vector machines is investigated and tested using real radar data collected in a compact range for commercial aircraft models. Unlike relevance vector machines (RVM) that utilize zero-mean Gaussian prior for every weight for both negative and positive classes and are thus vulnerable to questionable (deceptive) vectors, probabilistic vector machines [2], alternatively, use nonnegative priors for the positive class and vice versa. This paper compares the performance of these machines with other target identification tools, and highlights scenarios where classification via a probabilistic vector machine is more plausible. The problem addressed in this paper is a M-ary target classification problem and is implemented as a set of pairwise comparisons between all competing hypotheses.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-09-29

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

  11. Classification of ground moving targets using bicepstrum-based features extracted from Micro-Doppler radar signatures

    NASA Astrophysics Data System (ADS)

    Molchanov, Pavlo O.; Astola, Jaakko T.; Egiazarian, Karen O.; Totsky, Alexander V.

    2013-12-01

    In this article, a novel bicepstrum-based approach is suggested for ground moving radar target classification. Distinctive classification features were extracted from short-time backscattering bispectrum estimates of the micro-Doppler signature. Real radar data were obtained using surveillance Doppler microwave radar operating at 34 GHz. Classifier performance was studied in detail using the Gaussian Mixture Mode and Maximum Likelihood decision making rule, and the results were verified on a multilayer perceptron and Support Vector Machine. Experimental real radar measurements demonstrated that it is quite feasible to discern three classes of humans (single, two and three persons) walking in a vegetation cluttered environment using proposed bicepstrum-based classification features. Sophisticated bispectrum-based signal processing provides the extraction of new classification features in the form of phase relationships in the radar data. It provides a novel insight into moving radar target classification compared to the commonly used energy-based strategy.

  12. A comparison of 1-D and 2-D algorithms for radar target classification

    NASA Astrophysics Data System (ADS)

    Novak, Leslie M.

    The use of high-resolution radar measurement data from four ground vehicles (bulldozer, Dodge Power Wagon, Dodge Van, and Camaro) to evaluate the performance of several 1D and 2D classifiers is discussed. The 1D classifiers use high-resolution range profiles to classify targets; the 2D classifier uses high-resolution inverse synthetic aperture radar (ISAR) images to classify targets. Classification performance results using the 1D and 2D algorithms are presented, and it is shown that the 2D algorithm performed best.

  13. Analysis and exploitation of multipath ghosts in radar target image classification.

    PubMed

    Smith, Graeme E; Mobasseri, Bijan G

    2014-04-01

    An analysis of the relationship between multipath ghosts and the direct target image for radar imaging is presented. A multipath point spread function (PSF) is defined that allows for specular reflections in the local environment and can allow the ghost images to be localized. Analysis of the multipath PSF shows that certain ghosts can only be focused for the far field synthetic aperture radar case and not the full array case. Importantly, the ghosts are shown to be equivalent to direct target images taken from different observation angles. This equivalence suggests that exploiting the ghosts would improve target classification performance, and this improvement is demonstrated using experimental data and a naïve Bayesian classifer. The maximum performance gain achieved is 32%.

  14. Noncooperative target classification using hierarchical modeling of high-range resolution radar signatures

    NASA Astrophysics Data System (ADS)

    Eom, Kie Bum

    1996-06-01

    The classification of high range resolution radar returns using multiscale features is considered. Because of the characteristics unique to radar signals, such as clutter and sensitivity to viewing angle change, classifiers using features extracted from a single scale do not meet the requirements of non-cooperative target identification (NCTI). We present a hierarchical ARMA model for modeling high range resolution radar signals in multiple scales and apply it to NCTI database containing 5000 test samples and 5000 training samples. We first show that the radar signal at a course scale follows an ARMA process if it follows an ARMA model at a finer scale. The model parameters at different scales are easily computed from the parameters at another scale. Therefore, the hierarchical model allows us to compute spectral features at the coarse scale without adding much computational burden. The multiscale spectral features at five scales are computed using the hierarchical modeling approach, and are classified by a minimum distance classifier. The multiscale classifier is applied to both poorly aligned data and better aligned data. For both data sets, about 95 percent of the radar returns were correctly classified, showing that the multiscale classifier is robust to misalignment.

  15. rScene: a revolutionary low-cost micro-radar for target classification and tracking

    NASA Astrophysics Data System (ADS)

    Plummer, Thomas J.; Porter, Rich; Raines, Robert

    2014-06-01

    A small form factor, low cost radar named rScene® has been designed by McQ Inc. for the unattended detection, classification, tracking, and speed estimation of people and vehicles. This article will describe recent performance enhancements added to rScene® and present results relative to detection range and false alarms. Additionally, a low power (<1W) processing scheme is described that allows the rScene® to be deployed for longer duration, while still detecting desired target scenarios. Using the rScene® to detect other targets of interest like boats over water will also be addressed. Lastly, the lack of performance degradation due to hiding the rScene® in various types of concealed scenarios like behind walls, doors, foliage and camouflage material will be addressed. rScene® provides a variety of options to integrate the device into both wired and wireless communication infrastructures. Based on its sophisticated signal processing algorithms to classify targets and reject clutter, it allows for operation in challenging urban environments in which traditional unattended ground sensor modalities are less effective.

  16. Analytic radar micro-Doppler signatures classification

    NASA Astrophysics Data System (ADS)

    Oh, Beom-Seok; Gu, Zhaoning; Wang, Guan; Toh, Kar-Ann; Lin, Zhiping

    2017-06-01

    Due to its capability of capturing the kinematic properties of a target object, radar micro-Doppler signatures (m-DS) play an important role in radar target classification. This is particularly evident from the remarkable number of research papers published every year on m-DS for various applications. However, most of these works rely on the support vector machine (SVM) for target classification. It is well known that training an SVM is computationally expensive due to its nature of search to locate the supporting vectors. In this paper, the classifier learning problem is addressed by a total error rate (TER) minimization where an analytic solution is available. This largely reduces the search time in the learning phase. The analytically obtained TER solution is globally optimal with respect to the classification total error count rate. Moreover, our empirical results show that TER outperforms SVM in terms of classification accuracy and computational efficiency on a five-category radar classification problem.

  17. Radar clutter classification

    NASA Astrophysics Data System (ADS)

    Stehwien, Wolfgang

    1989-11-01

    The problem of classifying radar clutter as found on air traffic control radar systems is studied. An algorithm based on Bayes decision theory and the parametric maximum a posteriori probability classifier is developed to perform this classification automatically. This classifier employs a quadratic discriminant function and is optimum for feature vectors that are distributed according to the multivariate normal density. Separable clutter classes are most likely to arise from the analysis of the Doppler spectrum. Specifically, a feature set based on the complex reflection coefficients of the lattice prediction error filter is proposed. The classifier is tested using data recorded from L-band air traffic control radars. The Doppler spectra of these data are examined; the properties of the feature set computed using these data are studied in terms of both the marginal and multivariate statistics. Several strategies involving different numbers of features, class assignments, and data set pretesting according to Doppler frequency and signal to noise ratio were evaluated before settling on a workable algorithm. Final results are presented in terms of experimental misclassification rates and simulated and classified plane position indicator displays.

  18. Using phase for radar scatterer classification

    NASA Astrophysics Data System (ADS)

    Moore, Linda J.; Rigling, Brian D.; Penno, Robert P.; Zelnio, Edmund G.

    2017-04-01

    Traditional synthetic aperture radar (SAR) systems tend to discard phase information of formed complex radar imagery prior to automatic target recognition (ATR). This practice has historically been driven by available hardware storage, processing capabilities, and data link capacity. Recent advances in high performance computing (HPC) have enabled extremely dense storage and processing solutions. Therefore, previous motives for discarding radar phase information in ATR applications have been mitigated. First, we characterize the value of phase in one-dimensional (1-D) radar range profiles with respect to the ability to correctly estimate target features, which are currently employed in ATR algorithms for target discrimination. These features correspond to physical characteristics of targets through radio frequency (RF) scattering phenomenology. Physics-based electromagnetic scattering models developed from the geometrical theory of diffraction are utilized for the information analysis presented here. Information is quantified by the error of target parameter estimates from noisy radar signals when phase is either retained or discarded. Operating conditions (OCs) of signal-tonoise ratio (SNR) and bandwidth are considered. Second, we investigate the value of phase in 1-D radar returns with respect to the ability to correctly classify canonical targets. Classification performance is evaluated via logistic regression for three targets (sphere, plate, tophat). Phase information is demonstrated to improve radar target classification rates, particularly at low SNRs and low bandwidths.

  19. Integrated Range-Doppler Map and Extended Target Classification with Adaptive Waveform for Cognitive Radar

    DTIC Science & Technology

    2014-12-01

    REFERENCES [1] M. R. Bell, “Information theory and radar waveform design,” IEEE Trans. Information Theory., vol. 39, no. 5, pp. 1578 –1597, Sep. 1993...Bell, “Information theory and radar waveform design,” IEEE Trans. Information Theory., vol. 39, no. 5, pp. 1578 –1597, Sep. 1993. [7] J. Y. Nieh, and

  20. Development and Testing of a Multiple Frequency Continuous Wave Radar for Target Detection and Classification

    DTIC Science & Technology

    2007-03-01

    1 2’ VIH " 1 ’ 󈧏) (34) where is the modified Bessel function of zero order. Here is the conditional variance and is the conditional probability...10, the probability of detection is the area under the signal-plus-noise curve above the detection threshold co M vF (V 2+ A2)]10 ( vAPd= fnp~ju,( vIH ...Database Collection and Processing 7.1 Experimental Setup. Following the completion of the last radar hardware revision , an extensive database of radar

  1. Harmonic Phase Response of Nonlinear Radar Targets

    DTIC Science & Technology

    2015-10-01

    Frequency (E&RF) Division is the development of a radar system that can accurately detect and range an electronically nonlinear target, such as a detonator ...CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF PAGES 36 19a. NAME OF RESPONSIBLE PERSON Kelly D Sherbondy...from handheld radios to electronic detonators of improvised explosive devices (IEDs). Targets such as these are difficult to detect with linear radar

  2. Illumination Waveform Design for Non-Gaussian Multi-Hypothesis Target Classification in Cognitive Radar

    DTIC Science & Technology

    2012-06-01

    3 . REPORT TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE Illumination Waveform Design for Non-Gaussian Multi-Hypothesis Target...1  B.  OBJECTIVE ....................................................................................................2  C ...TRANSMISSION TECHNIQUES .....................................................12  C .  ITERATIVE ALGORITHMS FOR UPDATING THE PRIOR PROBABILITIES

  3. Online clustering algorithms for radar emitter classification.

    PubMed

    Liu, Jun; Lee, Jim P Y; Senior; Li, Lingjie; Luo, Zhi-Quan; Wong, K Max

    2005-08-01

    Radar emitter classification is a special application of data clustering for classifying unknown radar emitters from received radar pulse samples. The main challenges of this task are the high dimensionality of radar pulse samples, small sample group size, and closely located radar pulse clusters. In this paper, two new online clustering algorithms are developed for radar emitter classification: One is model-based using the Minimum Description Length (MDL) criterion and the other is based on competitive learning. Computational complexity is analyzed for each algorithm and then compared. Simulation results show the superior performance of the model-based algorithm over competitive learning in terms of better classification accuracy, flexibility, and stability.

  4. Basic Concepts of Radar Polarimetry and Its Applications to Target Discrimination, Classification, Imaging and Identification

    DTIC Science & Technology

    1982-05-18

    polarization basis Pre described in terms of geometrical target features as functions of the specular point surface coordinate parameters, known as gaussian ...phase OAB or OBA for SAA/SAB or SBB/SBA measurements was developed using fast magnetic waveguide switches and/or pin-diode switches, This method, when re...curvature recovery model Is based on the first order correction to the Physical Optics approximation. Higher order corrections are investigated by

  5. Radar target classification method with high accuracy and decision speed performance using MUSIC spectrum vectors and PCA projection

    NASA Astrophysics Data System (ADS)

    Secmen, Mustafa

    2011-10-01

    This paper introduces the performance of an electromagnetic target recognition method in resonance scattering region, which includes pseudo spectrum Multiple Signal Classification (MUSIC) algorithm and principal component analysis (PCA) technique. The aim of this method is to classify an "unknown" target as one of the "known" targets in an aspect-independent manner. The suggested method initially collects the late-time portion of noise-free time-scattered signals obtained from different reference aspect angles of known targets. Afterward, these signals are used to obtain MUSIC spectrums in real frequency domain having super-resolution ability and noise resistant feature. In the final step, PCA technique is applied to these spectrums in order to reduce dimensionality and obtain only one feature vector per known target. In the decision stage, noise-free or noisy scattered signal of an unknown (test) target from an unknown aspect angle is initially obtained. Subsequently, MUSIC algorithm is processed for this test signal and resulting test vector is compared with feature vectors of known targets one by one. Finally, the highest correlation gives the type of test target. The method is applied to wire models of airplane targets, and it is shown that it can tolerate considerable noise levels although it has a few different reference aspect angles. Besides, the runtime of the method for a test target is sufficiently low, which makes the method suitable for real-time applications.

  6. Radar System Classification Using Neural Networks

    DTIC Science & Technology

    1991-12-01

    This study investigated methods of improving the accuracy of neural networks in the classification of large numbers of classes. A literature search...revealed that neural networks have been successful in the radar classification problem, and that many complex problems have been solved using systems...of multiple neural networks . The experiments conducted were based on 32 classes of radar system data. The neural networks were modelled using a program

  7. Maximum likelihood classification of synthetic aperture radar imagery

    NASA Technical Reports Server (NTRS)

    Frost, V. S.; Yurovsky, L. S.

    1985-01-01

    Classification of synthetic aperture radar (SAR) images has important applications in geology, agriculture, and the military. A statistical model for SAR images is reviewed and a maximum likelihood classification algorithm developed for the classification of agricultural fields based on the model. It is first assumed that the target feature information is known a priori. The performance of the algorithm is then evaluated in terms of the probability of incorrect classification. A technique is also presented to extract the needed feature information from a SAR image; then both the feature extraction and the maximum likelihood classification algorithms are tested on a SEASAT-A SAR image.

  8. Millimeter radar improves target identification

    NASA Astrophysics Data System (ADS)

    McAulay, Alastair D.

    2011-06-01

    Recently developed millimeter wave radar has advantages for target identification over conventional microwave radar which typically use lower frequencies. We describe the pertinent features involved in the construction of the new millimeter wave radar, the pseudo-optical cavity source and the quasi-optical duplexer. The long wavelength relative to light allows the radar beam to penetrate through most weather because the wavelength is larger than the particle size for dust, drizzle rain, fog. Further the mm wave beam passes through an atmospheric transmission window that provides a dip in attenuation. The higher frequency than conventional radar provides higher Doppler frequencies, for example, than X-band radar. We show by simulation that small characteristic vibrations and slow turns of an aircraft become visible so that the Doppler signature improves identification. The higher frequency also reduces beam width, which increases transmit and receive antenna gains. For the same power the transmit beam extends to farther range and the increase in receive antenna gain increases signal to noise ratio for improved detection and identification. The narrower beam can also reduce clutter and reject other noise more readily. We show by simulation that the radar can be used at lower elevations over the sea than conventional radar.

  9. Feature utility in polarimetric radar image classification

    NASA Technical Reports Server (NTRS)

    Cumming, Ian G.; Van Zyl, Jakob J.

    1989-01-01

    The information content in polarimetric SAR images is examined, and the polarimetric image variables containing the information that is important to the classification of terrain features in the images are determined. It is concluded that accurate classification can be done when just over half of the image variables are retained. A reduction in image data dimensionality gives storage savings, and can lead to the improvement of classifier performance. In addition, it is shown that a simplified radar system with only phase-calibrated CO-POL or SINGLE TX channels can give classification performance which approaches that of a fully polarimetric radar.

  10. Multi-aspect angle classification of human radar signatures

    NASA Astrophysics Data System (ADS)

    Karabacak, C.; Gürbüz, S. Z.; Guldogan, M. B.; Gürbüz, A. C.

    2013-05-01

    The human micro-Doppler signature is a unique signature caused by the time-varying motion of each point on the human body, which can be used to discriminate humans from other targets exhibiting micro-Doppler, such as vehicles, tanks, helicopters, and even other animals. Classification of targets based on micro-Doppler generally involves joint timefrequency analysis of the radar return coupled with extraction of features that may be used to identify the target. Although many techniques have been investigated, including artificial neural networks and support vector machines, almost all suffer a drastic drop in classification performance as the aspect angle of human motion relative to the radar increases. This paper focuses on the use of radar networks to obtain multi-aspect angle data and thereby ameliorate the dependence of classification performance on aspect angle. Knowledge of human walking kinematics is exploited to generate a fuse spectrogram that incorporates estimates of model parameters obtained from each radar in the network. It is shown that the fused spectrogram better approximates the truly underlying motion of the target observed as compared with spectrograms generated from individual nodes.

  11. Detection of Marine Radar Targets

    NASA Astrophysics Data System (ADS)

    Briggs, John N.

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

  12. Discrimination between Targets and Clutter by Radar

    DTIC Science & Technology

    1981-12-01

    a corner reflector of known radar cross section in front of the target and recording the amplitude of the video signal from this range cell. The RF...in units of radar cross section and only a range correction was required. This is a reliable method of calibration provided the electromagnetic field...target or targets of known radar cross section . For this 10 second sample, the radars were operated in the applicable polariz atIon/frequency/resolution

  13. Holographic neural networks versus conventional neural networks: a comparative evaluation for the classification of landmine targets in ground-penetrating radar images

    NASA Astrophysics Data System (ADS)

    Mudigonda, Naga R.; Kacelenga, Ray; Edwards, Mark

    2004-09-01

    This paper evaluates the performance of a holographic neural network in comparison with a conventional feedforward backpropagation neural network for the classification of landmine targets in ground penetrating radar images. The data used in the study was acquired from four different test sites using the landmine detection system developed by General Dynamics Canada Ltd., in collaboration with the Defense Research and Development Canada, Suffield. A set of seven features extracted for each detected alarm is used as stimulus inputs for the networks. The recall responses of the networks are then evaluated against the ground truth to declare true or false detections. The area computed under the receiver operating characteristic curve is used for comparative purposes. With a large dataset comprising of data from multiple sites, both the holographic and conventional networks showed comparable trends in recall accuracies with area values of 0.88 and 0.87, respectively. By using independent validation datasets, the holographic network"s generalization performance was observed to be better (mean area = 0.86) as compared to the conventional network (mean area = 0.82). Despite the widely publicized theoretical advantages of the holographic technology, use of more than the required number of cortical memory elements resulted in an over-fitting phenomenon of the holographic network.

  14. Salient Feature Identification and Analysis using Kernel-Based Classification Techniques for Synthetic Aperture Radar Automatic Target Recognition

    DTIC Science & Technology

    2014-03-27

    combinations of these HRR projections represent the overall measured reflectivity of the target scene, g(s, φ), and can be expressed using the Radon ...collected in phase history and the target scene f (x, y) is desired, the inverse radon transform, or the backprojection operation, is more appropriate for

  15. Extended target recognition in cognitive radar networks.

    PubMed

    Wei, Yimin; Meng, Huadong; Liu, Yimin; Wang, Xiqin

    2010-01-01

    We address the problem of adaptive waveform design for extended target recognition in cognitive radar networks. A closed-loop active target recognition radar system is extended to the case of a centralized cognitive radar network, in which a generalized likelihood ratio (GLR) based sequential hypothesis testing (SHT) framework is employed. Using Doppler velocities measured by multiple radars, the target aspect angle for each radar is calculated. The joint probability of each target hypothesis is then updated using observations from different radar line of sights (LOS). Based on these probabilities, a minimum correlation algorithm is proposed to adaptively design the transmit waveform for each radar in an amplitude fluctuation situation. Simulation results demonstrate performance improvements due to the cognitive radar network and adaptive waveform design. Our minimum correlation algorithm outperforms the eigen-waveform solution and other non-cognitive waveform design approaches.

  16. Multisensor Target Detection And Classification

    NASA Astrophysics Data System (ADS)

    Ruck, Dennis W.; Rogers, Steven K.; Mills, James P.; Kabrisky, Matthew

    1988-08-01

    In this paper a new approach to the detection and classification of tactical targets using a multifunction laser radar sensor is developed. Targets of interest are tanks, jeeps, trucks, and other vehicles. Doppler images are segmented by developing a new technique which compensates for spurious doppler returns. Relative range images are segmented using an approach based on range gradients. The resultant shapes in the segmented images are then classified using Zernike moment invariants as shape descriptors. Two classification decision rules are implemented: a classical statistical nearest-neighbor approach and a multilayer perceptron architecture. The doppler segmentation algorithm was applied to a set of 180 real sensor images. An accurate segmentation was obtained for 89 percent of the images. The new doppler segmentation proved to be a robust method, and the moment invariants were effective in discriminating the tactical targets. Tanks were classified correctly 86 percent of the time. The most important result of this research is the demonstration of the use of a new information processing architecture for image processing applications.

  17. Autonomous Non-Linear Classification of LPI Radar Signal Modulations

    DTIC Science & Technology

    2007-09-01

    database of important LPI radar waveform modulations including Frequency Modulation Continuous Waveform ( FMCW ), Phase Shift Keying (PSK), Frequency...important LPI radar waveform modulations including Frequency Modulation Continuous Waveform ( FMCW ), Phase Shift Keying (PSK), Frequency Shift Keying (FSK...LINEAR CLASSIFICATION OF LPI RADAR SIGNAL MODULATIONS by Taylan O. Gulum September 2007 Thesis Co-Advisors: Phillip E. Pace Roberto

  18. Computing the apparent centroid of radar targets

    SciTech Connect

    Lee, C.E.

    1996-12-31

    A high-frequency multibounce radar scattering code was used as a simulation platform for demonstrating an algorithm to compute the ARC of specific radar targets. To illustrate this simulation process, several targets models were used. Simulation results for a sphere model were used to determine the errors of approximation associated with the simulation; verifying the process. The severity of glint induced tracking errors was also illustrated using a model of an F-15 aircraft. It was shown, in a deterministic manner, that the ARC of a target can fall well outside its physical extent. Finally, the apparent radar centroid simulation based on a ray casting procedure is well suited for use on most massively parallel computing platforms and could lead to the development of a near real-time radar tracking simulation for applications such as endgame fuzing, survivability, and vulnerability analyses using specific radar targets and fuze algorithms.

  19. Radar Imaging and Target Identification

    DTIC Science & Technology

    2009-02-09

    Methods in Wave Propagation, Vaxjo, Swe- den. • February 19, 2008, "Radar Imaging", math colloquium, Brigham- Young University. • January 31, 2008...manuscript, namely "Radar detection using sparsely distributed 19 apertures in urban environments", Ling Wang, II- Young Son, Trond Varslot, C. Evren...Coinmun. COM- 20, pp. 774-780, 1972. [24] M. Tomlinson, "New automatic equalizer employing modulo arithmetic," Electron. Lett. 7, pp. 138-139, 1971

  20. Two target height effects on interferometric synthetic aperture radar coherence

    SciTech Connect

    YOCKY,DAVID A.; JAKOWATZ JR.,CHARLES V.

    2000-03-07

    Useful products generated from interferometric synthetic aperture radar (IFSAR) complex data include height measurement, coherent change detection, and classification. The IFSAR coherence is a spatial measure of complex correlation between two collects, a product of IFSAR signal processing. A tacit assumption in such IFSAR signal processing is that one height target exists in each range-Doppler cell. This paper presents simulations of IFSAR coherence if two targets with different heights exist in a given range-Doppler cell, a condition in IFSAR collections produced by layover. It also includes airborne IFSAR data confirming the simulation results. The paper concludes by exploring the implications of the results on IFSAR classification and height measurements.

  1. Developments in target micro-Doppler signatures analysis: radar imaging, ultrasound and through-the-wall radar

    NASA Astrophysics Data System (ADS)

    Clemente, Carmine; Balleri, Alessio; Woodbridge, Karl; Soraghan, John J.

    2013-12-01

    Target motions, other than the main bulk translation of the target, induce Doppler modulations around the main Doppler shift that form what is commonly called a target micro-Doppler signature. Radar micro-Doppler signatures are generally both target and action specific and hence can be used to classify and recognise targets as well as to identify possible threats. In recent years, research into the use of micro-Doppler signatures for target classification to address many defence and security challenges has been of increasing interest. In this article, we present a review of the work published in the last 10 years on emerging applications of radar target analysis using micro-Doppler signatures. Specifically we review micro-Doppler target signatures in bistatic SAR and ISAR, through-the-wall radar and ultrasound radar. This article has been compiled to provide radar practitioners with a unique reference source covering the latest developments in micro-Doppler analysis, extraction and mitigation techniques. The article shows that this research area is highly active and fast moving and demonstrates that micro-Doppler techniques can provide important solutions to many radar target classification challenges.

  2. Crop classification with a Landsat/radar sensor combination

    NASA Technical Reports Server (NTRS)

    Li, R. Y.; Ulaby, F. T.; Eyton, J. R.

    1980-01-01

    A combined Landsat/radar approach to classification of remotely sensed data, with emphasis on crops, was undertaken. Radar data were obtained by microwave radar spectrometers over fields near Eudora, Kansas and Landsat image data were obtained for the same test site. After Landsat digital images were registered and test-cells extracted, a comparable set of radar image pixels were simulated to match the Landsat pixels. The combined data set is then used for classification, and the results are examined with the best combination of sensor variables identified. Finally, the usefulness of radar in a simulated cloud-cover situation is demonstrated. The major conclusion derived from this study is that the combination of radar/optical sensors is superior to either one alone.

  3. Optimal radar waveform design for moving target

    NASA Astrophysics Data System (ADS)

    Zhu, Binqi; Gao, Yesheng; Wang, Kaizhi; Liu, Xingzhao

    2016-07-01

    An optimal radar waveform-design method is proposed to detect moving targets in the presence of clutter and noise. The clutter is split into moving and static parts. Radar-moving target/clutter models are introduced and combined with Neyman-Pearson criteria to design optimal waveforms. Results show that optimal waveform for a moving target is different with that for a static target. The combination of simple-frequency signals could produce maximum detectability based on different noise-power spectrum density situations. Simulations show that our algorithm greatly improves signal-to-clutter plus noise ratio of radar system. Therefore, this algorithm may be preferable for moving target detection when prior information on clutter and noise is available.

  4. Fusion of radar and satellite target measurements

    NASA Astrophysics Data System (ADS)

    Moy, Gabriel; Blaty, Donald; Farber, Morton; Nealy, Carlton

    2011-06-01

    A potentially high payoff for the ballistic missile defense system (BMDS) is the ability to fuse the information gathered by various sensor systems. In particular, it may be valuable in the future to fuse measurements made using ground based radars with passive measurements obtained from satellite-based EO/IR sensors. This task can be challenging in a multitarget environment in view of the widely differing resolution between active ground-based radar and an observation made by a sensor at long range from a satellite platform. Additionally, each sensor system could have a residual pointing bias which has not been calibrated out. The problem is further compounded by the possibility that an EO/IR sensor may not see exactly the same set of targets as a microwave radar. In order to better understand the problems involved in performing the fusion of metric information from EO/IR satellite measurements with active microwave radar measurements, we have undertaken a study of this data fusion issue and of the associated data processing techniques. To carry out this analysis, we have made use of high fidelity simulations to model the radar observations from a missile target and the observations of the same simulated target, as gathered by a constellation of satellites. In the paper, we discuss the improvements seen in our tests when fusing the state vectors, along with the improvements in sensor bias estimation. The limitations in performance due to the differing phenomenology between IR and microwave radar are discussed as well.

  5. Radar Tomography of Moving Targets

    DTIC Science & Technology

    2005-09-01

    resolution limitations of CW, SAR and ISAR radar and the theory on tomographic processing. The following sections briefly review the activities...this form of logic to the case of SAR imaging. Here the cross range resolution is given by: )2/sin(4 θ λδ Δ =cr (which is approximately equivalent to...the image. The multilook technique was used to compare the range-Doppler results to the final narrowband tomographic technique. The multilook

  6. Classification of Targets in SAR Images Using ISAR Data

    DTIC Science & Technology

    2005-05-01

    Classification of Targets in SAR Images Using ISAR Data J. J. M. de Wit, R. J. Dekker, and A. C. van den Broek TNO Defence, Security, and Safety...classification of targets in SAR images by using ISAR measurements was studied, based on polarimetric SAR and ISAR data acquired with the MEMPHIS...interest in synthetic aperture radar ( SAR ) systems is increasing as well, mainly due to their all-weather capability. A study for the Dutch Ministry of

  7. Crop classification using airborne radar and LANDSAT data. [Colby, Kansas

    NASA Technical Reports Server (NTRS)

    Ulaby, F. T. (Principal Investigator); Li, R. Y.; Shanmugam, K. S.

    1981-01-01

    Airborne radar data acquired with a 13.3 GHz scatterometer over a test-site near Colby, Kansas were used to investigate the statistical properties of the scattering coefficient of three types of vegetation cover and of bare soil. A statistical model for radar data was developed that incorporates signal-fading and natural within-field variabilities. Estimates of the within-field and between-field coefficients of variation were obtained for each cover-type and compared with similar quantities derived from LANDSAT images of the same fields. The classification accuracy provided by LANDSAT alone, radar alone, and both sensors combined was investigated. The results indicate that the addition of radar to LANDSAT improves the classification accuracy by about 10; percentage-points when the classification is performed on a pixel basis and by about 15 points when performed on a field-average basis.

  8. Classification SAR targets with support vector machine

    NASA Astrophysics Data System (ADS)

    Cao, Lanying

    2007-02-01

    With the development of Synthetic Aperture Radar (SAR) technology, automatic target recognition (ATR) is becoming increasingly important. In this paper, we proposed a 3-class target classification system in SAR images. The system is based on invariant wavelet moments and support vector machine (SVM) algorithm. It is a two-stage approach. The first stage is to extract and select a small set of wavelet invariant moment features to indicate target images. The wavelet invariant moments take both advantages of the wavelet inherent property of multi-resolution analysis and moment invariants quality of invariant to translation, scaling changes and rotation. The second stage is classification of targets with SVM algorithm. SVM is based on the principle of structural risk minimization (SRM), which has been shown better than the principle of empirical risk minimization (ERM) which is used by many conventional networks. To test the performance and efficiency of the proposed method, we performed experiments on invariant wavelet moments, different kernel functions, 2-class identification, and 3-class identification. Test results show that wavelet invariant moments indicate the target effectively; linear kernel function achieves better results than other kernel functions, and SVM classification approach performs better than conventional nearest distance approach.

  9. Crop classification using airborne radar and Landsat data

    NASA Technical Reports Server (NTRS)

    Ulaby, F. T.; Li, R. Y.; Shanmugan, K. S.

    1982-01-01

    NASA 13.3 GHz airborne radar data from a soil moisture measurement analysis is used to investigate the statistical nature of the radar backscattering coefficient for bare ground and three different crop types, and to evaluate the crop classification rates using Landsat data alone or combined with the airborne survey. The scatterometer was a fan-beam Doppler system, VV polarized, and is considered only for 50 deg angles of incidence. A total of 36 fields were covered a week apart by the aircraft and Landsat, and Rayleigh statistics were used in the frequency averaging to eliminate fluctuations due to random fluctuations. Within-field variances were calculated for the Landsat and the radar data and used to design optimum crop classification procedures. The Landsat Band 4 readings were 67% accurate, and an increase in accuracy of 10% was achieved by the addition of the radar data.

  10. LADAR And FLIR Based Sensor Fusion For Automatic Target Classification

    NASA Astrophysics Data System (ADS)

    Selzer, Fred; Gutfinger, Dan

    1989-01-01

    The purpose of this report is to show results of automatic target classification and sensor fusion for forward looking infrared (FLIR) and Laser Radar sensors. The sensor fusion data base was acquired from the Naval Weapon Center and it consists of coregistered Laser RaDAR (range and reflectance image), FLIR (raw and preprocessed image) and TV. Using this data base we have developed techniques to extract relevant object edges from the FLIR and LADAR which are correlated to wireframe models. The resulting correlation coefficients from both the LADAR and FLIR are fused using either the Bayesian or the Dempster-Shafer combination method so as to provide a higher confidence target classifica-tion level output. Finally, to minimize the correlation process the wireframe models are modified to reflect target range (size of target) and target orientation which is extracted from the LADAR reflectance image.

  11. Synthetic aperture radar automatic target recognition based on curvelet transform

    NASA Astrophysics Data System (ADS)

    Wang, Shuang; Liu, Zhuo; Jiao, Licheng; He, Jun

    2009-10-01

    A novel synthetic aperture radar (SAR) automatic target recognition (ATR) approach based on Curvelet Transform is proposed. However, the existing approaches can not extract the more effective feature. In this paper, our method is concentrated on a new effective representation of the moving and stationary target acquisition and recognition (MSTAR) database to obtain a more accurate target region and reduce feature dimension. Firstly, MSTAR database can be extracted feature through the optimal sparse representation by curvelets to obtain a clear target region. However, considering the loss of part of edges of image. We extract coarse feature, which is to compensate fine feature error brought by segmentation. The final features consisting of fine and coarse feature are classified by SVM with Gaussian radial basis function (RBF) kernel. The experiments show that our proposed algorithm can achieve a better correct classification rate.

  12. Consideration of radar target glint from ST during OMV rendezvous

    NASA Astrophysics Data System (ADS)

    McDonald, M. W.; Malone, L. B.; Gleason, E. H.

    1985-09-01

    The nature of radar target glint and the factors upon which it depends when using the Hubble Space Telescope as a radar target is discussed. An analysis of the glint problem using a 35 MHz or 94 MHz radar on the orbital maneuvering vehicle is explored. A strategy for overcoming glint is suggested.

  13. Consideration of radar target glint from ST during OMV rendezvous

    NASA Technical Reports Server (NTRS)

    Mcdonald, M. W.; Malone, L. B.; Gleason, E. H.

    1985-01-01

    The nature of radar target glint and the factors upon which it depends when using the Hubble Space Telescope as a radar target is discussed. An analysis of the glint problem using a 35 MHz or 94 MHz radar on the orbital maneuvering vehicle is explored. A strategy for overcoming glint is suggested.

  14. Radar micro-Doppler simulations of classification capability with frequency

    NASA Astrophysics Data System (ADS)

    Tahmoush, David; Silvious, Jerry

    2012-06-01

    Classifying human signatures using radar requires a detailed understanding of the RF scattering phenomenology associated with humans as well as their motion. We model humans engaged in the activity of walking and analyze the separability of different body parts with frequency as well as lookdown angle. This work seeks to estimate the ability to classify the micro-Doppler signals generated by human motion, and especially arm motion, as a function of the radar frequency and other parameters. The simulations imply that for classification using arm motion, frequencies at Ku-band or higher are probably required, and that lookdown angle has a significant effect on the classification capability of the radar. Additionally, the sensitivity of the system required to isolate the motion of different body parts is estimated.

  15. Fall detection and classifications based on time-scale radar signal characteristics

    NASA Astrophysics Data System (ADS)

    Gadde, Ajay; Amin, Moeness G.; Zhang, Yimin D.; Ahmad, Fauzia

    2014-05-01

    Unattended catastrophic falls result in risk to the lives of elderly. There are growing efforts and rising interest in detecting falls of the aging population, especially those living alone. Radar serves as an effective non-intrusive sensor for detecting human activities. For radar to be effective, it is important to achieve low false alarms, i.e., the system can reliably differentiate between a fall and other human activities. In this paper, we discuss the time-scale based signal analysis of the radar returns from a human target. Reliable features are extracted from the scalogram and are used for fall classifications. The classification results and the advantages of using a wavelet transform are discussed.

  16. Radar Target Recognition Using Bispectrum Correlation

    DTIC Science & Technology

    2007-06-01

    21 2. Inverse Synthetic Aperture Radar ...................................................22 3. Range Profiles...characteristics need to be stored. 2. Inverse Synthetic Aperture Radar We often identify things based on pictures and Synthetic Aperture Radar (SAR) is an...By taking multiple discrete measurements while translating the radar , a larger effective aperture can be created. Inverse Synthetic Aperture Radar

  17. Exploitation of target shadows in synthetic aperture radar imagery for automatic target recognition

    NASA Astrophysics Data System (ADS)

    Saghri, John A.; DeKelaita, Andrew

    2006-08-01

    The utility of target shadows for automatic target recognition (ATR) in synthetic aperture radar (SAR) imagery is investigated. Although target shadow, when available, is not a powerful target discriminating feature, it can effectively increase the overall accuracy of the target classification when it is combined with other target discriminating features such as peaks, edges, and corners. A second and more important utility of target shadow is that it can be used to identify the target pose. Identification of the target pose before the recognition process reduces the number of reference images used for comparison/matching, i.e., the training sets, by at least fifty percent. Since implementation and the computation complexity of the pose detection algorithm is relatively simple, the proposed two-step process, i.e., pose detection followed matching, considerably reduces the complexity of the overall ATR system.

  18. Target & Propagation Models for the FINDER Radar

    NASA Technical Reports Server (NTRS)

    Cable, Vaughn; Lux, James; Haque, Salmon

    2013-01-01

    Finding persons still alive in piles of rubble following an earthquake, a severe storm, or other disaster is a difficult problem. JPL is currently developing a victim detection radar called FINDER (Finding Individuals in Emergency and Response). The subject of this paper is directed toward development of propagation & target models needed for simulation & testing of such a system. These models are both physical (real rubble piles) and numerical. Early results from the numerical modeling phase show spatial and temporal spreading characteristics when signals are passed through a randomly mixed rubble pile.

  19. Artifacts in Radar Imaging of Moving Targets

    DTIC Science & Technology

    2012-09-01

    coherent summing of random scatterers contributes to bright points on the imagery, which is known as speckle noise [3]. Figure 2. Radar...illustrate two commonly described schemes. A strip-map or scan mode of SAR imaging continually sweeps along a track and produces a strip of imagery. Here... track . Hence, the resolution for a broadside target is given by ([5], p. 22) 2 2( / ) 2 Stripmap D CR D         (3) where  is the carrier

  20. Target & Propagation Models for the FINDER Radar

    NASA Technical Reports Server (NTRS)

    Cable, Vaughn; Lux, James; Haque, Salmon

    2013-01-01

    Finding persons still alive in piles of rubble following an earthquake, a severe storm, or other disaster is a difficult problem. JPL is currently developing a victim detection radar called FINDER (Finding Individuals in Emergency and Response). The subject of this paper is directed toward development of propagation & target models needed for simulation & testing of such a system. These models are both physical (real rubble piles) and numerical. Early results from the numerical modeling phase show spatial and temporal spreading characteristics when signals are passed through a randomly mixed rubble pile.

  1. Automatic target classification of slow moving ground targets using space-time adaptive processing

    NASA Astrophysics Data System (ADS)

    Malas, John Alexander

    2002-04-01

    Air-to-ground surveillance radar technologies are increasingly being used by theater commanders to detect, track, and identify ground moving targets. New radar automatic target recognition (ATR) technologies are being developed to aid the pilot in assessing the ground combat picture. Most air-to-ground surveillance radars use Doppler filtering techniques to separate target returns from ground clutter. Unfortunately, Doppler filter techniques fall short on performance when target geometry and ground vehicle speed result in low line of sight velocities. New clutter filter techniques compatible with emerging advancements in wideband radar operation are needed to support surveillance modes of radar operation when targets enter this low velocity regime. In this context, space-time adaptive processing (STAP) in conjunction with other algorithms offers a class of signal processing that provide improved target detection, tracking, and classification in the presence of interference through the adaptive nulling of both ground clutter and/or jamming. Of particular interest is the ability of the radar to filter and process the complex target signature data needed to generate high range resolution (HRR) signature profiles on ground targets. A new approach is proposed which will allow air-to-ground target classification of slow moving vehicles in clutter. A wideband STAP approach for clutter suppression is developed which preserves the amplitude integrity of returns from multiple range bins consistent with the HRR ATR approach. The wideband STAP processor utilizes narrowband STAP principles to generate a series of adaptive sub-band filters. Each sub-band filter output is used to construct the complete filtered response of the ground target. The performance of this new approach is demonstrated and quantified through the implementation of a one dimensional template-based minimum mean squared error classifier. Successful minimum velocity identification is defined in terms of

  2. Review of the algorithms for radar single target tracking

    NASA Astrophysics Data System (ADS)

    Wei, Hao; Cai, Zong-ping; Tang, Bin; Yu, Ze-xiang

    2017-06-01

    The research of radar single target tracking is a hotspot in science all the time. This paper recommends the basic principle of radar single target tracking firstly. Then, the algorithms for radar single target tracking are classified into two segments, namely state estimation and tracking model. And the development of the algorithms is reviewed. It also analyses and comments the methods, features, merit and demerit in the application of these algorithms. At last, this paper introduces new progress of the research field.

  3. Correlating Flight Behavior and Radar Measurements for Species Based Classification of Bird Radar Echoes for Wind Energy Site Assessment

    NASA Astrophysics Data System (ADS)

    Werth, S. P.; Frasier, S. J.

    2015-12-01

    Wind energy is one of the fastest-growing segments of the world energy market, offering a clean and abundant source of electricity. However, wind energy facilities can have detrimental effects on wildlife, especially birds and bats. Monitoring systems based on marine navigation radar are often used to quantify migration near potential wind sites, but the ability to reliably distinguish between bats and different varieties of birds has not been practically achieved. This classification capability would enable wind site selection that protects more vulnerable species, such as bats and raptors. Flight behavior, such as wing beat frequency, changes in speed, or changes in orientation, are known to vary by species [1]. The ability to extract these properties from radar data could ultimately enable a species based classification scheme. In this work, we analyze the relationship between radar measurements and bird flight behavior in echoes from avifauna. During the 2014 fall migration season, the UMass dual polarized weather radar was used to collect low elevation observations of migrating birds as they traversed through a fixed antenna beam. The radar was run during the night time, in clear-air conditions. Data was coherently integrated, and detections of biological targets exceeding an SNR threshold were extracted. Detections without some dominant frequency content (i.e. clear periodicity, potentially the wing beat frequency) were removed from the sample in order to isolate observations suspected to contain a single species or bird. For the remaining detections, measurements including the polarimetric products and the Doppler spectrum were extracted at each time step over the duration of the observation. The periodic and time changing nature of some of these different measurements was found to have a strong correlation with flight behavior (i.e. flapping vs. gliding behavior). Assumptions about flight behavior and orientation were corroborated through scattering

  4. Distributed MIMO Radar for Imaging and High Resolution Target Localization

    DTIC Science & Technology

    2012-02-02

    28-2012 Final Report 04/15/2009 - 11/30/2011 Distributed MIMO Radar for Imaging and High Resolution Target Localization FA9550-09-1-0303 Alexander M...randomly placed sensors. MIMO radar, High-Resolution radar 19 Distributed MIMO Radar for Imaging and High Resolution Target Localization Air Force Office...configured with its antennas collocated [6] or distributed over an area [7, 8]. We refer to radio elements of a MIMO radar as nodes. Nodes may be equipped

  5. Data structures and target classification; Proceedings of the Meeting, Orlando, FL, Apr. 1, 2, 1991

    NASA Astrophysics Data System (ADS)

    Libby, Vibeke

    1991-08-01

    The present conference discusses topics in multisensor fusion and signal processing, data structures in distributed environments, computational methods and architectures, and automatic target recognition. Attention is given to the adaptive selection of sensors, multisensor imagery fusion based on target motion, multisensor imaging technology for airborne surveillance, optimal topology communications networks, scanning strategies for target detection, VLSI fuzzy-logic controller design, an optical pattern recognizer, radar-based target recognition techniques, and algorithms for radar clutter statistical classification.

  6. A preliminary investigation of bird classification by Doppler radar

    NASA Technical Reports Server (NTRS)

    Martinson, L. W.

    1973-01-01

    A preliminary study of the application of Doppler radar to the classification of birds is reported. The desirability for improvements in bird classification stems primarily from the hazards they present to jet aircraft in flight and in the vicinity of airports. A secondary need exists in the study of bird migration. The wing body and tail motion of a bird in flight reflect signals which, when analyzed properly present a signature of wing beat pattern which is unique for each bird species. Although the results of this investigation did not validate the feasibility of classifying bird species, they do indicate that a more thorough investigation is warranted. Certain gross characteristics such as wing beat rates, multiple bird patterns, and bird maneuverability, were indicated clearly in the results. Large birds with slow wing beat rates appear to be the most optimum subject for further study with the X-band Doppler radar used in this investigation.

  7. On the automatic classification of rain patterns on radar images

    NASA Astrophysics Data System (ADS)

    Pawlina Bonati, Apolonia

    The automation of the process of identification and classification of rain patterns on radar derived images is approached using some tools of digital image interpretation adapted to the specific application. The formal characterization of rain patterns and their partition in classes related to the type of precipitation is the main problem addressed in the paper, as the standard well established criteria for such classification are not defined. The digital maps of rain at horizontal plane derived from three-dimensional radar scans are processed by the interpretation package which identifies and classifies rain structures present on the map. The results generated by this package are illustrated in the paper and offered for discussion. The interpretation procedure is tailored for the radio-meteorology applications but the method is adaptable to other field requirements.

  8. Design of spectrally versatile forward-looking ground-penetrating radar for detection of concealed targets

    NASA Astrophysics Data System (ADS)

    Phelan, Brian R.; Ressler, Marc A.; Mazzaro, Gregory J.; Sherbondy, Kelly D.; Narayanan, Ram M.

    2013-05-01

    The design of high-resolution radars which can operate in theater involves a careful consideration of the radar's radiated spectrum. While a wide bandwidth yields better target detectability and classification, it can also interfere with other devices and/or violate federal and international communication laws. Under the Army Research Laboratory (ARL) Partnerships in Research Transition (PIRT) program, we are developing a Stepped-Frequency Radar (SFR) which allows for manipulation of the radiated spectrum, while still maintaining an effective ultra-wide bandwidth for achieving good range resolution. The SFR is a forward-looking, ultra-wideband (UWB) imaging radar capable of detecting concealed targets. This paper presents the research and analysis undertaken during the design of the SFR which will eventually complement an existing ARL system, the Synchronous Impulse REconstruction (SIRE) radar. The SFR is capable of excising prohibited frequency bands, while maintaining the down-range resolution capability of the original SIRE radar. The SFR has two transmit antennas and a 16-element receive antenna array, and this configuration achieves suitable cross-range resolution for target detection. The SFR, like the SIRE radar, is a vehicle mounted, forward-looking, ground penetrating radar (GPR) capable of using synthetic aperture radar (SAR) technology for the detection of subsurface targets via 3D imaging. Many contradicting design considerations are analyzed in this paper. The selection of system bandwidth, antenna types, number of antennas, frequency synthesizers, digitizers, receive amplifiers, wideband splitters, and many other components are critical to the design of the SFR. Leveraging commercial components and SIRE sub-systems were design factors offering an expedited time to the initial implementation of the radar while reducing overall costs. This SFR design will result in an ARL asset to support obscured target detection such as improvised explosive devices

  9. Classification of radar data by detecting and identifying spatial and temporal anomalies

    NASA Astrophysics Data System (ADS)

    Väilä, Minna; Venäläinen, Ilkka; Jylhä, Juha; Ruotsalainen, Marja; Perälä, Henna; Visa, Ari

    2010-04-01

    For some time, applying the theory of pattern recognition and classification to radar signal processing has been a topic of interest in the field of remote sensing. Efficient operation and target indication is often hindered by the signal background, which can have similar properties with the interesting signal. Because noise and clutter may constitute most part of the response of surveillance radar, aircraft and other interesting targets can be seen as anomalies in the data. We propose an algorithm for detecting these anomalies on a heterogeneous clutter background in each range-Doppler cell, the basic unit in the radar data defined by the resolution in range, angle and Doppler. The analysis is based on the time history of the response in a cell and its correlation to the spatial surroundings. If the newest time window of response in a resolution cell differs statistically from the time history of the cell, the cell is determined anomalous. Normal cells are classified as noise or different type of clutter based on their strength on each Doppler band. Anomalous cells are analyzed using a longer time window, which emulates a longer coherent illumination. Based on the decorrelation behavior of the response in the long time window, the anomalous cells are classified as clutter, an airplane or a helicopter. The algorithm is tested with both experimental and simulated radar data. The experimental radar data has been recorded in a forested landscape.

  10. Adaptive polarimetric sensing for optimum radar signature classification using a genetic search algorithm.

    PubMed

    Sadjadi, Firooz A

    2006-08-01

    An automated technique for adaptive radar polarimetric pattern classification is described. The approach is based on a genetic algorithm that uses a probabilistic pattern separation distance function and searches for those transmit and receive states of polarization sensing angles that optimize this function. Seven pattern separation distance functions--the Rayleigh quotient, the Bhattacharyya, divergence, Kolmogorov, Matusta, Kullback-Leibler distances, and the Bayesian probability of error--are used on real, fully polarimetric synthetic aperture radar target signatures. Each of these signatures is represented as functions of transmit and receive polarization ellipticity angles and the angle of polarization ellipse. The results indicate that, based on the majority of the distance functions used, there is a unique set of state of polarization angles whose use will lead to improved classification performance.

  11. Moving target detection for frequency agility radar by sparse reconstruction

    NASA Astrophysics Data System (ADS)

    Quan, Yinghui; Li, YaChao; Wu, Yaojun; Ran, Lei; Xing, Mengdao; Liu, Mengqi

    2016-09-01

    Frequency agility radar, with randomly varied carrier frequency from pulse to pulse, exhibits superior performance compared to the conventional fixed carrier frequency pulse-Doppler radar against the electromagnetic interference. A novel moving target detection (MTD) method is proposed for the estimation of the target's velocity of frequency agility radar based on pulses within a coherent processing interval by using sparse reconstruction. Hardware implementation of orthogonal matching pursuit algorithm is executed on Xilinx Virtex-7 Field Programmable Gata Array (FPGA) to perform sparse optimization. Finally, a series of experiments are performed to evaluate the performance of proposed MTD method for frequency agility radar systems.

  12. Moving target detection for frequency agility radar by sparse reconstruction.

    PubMed

    Quan, Yinghui; Li, YaChao; Wu, Yaojun; Ran, Lei; Xing, Mengdao; Liu, Mengqi

    2016-09-01

    Frequency agility radar, with randomly varied carrier frequency from pulse to pulse, exhibits superior performance compared to the conventional fixed carrier frequency pulse-Doppler radar against the electromagnetic interference. A novel moving target detection (MTD) method is proposed for the estimation of the target's velocity of frequency agility radar based on pulses within a coherent processing interval by using sparse reconstruction. Hardware implementation of orthogonal matching pursuit algorithm is executed on Xilinx Virtex-7 Field Programmable Gata Array (FPGA) to perform sparse optimization. Finally, a series of experiments are performed to evaluate the performance of proposed MTD method for frequency agility radar systems.

  13. Autonomous radar pulse modulation classification using modulation components analysis

    NASA Astrophysics Data System (ADS)

    Wang, Pei; Qiu, Zhaoyang; Zhu, Jun; Tang, Bin

    2016-12-01

    An autonomous method for recognizing radar pulse modulations based on modulation components analysis is introduced in this paper. Unlike the conventional automatic modulation classification methods which extract modulation features based on a list of known patterns, this proposed method classifies modulations by the existence of basic modulation components including continuous frequency modulations, discrete frequency codes and discrete phase codes in an autonomous way. A feasible way to realize this method is using the features of abrupt changes in the instantaneous frequency rate curve which derived by the short-term general representation of phase derivative. This method is suitable not only for the basic radar modulations but also for complicated and hybrid modulations. The theoretical result and two experiments demonstrate the effectiveness of the proposed method.

  14. Radar target recognition using non-cooperative scatterer matching game

    NASA Astrophysics Data System (ADS)

    Jouny, Ismail

    2012-05-01

    This paper utilizes game-theoretic principles in the automatic recognition of unknown radar targets. This study uses a non-cooperative matching game where pure strategies are associated with specific items to be matched, and agreement between possible hypotheses represents the payoff gained when playing a certain strategy against an opponent who is playing another strategy. The target recognition approach attempts to match scattering centers of an unknown target with those of library targets as competing strategies. The algorithm is tested using real radar data representing scattering from commercial aircraft models. Radar data of library targets at various azimuth positions are matched against an unknown radar target signature at a specific aspect angle. Computer simulations provide an estimate of the error rates in scenarios of additive Gaussian noise corrupting target signatures.

  15. Polarimetric Monopulse Radar Scattering Measurements of Targets at 95 GHz

    DTIC Science & Technology

    1991-09-01

    ARRAY USED FOR CALIBRATIONS Reflector Range to No. Reflector Type RCS(dBsm) Radar (m) I Wihe𔃻 (,15) 20 99 2 Dihedral 23 119 3 Grldded trihedral 14 139...hand circu- target azimuth angles to allow computation of lar polarization (RHCP) or left-hand circular rader cross section (RCS) polar plots, high...this report describes the polarization. basic characteristics of the radar and Section 3 contains a discussion of the procedures used for The radar has

  16. Convolutional neural networks for synthetic aperture radar classification

    NASA Astrophysics Data System (ADS)

    Profeta, Andrew; Rodriguez, Andres; Clouse, H. Scott

    2016-05-01

    For electro-optical object recognition, convolutional neural networks (CNNs) are the state-of-the-art. For large datasets, CNNs are able to learn meaningful features used for classification. However, their application to synthetic aperture radar (SAR) has been limited. In this work we experimented with various CNN architectures on the MSTAR SAR dataset. As the input to the CNN we used the magnitude and phase (2 channels) of the SAR imagery. We used the deep learning toolboxes CAFFE and Torch7. Our results show that we can achieve 93% accuracy on the MSTAR dataset using CNNs.

  17. Tracking moving radar targets with parallel, velocity-tuned filters

    DOEpatents

    Bickel, Douglas L.; Harmony, David W.; Bielek, Timothy P.; Hollowell, Jeff A.; Murray, Margaret S.; Martinez, Ana

    2013-04-30

    Radar data associated with radar illumination of a movable target is processed to monitor motion of the target. A plurality of filter operations are performed in parallel on the radar data so that each filter operation produces target image information. The filter operations are defined to have respectively corresponding velocity ranges that differ from one another. The target image information produced by one of the filter operations represents the target more accurately than the target image information produced by the remainder of the filter operations when a current velocity of the target is within the velocity range associated with the one filter operation. In response to the current velocity of the target being within the velocity range associated with the one filter operation, motion of the target is tracked based on the target image information produced by the one filter operation.

  18. Waveform design for cognitive radar: target detection in heavy clutter

    NASA Astrophysics Data System (ADS)

    Kirk, Benjamin H.; Narayanan, Ram M.; Martone, Anthony F.; Sherbondy, Kelly D.

    2016-05-01

    In many applications of radar systems, detection of targets in environments with heavy clutter and interference can be difficult. It is desired that a radar system should detect targets at a further range as well as be able to detect these targets with very few false positive or negative readings. In a cognitive radar system, there are ways that these negative effects can be mitigated and target detection can be significantly improved. An important metric to focus on for increasing target detectability is the signal-to-clutter ratio (SCR). Cognitive radar offers solutions to issues such as this with the use of a priori knowledge of targets and environments as well as real time adaptations. A feature of cognitive radar that is of interest is the ability to adapt and optimize transmitted waveforms to a given situation. A database is used to hold a priori and dynamic knowledge of the operational environment and targets to be detected, such as clutter characteristics and target radar cross-section (RCS) estimations. Assuming this knowledge is available or can be estimated in real-time, the transmitted waveform can be tailored using methods such as transmission of a spectrum corresponding to the target-to-clutter ratio (TCR). These methods provide significant improvement in distinguishing targets from clutter or interference.

  19. Model Order Selection Rules for Covariance Structure Classification in Radar

    NASA Astrophysics Data System (ADS)

    Carotenuto, Vincenzo; De Maio, Antonio; Orlando, Danilo; Stoica, Petre

    2017-10-01

    The adaptive classification of the interference covariance matrix structure for radar signal processing applications is addressed in this paper. This represents a key issue because many detection architectures are synthesized assuming a specific covariance structure which may not necessarily coincide with the actual one due to the joint action of the system and environment uncertainties. The considered classification problem is cast in terms of a multiple hypotheses test with some nested alternatives and the theory of Model Order Selection (MOS) is exploited to devise suitable decision rules. Several MOS techniques, such as the Akaike, Takeuchi, and Bayesian information criteria are adopted and the corresponding merits and drawbacks are discussed. At the analysis stage, illustrating examples for the probability of correct model selection are presented showing the effectiveness of the proposed rules.

  20. Characteristics and optimization of radar target with plasma cover

    NASA Astrophysics Data System (ADS)

    Yang, Ying-ying; Zhao, Wei-fang; Wang, Wen-ting; Yi, Xiao-jing; Ji, Jun-wen; Lin, Xue-chun

    2013-09-01

    In this paper, we investigated the characteristic of radar target, the spherical and the pyramidal missile warheads, and compared the RCS and performance of the targets with and without the cover of the plasma metamaterials. Numerical simulation is obtained by the numerical calculation Finite-difference time-domain method (FDTD). The parameters of plasmonic structures as a metamaterial cloak was designed and optimized. The relationship between the parameters of the cloak and the corresponding electromagnetic characteristic of the target are analyzed by the simulation and discussion in broadband radar signals. After optimization, the plasma cover could attenuate 40 dBsm of the radar cross section (RCS) of the targets maximally. The result shows that the anomalous phenomenon of cloaking and stealth effects induced by plasma materials for the radar target, which might have potential application of military affairs.

  1. Hydrometeor classification from polarimetric radar measurements: a clustering approach

    NASA Astrophysics Data System (ADS)

    Grazioli, Jacopo; Tuia, Devis; Berne, Alexis

    2015-04-01

    Hydrometeor classification is the process that aims at identifying the dominant type of hydrometeor (e.g. rain, hail, snow aggregates, hail, graupel, ice crystals) in a domain covered by a polarimetric weather radar during precipitation. The techniques documented in the literature are mostly based on numerical simulations and fuzzy logic. This involves the arbitrary selection of a set of hydrometeor classes and the numerical simulation of theoretical radar observations associated to each class. The information derived from the simulation is then applied to actual radar measurements by means of fuzzy logic input-output association. This approach has some limitations: the number and type of the hydrometeor categories undergoing identification is selected arbitrarily and the scattering simulations are based on constraining assumptions, especially in case of solid hydrometeors. Furthermore, in presence of noise and uncertainties, it is not guaranteed that the selected hydrometeor classes can be effectively identified in actual observations. In the present work we propose a different starting point for the classification task, which is based on observations instead of numerical simulations. We provide criteria for the selection of the number of hydrometeor classes that can be identified, by looking at how polarimetric observations collected over different precipitation events form clusters in the multi-dimensional space of the polarimetric variables. Two datasets, collected by an X-band weather radar, are employed in the study. The first dataset covers mountainous weather conditions (Swiss Alps), while the second includes Mediterranean orographic precipitation events collected during the special observation period (SOP) 2012 of the HyMeX campaign. We employ an unsupervised hierarchical clustering method to group the observations into clusters and we introduce a spatial smoothness constraint for the groups, assuming that the hydrometeor type changes smoothly in space

  2. Classification and correction of the radar bright band with polarimetric radar

    NASA Astrophysics Data System (ADS)

    Hall, Will; Rico-Ramirez, Miguel; Kramer, Stefan

    2015-04-01

    The annular region of enhanced radar reflectivity, known as the Bright Band (BB), occurs when the radar beam intersects a layer of melting hydrometeors. Radar reflectivity is related to rainfall through a power law equation and so this enhanced region can lead to overestimations of rainfall by a factor of up to 5, so it is important to correct for this. The BB region can be identified by using several techniques including hydrometeor classification and freezing level forecasts from mesoscale meteorological models. Advances in dual-polarisation radar measurements and continued research in the field has led to increased accuracy in the ability to identify the melting snow region. A method proposed by Kitchen et al (1994), a form of which is currently used operationally in the UK, utilises idealised Vertical Profiles of Reflectivity (VPR) to correct for the BB enhancement. A simpler and more computationally efficient method involves the formation of an average VPR from multiple elevations for correction that can still cause a significant decrease in error (Vignal 2000). The purpose of this research is to evaluate a method that relies only on analysis of measurements from an operational C-band polarimetric radar without the need for computationally expensive models. Initial results show that LDR is a strong classifier of melting snow with a high Critical Success Index of 97% when compared to the other variables. An algorithm based on idealised VPRs resulted in the largest decrease in error when BB corrected scans are compared to rain gauges and to lower level scans with a reduction in RMSE of 61% for rain-rate measurements. References Kitchen, M., R. Brown, and A. G. Davies, 1994: Real-time correction of weather radar data for the effects of bright band, range and orographic growth in widespread precipitation. Q.J.R. Meteorol. Soc., 120, 1231-1254. Vignal, B. et al, 2000: Three methods to determine profiles of reflectivity from volumetric radar data to correct

  3. Automatic identification of bird targets with radar via patterns produced by wing flapping.

    PubMed

    Zaugg, Serge; Saporta, Gilbert; van Loon, Emiel; Schmaljohann, Heiko; Liechti, Felix

    2008-09-06

    Bird identification with radar is important for bird migration research, environmental impact assessments (e.g. wind farms), aircraft security and radar meteorology. In a study on bird migration, radar signals from birds, insects and ground clutter were recorded. Signals from birds show a typical pattern due to wing flapping. The data were labelled by experts into the four classes BIRD, INSECT, CLUTTER and UFO (unidentifiable signals). We present a classification algorithm aimed at automatic recognition of bird targets. Variables related to signal intensity and wing flapping pattern were extracted (via continuous wavelet transform). We used support vector classifiers to build predictive models. We estimated classification performance via cross validation on four datasets. When data from the same dataset were used for training and testing the classifier, the classification performance was extremely to moderately high. When data from one dataset were used for training and the three remaining datasets were used as test sets, the performance was lower but still extremely to moderately high. This shows that the method generalizes well across different locations or times. Our method provides a substantial gain of time when birds must be identified in large collections of radar signals and it represents the first substantial step in developing a real time bird identification radar system. We provide some guidelines and ideas for future research.

  4. Autonomous Time-Frequency Cropping and Feature-Extraction Algorithms for Classification of LPI Radar Modulations

    DTIC Science & Technology

    2006-06-01

    INTERCEPT ( LPI ) SIGNAL MODULATIONS In this chapter nine LPI radar modulations are described: FMCW , Frank, P1, P2, P3, P4, T1(n), T2(n). Although not a LPI ...FREQUENCY CROPPING AND FEATURE-EXTRACTION ALGORITHMS FOR CLASSIFICATION OF LPI RADAR MODULATIONS by Eric R. Zilberman June 2006 Thesis...and Feature- Extraction Algorithms for Classification of LPI Radar Modulations 6. AUTHOR Eric R. Zilberman 5. FUNDING NUMBERS 7. PERFORMING

  5. Radar cross sections of standard and complex shape targets

    NASA Technical Reports Server (NTRS)

    Sohel, M. S.

    1974-01-01

    The theoretical, analytical, and experimental results are described for radar cross sections (RCS) of different-shaped targets. Various techniques for predicting RCS are given, and RCS of finite standard targets are presented. Techniques used to predict the RCS of complex targets are made, and the RCS complex shapes are provided.

  6. Iceberg and ship detection and classification in single, dual and quad polarized synthetic aperture radar

    NASA Astrophysics Data System (ADS)

    Howell, Carl

    Iceberg and ship identification in satellite synthetic aperture radar (SAR) data is an essential part of offering an operational iceberg surveillance program. Identification here refers to detection of ocean SAR targets and then classification of these targets as iceberg, ship, or unknown. Maximizing the detection and minimizing incorrect classification of iceberg and ship targets are required. Because coarser resolution satellite SAR data is at times not as intuitive as satellite optical data for manual human interpreted target classification, this process can be labor intensive, subjective, and error prone. Therefore, it is desired that an automated method for iceberg or ship identification be implemented. The methodology investigated here follows a well known standard in supervised pattern recognition, the maximum likelihood-quadratic discriminant function. The goal here in this thesis is to build class models from known iceberg and ship targets. Each class model is based on features that describe targets such as brightness, texture, and shape. Based on these descriptors as training input into the discriminant functions, future unknown targets can be compared with the class model for best fit. The best fit (or minimum distance) is used to assign class status for these unknown targets. One major consideration when using this type of pattern recognition approach is feature selection. Feature selection is based on the notion that some subset (subspace) of the descriptive metrics will lead to improved classification accuracy when comparing discriminant functions. Sequential forward selection and variants of exhaustive search algorithms are implemented and compared. RADARSAT-1, ENVSIAT AP (HH/HV), and EMISAR SAR iceberg and ship targets are used for algorithm training, feature selection, and performance estimation.

  7. Validation of the Electromagnetic Code FACETS for Numerical Simulation of Radar Target Images

    DTIC Science & Technology

    2009-12-01

    radar cross - section (stealth) targets. Radar images such as High Range Resolution profiles, and Synthetic Aperture Radar / Inverse Synthetic Aperture...target is a precisely designed and machined engineering test target containing standard radar reflector primitive shapes such as flat plates, dihedrals ...compute radar images of aircraft. The code was developed by Thales Defence Information Systems, UK. FACETS computes the radar cross - section and SAR image

  8. Hydrometeor classification using data mining techniques and polarimetric radar observations

    NASA Astrophysics Data System (ADS)

    Berne, A.; Grazioli, J.; Tuia, D.

    2013-12-01

    Hydrometeor classification aims at identifying the dominant type of hydrometeors in the sampling volume of a (polarimetric) weather radar. To do so, classical techniques make use of scattering simulations and fuzzy logic. A set of hydrometeor classes must be selected a-priori, and the scattering simulations are used to reproduce radar observations related with each class. Fuzzy logic is eventually used to link actually collected measurements with the simulated sets. With these methods, the number and type of hydrometeor categories undergoing identification is selected arbitrarily, the scattering simulations can be based on unreliable assumptions especially in case of solid particles and the effect of the noise on the measurements is not taken into account. In the present work, we develop a new approach to the classification problem, based on observations instead of scattering simulations. The goal is to provide objective criteria in the selection of the number of hydrometeor classes that can be reliably identified, by looking at how polarimetric observations collected over a set of different precipitation events form clusters in the multi-dimensional space of the polarimetric variables. Additional information is given by the spatial smoothness of the classified fields and by the altitude with respect to the zero degree level. Two polarimetric datasets, collected by an X-band radar are employed in this study. The two datasets cover weather conditions ranging from alpine precipitation collected in the Swiss Alps to Mediterranean orographic events, collected during the special observation period (SOP) 2012 of the HyMeX campaign. The optimal number of clusters is iteratively determined as a trade-off between the spatial smoothness of the classified domains and the complexity of the partitions , using an unsupervised clustering technique based on a correlation metrics. Eight clusters have been identified, 3 of them associated with liquid precipitation, 4 with solid

  9. Necessity to adapt land use and land cover classification systems to readily accept radar data

    NASA Technical Reports Server (NTRS)

    Drake, B.

    1977-01-01

    A hierarchial, four level, standardized system for classifying land use/land cover primarily from remote-sensor data (USGS system) is described. The USGS system was developed for nonmicrowave imaging sensors such as camera systems and line scanners. The USGS system is not compatible with the land use/land cover classifications at different levels that can be made from radar imagery, and particularly from synthetic-aperture radar (SAR) imagery. The use of radar imagery for classifying land use/land cover at different levels is discussed, and a possible revision of the USGS system to more readily accept land use/land cover classifications from radar imagery is proposed.

  10. Analysis of spatially mismatched imagery for synthetic aperture radar ATR classification

    NASA Astrophysics Data System (ADS)

    Rupp, Chad T.; Halversen, Shawn D.; Montagnino, Lee J.; Hebert, Christina L.; Young, Matthew T.; Cassabaum, Mary L.; Ku, Neilson

    2008-04-01

    Template-based classification algorithms used with synthetic aperture radar (SAR) automatic target recognition (ATR) degrade in performance when used with spatially mismatched imagery. The degradation, caused by a spatial mismatch between the template and image, is analyzed to show acceptable tolerances for SAR systems. The mismatch between the image and template is achieved by resampling the test imagery to different pixel spacings. A consistent SAR dataset is used to examine pixel spacings between 0.1069 and 0.2539 meters with a nominal spacing of 0.2021 meters. Performance degradation is observed as the pixel spacing is adjusted, Small amounts of variation in the pixel spacing cause little change in performance and allow design engineers to set reliable tolerances. Alternatively, the results show that using templates and images collected from slightly different sensor platforms is a very real possibility with the ability to predict the classification performance.

  11. Micro-doppler radar classification of human motions under various training scenarios

    NASA Astrophysics Data System (ADS)

    Fairchild, Dustin P.; Narayanan, Ram M.

    2013-05-01

    The identification and classification of human motions has become a popular area of research due to its broad range of applications. Knowledge of a person's movements can be a useful tool in surveillance, security, military combat, search and rescue operations, and the medical fields. Classification of common stationary human movements has been performed under various scenarios for two different micro-Doppler radar systems: S-band radar and millimeter-wave (mm-wave) radar. Each radar system has been designed for a specific scenario. The S-band radar is intended for through-the-wall situations at close distances, whereas the mm-wave radar is designed for long distance applications and also for through light foliage. Here, the performance of these radars for different training scenarios is investigated. The S-band radar will be analyzed for classification without a wall barrier, through a brick wall, and also through a cinder block wall. The effect of a wall barrier on micro-Doppler signatures will be briefly discussed. The mm-wave radar will be analyzed for classification at distances of 30, 60, and 91 meters.

  12. Automated target recognition using passive radar and coordinated flight models

    NASA Astrophysics Data System (ADS)

    Ehrman, Lisa M.; Lanterman, Aaron D.

    2003-09-01

    Rather than emitting pulses, passive radar systems rely on illuminators of opportunity, such as TV and FM radio, to illuminate potential targets. These systems are particularly attractive since they allow receivers to operate without emitting energy, rendering them covert. Many existing passive radar systems estimate the locations and velocities of targets. This paper focuses on adding an automatic target recognition (ATR) component to such systems. Our approach to ATR compares the Radar Cross Section (RCS) of targets detected by a passive radar system to the simulated RCS of known targets. To make the comparison as accurate as possible, the received signal model accounts for aircraft position and orientation, propagation losses, and antenna gain patterns. The estimated positions become inputs for an algorithm that uses a coordinated flight model to compute probable aircraft orientation angles. The Fast Illinois Solver Code (FISC) simulates the RCS of several potential target classes as they execute the estimated maneuvers. The RCS is then scaled by the Advanced Refractive Effects Prediction System (AREPS) code to account for propagation losses that occur as functions of altitude and range. The Numerical Electromagnetic Code (NEC2) computes the antenna gain pattern, so that the RCS can be further scaled. The Rician model compares the RCS of the illuminated aircraft with those of the potential targets. This comparison results in target identification.

  13. Fading characteristics of panchromatic radar backscatter from selected agricultural targets

    NASA Technical Reports Server (NTRS)

    Bush, T. F.; Ulaby, F. T.

    1973-01-01

    An experiment was performed to empirically determine the fading characteristics of backscattered radar signals from four agricultural targets at 9 GHz. After a short review of the statistics of Rayleigh fading backscatter, the data processing method and results of the data are analyzed. Comparison with theory shows adequate agreement with the experimental results, provided of course, the targets are modeled in a correct manner.

  14. Radar Resource Management in a Dense Target Environment

    DTIC Science & Technology

    2014-03-01

    propagation factor [dimensionless] σo = Target radar cross section (RCS) [m2] R = Range to the target [m] ko = Boltzmann constant [1.38x10−23J/K] To...12.604825 Eberhart, R., & Kennedy, J. (1995). A new optimizer using particle swarm theory. Proceedings of the Sixth International Symposium on Micro Machine

  15. 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.

  16. Photometry of six radar target asteroids

    NASA Technical Reports Server (NTRS)

    Wisniewski, W. Z.

    1987-01-01

    Photoelectric photometry of six earth-approaching asteroids is presented. The selection criterion was that they were close enough in 1986 to be observed by radar. Rotation periods were obtained for 1986 DA, 3199, 3103, and 1983 RD. 1986 JK and 1986 RA showed no detectable brightness variations during the monitoring time on several nights each, and therefore were either seen pole-on or have long rotation periods. Asteroids 1986 JK and 1986 RA are of taxonomic class C, 1986 DA and 3103 of class X, 1983 RD of class Q, and only 3199 of the class S that was previously believed to be predominant among earth-approaching asteroids.

  17. Unsupervised classification of scattering behavior using radar polarimetry data

    NASA Technical Reports Server (NTRS)

    Van Zyl, Jakob J.

    1989-01-01

    The use of an imaging radar polarimeter data for unsupervised classification of scattering behavior is described by comparing the polarization properties of each pixel in a image to that of simple classes of scattering such as even number of reflections, odd number of reflections, and diffuse scattering. For example, when this algorithm is applied to data acquired over the San Francisco Bay area in California, it classifies scattering by the ocean as being similar to that predicted by the class of odd number of reflections, scattering by the urban area as being similar to that predicted by the class of even number of reflections, and scattering by the Golden Gate Park as being similar to that predicted by the diffuse scattering class. It also classifies the scattering by a lighthouse in the ocean and boats on the ocean surface as being similar to that predicted by the even number of reflections class, making it easy to identify these objects against the background of the surrounding ocean. The algorithm is also applied to forested areas and shows that scattering from clear-cut areas and agricultural fields is mostly similar to that predicted by the odd number of reflections class, while the scattering from tree-covered areas generally is classified as being a mixture of pixels exhibiting the characteristics of all three classes, although each pixel is identified with only a single class.

  18. Classification of impulse radar waveforms using neural networks.

    PubMed

    Vrckovnik, G; Chung, T; Carter, C R

    1994-03-01

    In this paper, it is demonstrated that multilayer neural networks, trained with the backpropagation algorithm and radial basis functions, can classify impulse radar waveforms from three different asphalt-covered bridge decks, each with its own structure. It might be thought that the thickness of asphalt and the depth of concrete over the reinforcing bars would be nearly constant for any one bridge deck; however in practice this is not the case. There are often significant changes in the thickness of the asphalt and the cover over reinforcement. Furthermore, a certain amount of damage to the concrete caused by severe winter climate often produces a random variation in the reflected waveforms obtained from different locations. These factors lead to a significant number of combinations of waveforms that can be obtained from any given structural type of deck. The classification accuracies achieved ranged between 89.9% and 100%. The accuracies achieved after using principal components analysis to reduce the dimensionality of the input data ranged between 95.6% and 100%.

  19. Polarimetric monopulse radar scattering measurements of targets at 95 GHz

    NASA Astrophysics Data System (ADS)

    Wellman, R. J.; Nemarich, J.; Dropkin, H.; Hutchins, D. R.; Silvious, J. L.; Wikner, D. A.

    1991-09-01

    This paper describes a 95-GHz polarimetric monopulse instrumentation radar and selected scattering measurement results for an armored vehicle. The radar is all-solid-state, coherent, frequency steppable over a 640-MHz bandwidth, and completely polarimetric for linearly or circularly polarized radiation. Details of the methods used to perform the amplitude and phase calibrations and the effectiveness of polarization distortion matrix corrections are included in the paper. Measurements made with the radar of various vehicles on a turntable have allowed quasi-three-dimensional polarimetric ISAR images of the targets to be generated. Sample images for an infantry combat vehicle are presented together with high-resolution range profiles of the target for all monopulse channels.

  20. Radar Polarimetric Techniques in Target Signature Characterisation.

    NASA Astrophysics Data System (ADS)

    Sampath, Venkatesh

    Les techniques polarimetriques servent a determiner les coefficients complexes de retrodiffusion des cibles radar pour toute combinaison de polarisations transmise et recue. Lorsque les champs electriques sont utilises, on doit considerer quatre coefficients en tout, regroupes dans une matrice appelee la matrice de retrodiffusion. Cette matrice contient beaucoup de renseignements sur la cible (en particulier sa symetrie, ses dimensions, la diposition et la separation de ses points brillants, etc). Sa connaissance est donc fondamentale et si chacun de ses coefficients peut etre calcule pour une combinaison donnee de polarisation, on peut reconstituer cette matrice et en faire ressortir toute l'information qu'elle contient sur l'objet en question. De plus, en disposant de techniques de polarimetrie, on peut retrouver cette matrice pour n'importe quelle combinaison de polarisation des antennes en transmission et reception.

  1. Wavelet-based rotationally invariant target classification

    NASA Astrophysics Data System (ADS)

    Franques, Victoria T.; Kerr, David A.

    1997-07-01

    In this paper, a novel approach to feature extraction for rotationally invariant object classification is proposed based directly on a discrete wavelet transformation. This form of feature extraction is equivalent to retaining information features while eliminating redundant features from images, which is a critical property when analyzing large, high dimensional images. Usually, researchers have resorted to a data pre-processing method to reduce the size of the feature space prior to classification. The proposed method employs statistical features extracted directly from the wavelet coefficients generated from a three-level subband decomposition system using a set of orthogonal and regular Quadrature Mirror Filters. This algorithm has two desirable properties: (1) It reduces the number of dimensions of the feature space necessary to achieve the same classification accuracy as in the original space for a given pattern recognition problem; (2) Regardless of the target orientation, the algorithm can perform classification with low error rates. Furthermore, the filters used have performed well in the image compression regime, but they have not been applied to applications in target classification which will be demonstrated in this paper. The results of several classification experiments on variously oriented samples of the visible wavelength targets will be presented.

  2. Automatic ship classification system for inverse synthetic aperture radar (ISAR) imagery

    NASA Astrophysics Data System (ADS)

    Menon, Murali M.

    1995-04-01

    The U.S. Navy has been interested in applying neural network processing architectures to automatically determine the naval class of ships from an inverse synthetic aperture radar (ISAR) on-board an airborne surveillance platform. Currently an operator identifies the target based on an ISAR display. The emergence of the littoral warfare scenario, coupled with the addition of multiple sensors on the platform, threatens to impair the ability of the operator to identify and track targets in a timely manner. Thus, on-board automation is quickly becoming a necessity. Over the past four years the Opto-Radar System Group at MIT Lincoln Laboratory has developed and fielded a neural network based automatic ship classification (ASC) system for ISAR imagery. This system utilizes imagery from the APS-137 ISAR. Previous related work with ASC systems processed either simulated or real ISAR imagery under highly controlled conditions. The focus of this work was to develop a ship classification system capability of providing real-time identification from imagery acquired during an actual mission. The ship classification system described in this report uses both neural network and conventional processing techniques to determine the naval class of a ship from a range- Doppler (ISAR) image. The `learning' capability of the neural network classifier allows a single naval class to be distributed across many categories such that a degree of invariance to ship motion is developed. The ASC system was evaluated on 30 ship class database that had also been used for an operational readiness evaluation of ISAR crews. The results of the evaluation indicate that the ASC system has a performance level comparable to ISAR operators and typically provides a significant improvement in throughput.

  3. 5. Photocopy of photograph showing target tracking radar from 'Procedures ...

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

    5. Photocopy of photograph showing target tracking radar from 'Procedures and Drills for the NIKE Hercules Missile Battery,' Department of the Army Field Manual, FM-44-82 from Institute for Military History, Carlisle Barracks, Carlisle, PA, 1959 - NIKE Missile Battery PR-79, East Windsor Road south of State Route 101, Foster, Providence County, RI

  4. Coherent Multilook Radar Detection for Targets in Pareto Distributed Clutter

    DTIC Science & Technology

    2012-01-01

    measurements, for maritime high resolution radar returns. Using the theory of spherically invariant random processes, the Neyman -Pearson optimal...allows the determination of detection decision rules. The Pareto distri- bution is put into this framework, and the Neyman -Pearson detector is specified...6 3 Neyman -Pearson Detectors 7 3.1 Case of a Completely Known Target . . . . . . . . . . . . . . . . . . . . . 8 3.2

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

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaowen; Wang, Kaizhi; Liu, Xingzhao

    2017-01-01

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

  6. Birds and insects as radar targets - A review

    NASA Technical Reports Server (NTRS)

    Vaughn, C. R.

    1985-01-01

    A review of radar cross-section measurements of birds and insects is presented. A brief discussion of some possible theoretical models is also given and comparisons made with the measurements. The comparisons suggest that most targets are, at present, better modeled by a prolate spheroid having a length-to-width ratio between 3 and 10 than by the often used equivalent weight water sphere. In addition, many targets observed with linear horizontal polarization have maximum cross sections much better estimated by a resonant half-wave dipole than by a water sphere. Also considered are birds and insects in the aggregate as a local radar 'clutter' source. Order-of-magnitude estimates are given for many reasonable target number densities. These estimates are then used to predict X-band volume reflectivities. Other topics that are of interest to the radar engineer are discussed, including the doppler bandwidth due to the internal motions of a single bird, the radar cross-section probability densities of single birds and insects, the variability of the functional form of the probability density functions, and the Fourier spectra of single birds and insects.

  7. Birds and insects as radar targets - A review

    NASA Technical Reports Server (NTRS)

    Vaughn, C. R.

    1985-01-01

    A review of radar cross-section measurements of birds and insects is presented. A brief discussion of some possible theoretical models is also given and comparisons made with the measurements. The comparisons suggest that most targets are, at present, better modeled by a prolate spheroid having a length-to-width ratio between 3 and 10 than by the often used equivalent weight water sphere. In addition, many targets observed with linear horizontal polarization have maximum cross sections much better estimated by a resonant half-wave dipole than by a water sphere. Also considered are birds and insects in the aggregate as a local radar 'clutter' source. Order-of-magnitude estimates are given for many reasonable target number densities. These estimates are then used to predict X-band volume reflectivities. Other topics that are of interest to the radar engineer are discussed, including the doppler bandwidth due to the internal motions of a single bird, the radar cross-section probability densities of single birds and insects, the variability of the functional form of the probability density functions, and the Fourier spectra of single birds and insects.

  8. An image-based approach for classification of human micro-doppler radar signatures

    NASA Astrophysics Data System (ADS)

    Tivive, Fok Hing Chi; Phung, Son Lam; Bouzerdoum, Abdesselam

    2013-05-01

    With the advances in radar technology, there is an increasing interest in automatic radar-based human gait identification. This is because radar signals can penetrate through most dielectric materials. In this paper, an image-based approach is proposed for classifying human micro-Doppler radar signatures. The time-varying radar signal is first converted into a time-frequency representation, which is then cast as a two-dimensional image. A descriptor is developed to extract micro-Doppler features from local time-frequency patches centered along the torso Doppler frequency. Experimental results based on real data collected from a 24-GHz Doppler radar showed that the proposed approach achieves promising classification performance.

  9. Detection and identification of human targets in radar data

    NASA Astrophysics Data System (ADS)

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

    2007-04-01

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

  10. Minimum acquisition time detection. [of radar targets

    NASA Technical Reports Server (NTRS)

    Brock, H. I.; Hung, J. C.

    1975-01-01

    Two different methods of target detection when the return signal is contaminated with noise are discussed and compared. The first method uses Neyman-Pearson detection philosophy and selects the threshold level to give a desired false alarm probability. The maximum probability of false alarm is constrained by the target cross scan velocity component. The second method (minimum acquisition time detection), which is similar to the ideal observer, selects the threshold level to minimize the expected target acquisition time. The probabilities of false alarm and missed detection are selected so that the errors produced by these effects produce the minimum acquisition time. Three different scan techniques - linear, spiral and two-mode scan - are studied and compared.

  11. Concealed target detection using augmented reality with SIRE radar

    NASA Astrophysics Data System (ADS)

    Saponaro, Philip; Kambhamettu, Chandra; Ranney, Kenneth; Sullivan, Anders

    2013-05-01

    The Synchronous Impulse Reconstruction (SIRE) forward-looking radar, developed by the U.S. Army Research Laboratory (ARL), can detect concealed targets using ultra-wideband synthetic aperture technology. The SIRE radar has been mounted on a Ford Expedition and combined with other sensors, including a pan/tilt/zoom camera, to test its capabilities of concealed target detection in a realistic environment. Augmented Reality (AR) can be used to combine the SIRE radar image with the live camera stream into one view, which provides the user with information that is quicker to assess and easier to understand than each separated. In this paper we present an AR system which utilizes a global positioning system (GPS) and inertial measurement unit (IMU) to overlay a SIRE radar image onto a live video stream. We describe a method for transforming 3D world points in the UTM coordinate system onto the video stream by calibrating for the intrinsic parameters of the camera. This calibration is performed offline to save computation time and achieve real time performance. Since the intrinsic parameters are affected by the zoom of the camera, we calibrate at eleven different zooms and interpolate. We show the results of a real time transformation of the SAR imagery onto the video stream. Finally, we quantify both the 2D error and 3D residue associated with our transformation and show that the amount of error is reasonable for our application.

  12. Radar Waveform Synthesis for Target Identification.

    DTIC Science & Technology

    1983-06-05

    presented elsewhere [6]. 6. Experiment A facility for the measurement of transient electromagentic waves scattered by various targets illuminated by short...or the excitation signal for the zero-mode response, allA n and Bn are set to be zero. For this case [dm ] will have non- trivial solutions only...duration, transient TEM waves has been improved and modified over the past year. The experimental arrangement is indicated in Fig. 9. A spherical TEM

  13. Active calibration target for bistatic radar cross-section measurements

    NASA Astrophysics Data System (ADS)

    Pienaar, M.; Odendaal, J. W.; Joubert, J.; Cilliers, J. E.; Smit, J. C.

    2016-05-01

    Either passive calibration targets are expensive and complex to manufacture or their bistatic radar cross section (RCS) levels are significantly lower than the monostatic RCS levels of targets such as spheres, dihedral, and trihedral corner reflectors. In this paper the performance of an active calibration target with relative high bistatic RCS values is illustrated as a reference target for bistatic RCS measurements. The reference target is simple to manufacture, operates over a wide frequency range, and can be configured to calibrate all four polarizations (VV, HH, HV, and VH). Bistatic RCS measurements of canonical targets, performed in a controlled environment, are calibrated with the reference target and the results are compared to simulated results using FEKO.

  14. External calibration of polarimetric radar images using distributed targets

    NASA Technical Reports Server (NTRS)

    Yueh, Simon H.; Nghiem, S. V.; Kwok, R.

    1992-01-01

    A new technique is presented for calibrating polarimetric synthetic aperture radar (SAR) images using only the responses from natural distributed targets. The model for polarimetric radars is assumed to be X = cRST where X is the measured scattering matrix corresponding to the target scattering matrix S distorted by the system matrices T and R (in general T does not equal R(sup t)). To allow for the polarimetric calibration using only distributed targets and corner reflectors, van Zyl assumed a reciprocal polarimetric radar model with T = R(sup t); when applied for JPL SAR data, a heuristic symmetrization procedure is used by POLCAL to compensate the phase difference between the measured HV and VH responses and then take the average of both. This heuristic approach causes some non-removable cross-polarization responses for corner reflectors, which can be avoided by a rigorous symmetrization method based on reciprocity. After the radar is made reciprocal, a new algorithm based on the responses from distributed targets with reflection symmetry is developed to estimate the cross-talk parameters. The new algorithm never experiences problems in convergence and is also found to converge faster than the existing routines implemented for POLCAL. When the new technique is implemented for the JPL polarimetric data, symmetrization and cross-talk removal are performed on a line-by-line (azimuth) basis. After the cross-talks are removed from the entire image, phase and amplitude calibrations are carried out by selecting distributed targets either with azimuthal symmetry along the looking direction or with some well-known volume and surface scattering mechanisms to estimate the relative phases and amplitude responses of the horizontal and vertical channels.

  15. Ultra wide band radar holographic imaging of subsurface targets

    SciTech Connect

    Collins, H.D.; Gribble, R.P.

    1993-08-01

    This report discusses ultra wide band (i.e., 60 ps impulse) radar holography which is a unique technique for imaging subsurface targets with extremely high lateral and depth resolution. The large frequency bandwidth, typically 100%, provides excellent depth resolution and the synthetic aperture optimum lateral resolution of one-half wavelength at the center pulse frequency. Radar impulse holography can simply be described as a multi-frequency detection and imaging technique where the target`s broadband time waveform signals are recorded over a defined aperture; decomposed into their discrete frequency components as single frequency holograms, and reconstructed into a composite image. Computer generated holograms are constructed for each frequency component in the 3-dB pulse bandwidth and plane wave angular spectrums computed to provide unique detection analysis with respect to target identification, etc. The hologram at each frequency component in the pulse can be thought of as a diffraction lens for each reflecting point on the target. A complex target consists, of a multitude of points, and the recorded hologram becomes the superposition of these individual diffraction lens. It is a unique diffraction pattern capable of defining the target`s image and scattering characteristics in the near- and far-field.

  16. Passive synthetic aperture radar imaging of ground moving targets

    NASA Astrophysics Data System (ADS)

    Wacks, Steven; Yazici, Birsen

    2012-05-01

    In this paper we present a method for imaging ground moving targets using passive synthetic aperture radar. A passive radar imaging system uses small, mobile receivers that do not radiate any energy. For these reasons, passive imaging systems result in signicant cost, manufacturing, and stealth advantages. The received signals are obtained by multiple airborne receivers collecting scattered waves due to illuminating sources of opportunity such as commercial television, radio, and cell phone towers. We describe a novel forward model and a corresponding ltered-backprojection type image reconstruction method combined with entropy optimization. Our method determines the location and velocity of multiple targets moving at dierent velocities. Furthermore, it can accommodate arbitrary imaging geometries. we present numerical simulations to verify the imaging method.

  17. Hierarchical classification of dynamically varying radar pulse repetition interval modulation patterns.

    PubMed

    Kauppi, Jukka-Pekka; Martikainen, Kalle; Ruotsalainen, Ulla

    2010-12-01

    The central purpose of passive signal intercept receivers is to perform automatic categorization of unknown radar signals. Currently, there is an urgent need to develop intelligent classification algorithms for these devices due to emerging complexity of radar waveforms. Especially multifunction radars (MFRs) capable of performing several simultaneous tasks by utilizing complex, dynamically varying scheduled waveforms are a major challenge for automatic pattern classification systems. To assist recognition of complex radar emissions in modern intercept receivers, we have developed a novel method to recognize dynamically varying pulse repetition interval (PRI) modulation patterns emitted by MFRs. We use robust feature extraction and classifier design techniques to assist recognition in unpredictable real-world signal environments. We classify received pulse trains hierarchically which allows unambiguous detection of the subpatterns using a sliding window. Accuracy, robustness and reliability of the technique are demonstrated with extensive simulations using both static and dynamically varying PRI modulation patterns.

  18. Radar micro-Doppler based human activity classification for indoor and outdoor environments

    NASA Astrophysics Data System (ADS)

    Zenaldin, Matthew; Narayanan, Ram M.

    2016-05-01

    This paper presents the results of our experimental investigation into how different environments impact the classification of human motion using radar micro-Doppler (MD) signatures. The environments studied include free space, through-thewall, leaf tree foliage, and needle tree foliage. Results on presented on classification of the following three motions: crawling, walking, and jogging. The classification task was designed how to best separate these movements. The human motion data were acquired using a monostatic coherent Doppler radar operating in the C-band at 6.5 GHz from a total of six human subjects. The received signals were analyzed in the time-frequency domain using the Short-time Fourier Transform (STFT) which was used for feature extraction. Classification was performed using a Support Vector Machine (SVM) using a Radial Basis Function (RBF). Classification accuracies in the range 80-90% were achieved to separate the three movements mentioned.

  19. Improving crop classification through attention to the timing of airborne radar acquisitions

    NASA Technical Reports Server (NTRS)

    Brisco, B.; Ulaby, F. T.; Protz, R.

    1984-01-01

    Radar remote sensors may provide valuable input to crop classification procedures because of (1) their independence of weather conditions and solar illumination, and (2) their ability to respond to differences in crop type. Manual classification of multidate synthetic aperture radar (SAR) imagery resulted in an overall accuracy of 83 percent for corn, forest, grain, and 'other' cover types. Forests and corn fields were identified with accuracies approaching or exceeding 90 percent. Grain fields and 'other' fields were often confused with each other, resulting in classification accuracies of 51 and 66 percent, respectively. The 83 percent correct classification represents a 10 percent improvement when compared to similar SAR data for the same area collected at alternate time periods in 1978. These results demonstrate that improvements in crop classification accuracy can be achieved with SAR data by synchronizing data collection times with crop growth stages in order to maximize differences in the geometric and dielectric properties of the cover types of interest.

  20. Improving crop classification through attention to the timing of airborne radar acquisitions

    NASA Technical Reports Server (NTRS)

    Brisco, B.; Ulaby, F. T.; Protz, R.

    1984-01-01

    Radar remote sensors may provide valuable input to crop classification procedures because of (1) their independence of weather conditions and solar illumination, and (2) their ability to respond to differences in crop type. Manual classification of multidate synthetic aperture radar (SAR) imagery resulted in an overall accuracy of 83 percent for corn, forest, grain, and 'other' cover types. Forests and corn fields were identified with accuracies approaching or exceeding 90 percent. Grain fields and 'other' fields were often confused with each other, resulting in classification accuracies of 51 and 66 percent, respectively. The 83 percent correct classification represents a 10 percent improvement when compared to similar SAR data for the same area collected at alternate time periods in 1978. These results demonstrate that improvements in crop classification accuracy can be achieved with SAR data by synchronizing data collection times with crop growth stages in order to maximize differences in the geometric and dielectric properties of the cover types of interest.

  1. Objective Classification of Radar Profile Types, and Their Relationship to Lightning Occurrence

    NASA Technical Reports Server (NTRS)

    Boccippio, Dennis

    2003-01-01

    A cluster analysis technique is used to identify 16 "archetypal" vertical radar profile types from a large, globally representative sample of profiles from the TRMM Precipitation Radar. These include nine convective types (7 of these deep convective) and seven stratiform types (5 of these clearly glaciated). Radar profile classification provides an alternative to conventional deep convective storm metrics, such as 30 dBZ echo height, maximum reflectivity or VIL. As expected, the global frequency of occurrence of deep convective profile types matches satellite-observed total lightning production, including to very small scall local features. Each location's "mix" of profile types provides an objective description of the local convective spectrum, and in turn, is a first step in objectively classifying convective regimes. These classifiers are tested as inputs to a neural network which attempts to predict lightning occurrence based on radar-only storm observations, and performance is compared with networks using traditional radar metrics as inputs.

  2. Objective Classification of Radar Profile Types, and Their Relationship to Lightning Occurrence

    NASA Technical Reports Server (NTRS)

    Boccippio, Dennis

    2003-01-01

    A cluster analysis technique is used to identify 16 "archetypal" vertical radar profile types from a large, globally representative sample of profiles from the TRMM Precipitation Radar. These include nine convective types (7 of these deep convective) and seven stratiform types (5 of these clearly glaciated). Radar profile classification provides an alternative to conventional deep convective storm metrics, such as 30 dBZ echo height, maximum reflectivity or VIL. As expected, the global frequency of occurrence of deep convective profile types matches satellite-observed total lightning production, including to very small scall local features. Each location's "mix" of profile types provides an objective description of the local convective spectrum, and in turn, is a first step in objectively classifying convective regimes. These classifiers are tested as inputs to a neural network which attempts to predict lightning occurrence based on radar-only storm observations, and performance is compared with networks using traditional radar metrics as inputs.

  3. External calibration of polarimetric radars using point and distributed targets

    NASA Technical Reports Server (NTRS)

    Yueh, S. H.; Kong, J. A.; Shin, R. T.

    1991-01-01

    Polarimetric calibration algorithms using combinations of point targets and reciprocal distributed targets are developed. From the reciprocity relations of distributed targets, and equivalent point target response is derived. Then the problem of polarimetric calibration using two point targets and one distributed target reduces to that using three point targets, which has been previously solved. For calibration using one point target and one reciprocal distributed target, two cases are analyzed with the point target being a trihedral reflector or a polarimetric active radar calibrator (PARC). For both cases, the general solutions of the system distortion matrices are written as a product of a particular solution and a matrix with one free parameter. For the trihedral-reflector case, this free parameter is determined by assuming azimuthal symmetry for the distributed target. For the PARC case, knowledge of one ratio of two covariance matrix elements of the distributed target is required to solve for the free parameter. Numerical results are simulated to demonstrate the usefulness of the developed algorithms.

  4. Radar target imaging by time-domain inverse scattering

    NASA Astrophysics Data System (ADS)

    Morag, M.

    1981-03-01

    This thesis describes the study and development of a workable inverse scattering method for imaging and identification of radar targets. The space-time integral approach is used for iterative target shape reconstruction. Following an overview of transient electromagnetics, the integral equation is applied for thin-wire transient response computation. The analytical time domain integral equation is derived and solved numerically, for general conducting bodies of revolution. Finally the algorithm for an inverse scattering computer solution is derived and tested under simulation of physical environments.

  5. Shape-based recognition of targets in synthetic aperture radar images using elliptical Fourier descriptors

    NASA Astrophysics Data System (ADS)

    Nicoli, Louis P.; Anagnostopoulos, Georgios C.

    2008-04-01

    This paper primarily investigates the use of shape-based features by an Automatic Target Recognition (ATR) system to classify various types of targets in Synthetic Aperture Radar (SAR) images. In specific, shapes of target outlines are represented via Elliptical Fourier Descriptors (EFDs), which, in turn, are utilized as recognition features. According to the proposed ATR approach, a segmentation stage first isolates the target region from shadow and ground clutter via a sequence of fast thresholding and morphological operations. Next, a number of EFDs are computed that can sufficiently describe the salient characteristics of the target outline. Finally, a classification stage based on an ensemble of Support Vector Machines identifies the target with the appropriate class label. In order to experimentally illustrate the merit of the proposed approach, SAR intensity images from the well-known Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset were used as 10-class and 3-class recognition problems. Furthermore, comparisons were drawn in terms of classification performance and computational complexity to other successful methods discussed in the literature, such as template matching methods. The obtained results portray that only a very limited amount of EFDs are required to achieve recognition rates that are competitive to well-established approaches.

  6. Moving target imaging using ultrawideband synthetic aperture radar

    NASA Astrophysics Data System (ADS)

    Guo, Hanwei; Liang, Diannong; Wan, Yan; Huang, Xiaotao; Dong, Zhen

    2003-09-01

    Moving Target High Resolution Imaging of Foliage Penetrate Ultra-Wide Band Synthetic Aperture Radar (FOPEN UWB SAR) is of great significance for battlefield awareness of concealed target. Great range migration and strong clutter make moving target detection and imaging difficult, especially the Signal to Clutter Ration(SCR) some times is so low that the moving targets is invisible in FOPEN UWB SAR imagery. To improve SCR, the clean technique is used in range compressed data domain. The clean technique and data reconstruction help single channel of FOPEN UWB SAR suppress strong tree clutter and stationary target signal from region of interest. A new definition called General Key-Stone Transform is given, which can correct any order of range migration. FOPEN UWB SAR has long integrated time. The plane and target moving in long time lead to complex range migration. To obtain high resolution imagery of moving target, General Key-Stone transform are applied to remove the range migration and realize multiple moving target data segment. Both General Key-Stone Transform and Clean Technique are applied in real data processing of FOPEN UWB SAR. The result shows that multiple moving targets in the trees are clearly detected and high resolution imagery is formed.

  7. 3-D Imaging of Partly Concealed Targets by Laser Radar

    DTIC Science & Technology

    2005-10-01

    laser in the green wavelength region was used for illumination. 3-D Imaging of Partly Concealed Targets by Laser Radar 11 - 8 RTO-MP-SET-094...acknowledge Marie Carlsson and Ann Charlotte Gustavsson for their assistance in some of the experiments. 7.0 REFERENCES [1] U. Söderman, S. Ahlberg...SPIE Vol. 3707, pp. 432-448, USA, 1999. [14] D. Letalick, H. Larsson, M. Carlsson, and A.-C. Gustavsson , “Laser sensors for urban warfare,” FOI

  8. Crop classification using multidate/multifrequency radar data. [Colby, Kansas

    NASA Technical Reports Server (NTRS)

    Ulaby, F. T. (Principal Investigator); Shanmugam, K. S.; Narayanan, V.; Dobson, C.

    1981-01-01

    Both C- and L-band radar data acquired over a test site near Colby, Kansas during the summer of 1978 were used to identify three types of vegetation cover and bare soil. The effects of frequency, polarization, and the look angle on the overall accuracy of recognizing the four types of ground cover were analyzed. In addition, multidate data were used to study the improvement in recognition accuracy possible with the addition of temporal information. The soil moisture conditions had changed considerably during the temporal sequence of the data; hence, the effects of soil moisture on the ability to discriminate between cover types were also analyzed. The results provide useful information needed for selecting the parameters of a radar system for monitoring crops.

  9. Along Track Interferometry Synthetic Aperture Radar (ATI-SAR) Techniques for Ground Moving Target Detection

    DTIC Science & Technology

    2006-01-01

    DISTRIBUTION CODE 13. ABSTRACT (Maximum 200 Words) Conventional along track interferometric synthetic aperature radar , ATI-SAR, approaches can detect...House, Inc., Norwood, MA, 1995. [14] R. Bamler and P. Hartl, " Synthetic aperture radar interferometry," Inverse Problems, vol. 14, R1-R54, 1998. [15... SYNTHETIC APERTURE RADAR (ATI-SAR) TECHNIQUES FOR GROUND MOVING TARGET DETECTION Stiefvater Consultants

  10. Radar-target signatures from MMW-measurement platform

    NASA Astrophysics Data System (ADS)

    Inaebnit, Christian; John, Marc-Andre; Aulenbacher, Uwe

    2003-08-01

    Automatic target detection (ATR) depends on the surrounding clutter as well as on the target signatures. Swiss DoD has established a measurement-platform in the W-Band frequency frame to generate the necessary data's . The wavelength of the W-Band is extreme smaller than the target dimension and the footprint of the antenna does not illuminate the entire target. This have the result, that the actual echo-signal correlates strongly to the view angle. The signature of a target is so complex for any evaluation, that it is necessary to create a statistic model with virtual scatters. As an example this model can be integrated in simulations of smart ammunition effectiveness. With data of a statistical model it is possible to: 1. to evaluate the object according its RCS. 2. to create the necessary camouflage-precaution against radar-seekers and check there efficiency. 3. Detection probabilities of a target in different clutter conditions. 4. to identify strong reflectors and thereby reduce the RCS value of the target.

  11. Synthetic Aperture Radar Target Recognition with Feature Fusion Based on a Stacked Autoencoder.

    PubMed

    Kang, Miao; Ji, Kefeng; Leng, Xiangguang; Xing, Xiangwei; Zou, Huanxin

    2017-01-20

    Feature extraction is a crucial step for any automatic target recognition process, especially in the interpretation of synthetic aperture radar (SAR) imagery. In order to obtain distinctive features, this paper proposes a feature fusion algorithm for SAR target recognition based on a stacked autoencoder (SAE). The detailed procedure presented in this paper can be summarized as follows: firstly, 23 baseline features and Three-Patch Local Binary Pattern (TPLBP) features are extracted. These features can describe the global and local aspects of the image with less redundancy and more complementarity, providing richer information for feature fusion. Secondly, an effective feature fusion network is designed. Baseline and TPLBP features are cascaded and fed into a SAE. Then, with an unsupervised learning algorithm, the SAE is pre-trained by greedy layer-wise training method. Capable of feature expression, SAE makes the fused features more distinguishable. Finally, the model is fine-tuned by a softmax classifier and applied to the classification of targets. 10-class SAR targets based on Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset got a classification accuracy up to 95.43%, which verifies the effectiveness of the presented algorithm.

  12. Synthetic Aperture Radar Target Recognition with Feature Fusion Based on a Stacked Autoencoder

    PubMed Central

    Kang, Miao; Ji, Kefeng; Leng, Xiangguang; Xing, Xiangwei; Zou, Huanxin

    2017-01-01

    Feature extraction is a crucial step for any automatic target recognition process, especially in the interpretation of synthetic aperture radar (SAR) imagery. In order to obtain distinctive features, this paper proposes a feature fusion algorithm for SAR target recognition based on a stacked autoencoder (SAE). The detailed procedure presented in this paper can be summarized as follows: firstly, 23 baseline features and Three-Patch Local Binary Pattern (TPLBP) features are extracted. These features can describe the global and local aspects of the image with less redundancy and more complementarity, providing richer information for feature fusion. Secondly, an effective feature fusion network is designed. Baseline and TPLBP features are cascaded and fed into a SAE. Then, with an unsupervised learning algorithm, the SAE is pre-trained by greedy layer-wise training method. Capable of feature expression, SAE makes the fused features more distinguishable. Finally, the model is fine-tuned by a softmax classifier and applied to the classification of targets. 10-class SAR targets based on Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset got a classification accuracy up to 95.43%, which verifies the effectiveness of the presented algorithm. PMID:28117689

  13. Ultrawideband radar target discrimination utilizing an advanced feature set

    NASA Astrophysics Data System (ADS)

    Nguyen, Lam H.; Kapoor, Ravinder; Wong, David C.; Sichina, Jeffrey

    1998-09-01

    The Army Research Laboratory, as part of its mission-funded applied research program, has been evaluating the utility of a low-frequency, ultra wideband imaging radar to detect tactical vehicles concealed by foliage. Measurement programs conducted at Aberdeen Proving Grounds and elsewhere have yielded a significant and unique database of extremely wideband and (in some cases) fully polarimetric data. Prior work has concentrated on developing computationally efficient methods to quickly canvass large quantities of data to identify likely target occurrences--often called `prescreening.' This paper reviews recent findings from our phenomenology/detection efforts. Included is a reformulated prescreener that has been trained and tested against a significantly larger data set than was used in the prior work. Also discussed are initial efforts aimed at the discrimination of targets from the difficult clutter remaining after prescreening. Performance assessments are included that detail detection rates versus false alarm levels.

  14. Classification of radar jammer FM signals using a neural network

    NASA Astrophysics Data System (ADS)

    Mendoza, Ariadna; Soto, Alberto; Flores, Benjamin C.

    2017-05-01

    We propose an approach based on artificial Neural Networks (NN) to classify wideband radar jammer signals for more efficient use of countermeasures. A robust NN is be used to correctly differentiate Frequency-Modulated (FM) signals from bandlimited Additive White Gaussian Noise (AWGN). We compare the performance of the NN using the samples of the power spectrum versus the autocorrelation. Prior experiments showed that frequency-domain moments of the FM signal itself are better descriptors than time-domain moments. Using simulated wideband FM radar signals, we compute a set of N autocorrelation and spectra and feed them to the NN which has ten hidden layers. For training purposes, the autocorrelations or spectra sets are divided into three groups, 75% for training, 15% for validating and 15% for testing. For the power spectra set, we observe that a Signal to Noise Ratio (SNR) of 5dB allows the network to approach an average of 5% percent Probability of Error (PE). Training with the autocorrelation set yields comparable results. For an SNR of 5dB, the average PE reached an average of 0.3%. In both instances, the NN reaches zero percent PE at an SNR of 10dB.

  15. Activity monitoring and motion classification of the lizard Chamaeleo jacksonii using multiple Doppler radars.

    PubMed

    Singh, Aditya; Lee, Scott S K; Butler, Marguerite; Lubecke, Victor

    2012-01-01

    We describe a simple, non-contact and efficient tool for monitoring the natural activity of a small lizard (Chamaeleo jacksonii) to yield valuable information about their metabolic activity and energy expenditure. It allows monitoring in a non-confined laboratory environment and uses multiple Doppler radars operating at 10.525 GHz. We developed a classification algorithm that can differentiate between fidgeting and locomotion by processing the quadrature baseband signals from the radars. The results have been verified by visual inspection and indicate that the tool could also be used for automated monitoring of the activities of reptiles and other small animals.

  16. Activity Monitoring and Motion Classification of the Lizard Chamaeleo jacksonii Using Multiple Doppler Radars

    PubMed Central

    Singh, Aditya; Lee, Scott SK; Butler, Marguerite; Lubecke, Victor

    2016-01-01

    We describe a simple, non-contact and efficient tool for monitoring the natural activity of a small lizard (Chamaeleo jacksonii) to yield valuable information about their metabolic activity and energy expenditure. It allows monitoring in a non-confined laboratory environment and uses multiple Doppler radars operating at 10.525 GHz. We developed a classification algorithm that can differentiate between fidgeting and locomotion by processing the quadrature baseband signals from the radars. The results have been verified by visual inspection and indicate that the tool could also be used for automated monitoring of the activities of reptiles and other small animals. PMID:23366934

  17. Detection and tracking of human targets in indoor and urban environments using through-the-wall radar sensors

    NASA Astrophysics Data System (ADS)

    Radzicki, Vincent R.; Boutte, David; Taylor, Paul; Lee, Hua

    2017-05-01

    Radar based detection of human targets behind walls or in dense urban environments is an important technical challenge with many practical applications in security, defense, and disaster recovery. Radar reflections from a human can be orders of magnitude weaker than those from objects encountered in urban settings such as walls, cars, or possibly rubble after a disaster. Furthermore, these objects can act as secondary reflectors and produce multipath returns from a person. To mitigate these issues, processing of radar return data needs to be optimized for recognizing human motion features such as walking, running, or breathing. This paper presents a theoretical analysis on the modulation effects human motion has on the radar waveform and how high levels of multipath can distort these motion effects. From this analysis, an algorithm is designed and optimized for tracking human motion in heavily clutter environments. The tracking results will be used as the fundamental detection/classification tool to discriminate human targets from others by identifying human motion traits such as predictable walking patterns and periodicity in breathing rates. The theoretical formulations will be tested against simulation and measured data collected using a low power, portable see-through-the-wall radar system that could be practically deployed in real-world scenarios. Lastly, the performance of the algorithm is evaluated in a series of experiments where both a single person and multiple people are moving in an indoor, cluttered environment.

  18. Target classification algorithm based on feature aided tracking

    NASA Astrophysics Data System (ADS)

    Zhan, Ronghui; Zhang, Jun

    2013-03-01

    An effective target classification algorithm based on feature aided tracking (FAT) is proposed, using the length of target (target extent) as the classification information. To implement the algorithm, the Rao-Blackwellised unscented Kalman filter (RBUKF) is used to jointly estimate the kinematic state and target extent; meanwhile the joint probability data association (JPDA) algorithm is exploited to implement multi-target data association aided by target down-range extent. Simulation results under different condition show the presented algorithm is both accurate and robust, and it is suitable for the application of near spaced targets tracking and classification under the environment of dense clutters.

  19. Kernel linear representation: application to target recognition in synthetic aperture radar images

    NASA Astrophysics Data System (ADS)

    Dong, Ganggang; Wang, Na; Kuang, Gangyao; Zhang, Yinfa

    2014-01-01

    A method for target classification in synthetic aperture radar (SAR) images is proposed. The samples are first mapped into a high-dimensional feature space in which samples from the same class are assumed to span a linear subspace. Then, any new sample can be uniquely represented by the training samples within given constraint. The conventional methods suggest searching the sparest representations with ℓ1-norm (or ℓ) minimization constraint. However, these methods are computationally expensive due to optimizing nondifferential objective function. To improve the performance while reducing the computational consumption, a simple yet effective classification scheme called kernel linear representation (KLR) is presented. Different from the previous works, KLR limits the feasible set of representations with a much weaker constraint, ℓ-norm minimization. Since, KLR can be solved in closed form there is no need to perform the ℓ-minimization, and hence the calculation burden has been lessened. Meanwhile, the classification accuracy has been improved due to the relaxation of the constraint. Extensive experiments on a real SAR dataset demonstrate that the proposed method outperforms the kernel sparse models as well as the previous works performed on SAR target recognition.

  20. Determining human target facing orientation using bistatic radar micro-Doppler signals

    NASA Astrophysics Data System (ADS)

    Fairchild, Dustin P.; Narayanan, Ram M.

    2014-06-01

    Micro-Doppler radar signals can be used to separate moving human targets from stationary clutter and also to identify and classify human movements. Traditional micro-Doppler radar systems which use a single sensor, monostatic system, suffer from the drawback that only the radial component of the micro-Doppler signal will be observed by the radar operator. This reduces the sensitivity of human activity recognition if the movements are not directly towards or away with respect to the line-of-sight to the radar antenna. In this paper, we propose the use of two bistatic micro-Doppler sensors to overcome this limitation. By using multiple sensors, the orientation of oscillating targets with respect to the radar line-of-sight can be inferred, thereby providing additional information to the radar operator. This approach can be used to infer the facing direction of the human with respect to the radar beam.

  1. Detection of small, slow ground targets using Synthetic Aperture Radar

    NASA Technical Reports Server (NTRS)

    Chen, Curtis; Chapin, Elaine; Rosen, Paul

    2005-01-01

    Synthetic aperture radar (SAR) along-track interferometry (ATI) is a technique for sensing Earth-surface motion. The technique involves interferometrically combining data from two radar images acquired from phase centers separated along the platform flight track.

  2. Radar detection of buried targets in coastal environments

    NASA Astrophysics Data System (ADS)

    Brode, Chad M.; Narayanan, Ram M.

    2017-05-01

    Coastal soils offer a number of challenges in electromagnetic remote sensing applications. They are highly saline owing to their constant contact with salt water resulting in high values for the real and imaginary parts of their permittivity. Due to this fact, it is desirable to model these properties and determine how they will affect the detection and location of targets buried in coastal soil environments. We examined the propagation of a plane wave with three different incidence angles on a cubic perfect electric conductor (PEC) target contained within an semi-infinite dielectric material with the same properties as the soil. This response was then compared to that of a baseline target with no dielectric surrounding it and a dielectric mimicking dry sandy soil. The results show that the signal is both highly reflected at the surface of the wet coastal soil, and significantly attenuated as it propagates through the wet soil dielectric. The results of our modeling and simulation studies over a wide range of conditions (e.g. frequency, soil salinity, burial depth, etc.) are presented and trade-offs examined in order to develop a cognitive radar system for enhancing target detection and clutter suppression.

  3. Narrowband radar imaging for precessional targets with specular scattering

    NASA Astrophysics Data System (ADS)

    Liu, Yuling; Wei, Xizhang; Peng, Bo

    2016-10-01

    Narrowband radar imaging algorithms based on the micro-Doppler (m-D) characteristics of precessional targets will lose efficacy since specular scattering makes the spectrogram discontinuous and unrecognizable. Specular scattering occurs under the condition that the incident angle of wave is perpendicular to the target surface. To image the precessional target under specular scattering, we propose a narrowband imaging algorithm via complex-valued empirical-mode decomposition-time frequency distribution-general Radon transform (CEMD-TFD-GRT) after analyzing the m-D characteristics of specular scattering centers. The CEMD first decomposes the echo into several components according to their spectrums varying from high to low so that the Doppler spectrums suppressed by the specular scattering can be recognized. Then, TFD-GRT is used to extract the parameters of m-D curves from which the positions of scattering centers can be reconstructed. In addition, the computation complexity of CEMD-TFD-GRT is analyzed and the Cramer-Rao low bounds for the coordinates estimation are derived. The experiment results with anechoic chamber data demonstrate that the scattering centers of precessional targets can be imaged with the proposed algorithm even when specular scattering occurs. The noise influence on the proposed algorithm is also presented with the experiments.

  4. Detection and Classification of Low Probability of Intercept Radar Signals Using Parallel Filter Arrays and Higher Order Statistics

    DTIC Science & Technology

    2002-09-01

    Resulting Plots for Different LPI Radar Signals (1) FMCW Table 9 shows a FMCW signal with carrier frequency equal to 1 KHz, sampling frequency equal to...REPORT TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE: Detection and Classification of LPI Radar Signals using Parallel Filter...In order to detect LPI radar waveforms new signal processing techniques are required. This thesis first develops a MATLAB® toolbox to generate

  5. Hydrometeor classification through statistical clustering of polarimetric radar measurements: a semi-supervised approach

    NASA Astrophysics Data System (ADS)

    Besic, Nikola; Ventura, Jordi Figueras i.; Grazioli, Jacopo; Gabella, Marco; Germann, Urs; Berne, Alexis

    2016-09-01

    Polarimetric radar-based hydrometeor classification is the procedure of identifying different types of hydrometeors by exploiting polarimetric radar observations. The main drawback of the existing supervised classification methods, mostly based on fuzzy logic, is a significant dependency on a presumed electromagnetic behaviour of different hydrometeor types. Namely, the results of the classification largely rely upon the quality of scattering simulations. When it comes to the unsupervised approach, it lacks the constraints related to the hydrometeor microphysics. The idea of the proposed method is to compensate for these drawbacks by combining the two approaches in a way that microphysical hypotheses can, to a degree, adjust the content of the classes obtained statistically from the observations. This is done by means of an iterative approach, performed offline, which, in a statistical framework, examines clustered representative polarimetric observations by comparing them to the presumed polarimetric properties of each hydrometeor class. Aside from comparing, a routine alters the content of clusters by encouraging further statistical clustering in case of non-identification. By merging all identified clusters, the multi-dimensional polarimetric signatures of various hydrometeor types are obtained for each of the studied representative datasets, i.e. for each radar system of interest. These are depicted by sets of centroids which are then employed in operational labelling of different hydrometeors. The method has been applied on three C-band datasets, each acquired by different operational radar from the MeteoSwiss Rad4Alp network, as well as on two X-band datasets acquired by two research mobile radars. The results are discussed through a comparative analysis which includes a corresponding supervised and unsupervised approach, emphasising the operational potential of the proposed method.

  6. Detection of Metallic and Electronic Radar Targets by Acoustic Modulation of Electromagnetic Waves

    DTIC Science & Technology

    2017-07-01

    translational motion in the target, the electric -field intensity reflected by the target Erefl may be written as a sinusoid with a phase that is linearly...Rx radar receiver SCPI Standard Commands for Programmable Instruments Tx radar transmitter USB universal serial bus Approved for public

  7. Polarization utilization in radar target reconstruction: C-wide (Multi-frequency) band relationship of a target's characteristic operators with its unique set of natural eigenfrequencies

    NASA Astrophysics Data System (ADS)

    Boerner, W. M.; Huynen, J. R.; Mathur, N. C.; Foo, B. Y.; Nespor, J. D.

    1983-12-01

    During the tenure of this initiation contract on Polarization Utilization in Radar Target Identification a center of excellence for research in high resolution radar polarimetry was established within the Electromagnetic Imaging Division (EMID), Communications Laboratory (CL), Department of Electrical Engineering and Computer Science (EECS), University of Illinois at Chicago (UIC) with the express purpose of advancing theoretical, computational and experimental methods for radar target detection in clutter; separation of useful target vector signal from noise and clutter; classification of targets and/or clutter; target and/or clutter imaging, as well as target identification. To assist us in this endeavor, the College of Engineering, UIC, initially made available 2,200 sq. ft. laboratory space which now has expanded to 9,000 sq. ft. within SEL-4209/4210/4211 with adjacent side rooms, housing the CL-office, work and laboratory space for 18 research assistants and a DEC-VAX 11/750 and 780 Research Computer Processing System with some peripheral image processing, printing, color-graphics processors which were made available with partial funding from DoD-research offices and need to be further expanded.

  8. Localization of an air target by means of GNSS-based multistatic radar

    NASA Astrophysics Data System (ADS)

    Akhmedov, Daulet Sh.; Raskaliyev, Almat S.

    2016-08-01

    The possibility of utilizing transmitters of opportunity for target detection, tracking and positioning is of great interest to the radar community. In particular the optional use of Global Navigation Satellite System (GNSS) has lately triggered scientific research that has purpose to take advantage of this source of signal generation for passive radar. Number of studies have been conducted previously on development of GNSS-based bistatic and multistatic radars for detection and range estimation to the object located in the close atmosphere. To further enrich research in this area, we present a novel method for coordinate determination of the air target by means of the GNSS-based multistatic radar.

  9. Development of a polarimetric radar based hydrometeor classification algorithm for winter precipitation

    NASA Astrophysics Data System (ADS)

    Thompson, Elizabeth Jennifer

    The nation-wide WSR-88D radar network is currently being upgraded for dual-polarized technology. While many convective, warm-season fuzzy-logic hydrometeor classification algorithms based on this new suite of radar variables and temperature have been refined, less progress has been made thus far in developing hydrometeor classification algorithms for winter precipitation. Unlike previous studies, the focus of this work is to exploit the discriminatory power of polarimetric variables to distinguish the most common precipitation types found in winter storms without the use of temperature as an additional variable. For the first time, detailed electromagnetic scattering of plates, dendrites, dry aggregated snowflakes, rain, freezing rain, and sleet are conducted at X-, C-, and S-band wavelengths. These physics-based results are used to determine the characteristic radar variable ranges associated with each precipitation type. A variable weighting system was also implemented in the algorithm's decision process to capitalize on the strengths of specific dual-polarimetric variables to discriminate between certain classes of hydrometeors, such as wet snow to indicate the melting layer. This algorithm was tested on observations during three different winter storms in Colorado and Oklahoma with the dual-wavelength X- and S-band CSU-CHILL, C-band OU-PRIME, and X-band CASA IP1 polarimetric radars. The algorithm showed success at all three frequencies, but was slightly more reliable at X-band because of the algorithm's strong dependence on KDP. While plates were rarely distinguished from dendrites, the latter were satisfactorily differentiated from dry aggregated snowflakes and wet snow. Sleet and freezing rain could not be distinguished from rain or light rain based on polarimetric variables alone. However, high-resolution radar observations illustrated the refreezing process of raindrops into ice pellets, which has been documented before but not yet

  10. Polarimetric Synthetic Aperture Radar data for Crop Cover Classification

    NASA Astrophysics Data System (ADS)

    Ramana, K. V.; Srikanth, P.; Deepika, U.; Sesha Sai, M. V. R.

    2014-11-01

    The interest in crop inventory through the use of microwave sensors is on the rise owing to need for accurate crop forecast and the availability of multi polarization data. Till recently, the temporal amplitude data has been used for crop discrimination as well as acreage estimation. With the availability of dual and quadpol data, the differential response of crop geometry at various crop growth stages to various polarizations is being exploited for discrimination and classification of crops. An attempt has been made in the current study with RISAT1 and Radarsat2 C-band single, dual, fully and hybrid polarimetric data for crop inventory. The single date hybrid polarimetric data gave comparable results to the three date single polarization data as well as with the single date fully polarimetric data for crops like rice and cotton.

  11. Segmentation, classification, and pose estimation of maritime targets in flash-ladar imagery

    NASA Astrophysics Data System (ADS)

    Armbruster, Walter; Hammer, Marcus

    2012-09-01

    The paper presents new techniques for automatic segmentation, classification, and generic pose estimation of ships and boats in laser radar imagery. Segmentation, which primarily involves elimination of water reflections, is based on modeling surface waves and comparing the expected water reflection signature to the ladar intensity image. Shape classification matches a parametric shape representation of a generic ship hull with parameters extracted from the range image. The extracted parameter vector defines an instance of a geometric 3D model which can be registered with the range image for precision pose estimation. Results show that reliable automatic acquisition, aim point selection and realtime tracking of maritime targets is feasible even for erratic sensor and target motions, temporary occlusions, and evasive target maneuvers.

  12. Evaluation of second-order texture parameters for sea ice classification from radar images

    NASA Astrophysics Data System (ADS)

    Shokr, Mohammed E.

    1991-06-01

    With the advent of airborne and spaceborne synthetic aperture radar (SAR) systems, sea ice classification from SAR images has become an important research subject. Since gray tone alone has proven to be of limited capability in differentiating ice types, texture has naturally become an attractive avenue to explore. Accordingly, performance of texture quantification parameters as related to their ability to discriminate ice types has to be examined. SAR image appearance depends on radar parameters involved in the image construction procedures from the doppler history record. Therefore the feasibility of using universal texture/ice type relationships that hold for all combinations of radar parameters also has to be investigated. To that end, imagery data from three different SAR systems were used in this study. Five conventional texture parameters, derived from the gray level co-occurrence matrix (GLCM), were examined. Two of them were modified to ensure their invariant character under linear gray tone transformations. Results indicated that all parameters were highly correlated. The parameters did not, in general, vary with the computational variables used in generating co-occurrence matrices. Ice types can be identified uniquely by the mean value of any texture parameter. The relatively high variability of texture parameters, however, confuses ice discrimination, particularly of smoother ice types. Ice classification was conducted using a per-pixel maximum likelihood supervised scheme. When texture was combined with gray tone, the overall average classification accuracy was improved. Texture was successful in improving the classification accuracy of multiyear ice but was less promising in discriminating first-season ice types. The best two GLCM texture parameters, according to the computed overall average classification accuracies, were the inverse difference moment and the entropy. A brief description of GLCM texture parameters as related to ice's physical

  13. Multiple target tracking and target attitude determination with a scanning laser radar

    NASA Technical Reports Server (NTRS)

    Flom, T.; Coombes, D.

    1974-01-01

    A scanning laser radar that can acquire and track single or multiple targets has recently been developed. Scan patterns have been designed for acquisition and tracking of one or more targets using a narrow laser beam. A synchronously scanned transmitter-receiver is used to acquire and track targets anywhere in a 376 x 376 element raster covering a 30 x 30 deg field. All scan patterns are electronically programmed, and the system automatically acquires and tracks the target or targets without the aid of an operator. The maximum tracking rate is 1.0 deg/sec (10.0 deg/sec) when used with a 1 kHz (10 kHz) scan rate. The estimated free space range against passive cooperative targets (corner cube reflectors) is 30 nautical miles. The laser radar has an accuracy of 10 cm (range) and 0.05 deg (angle). The developmental system is relatively small (1.5 cu ft), lightweight (60 lbs) and low-power-consuming (60 W).

  14. The Who, What, Where and When of Radar Targeting: Key Note Speech

    DTIC Science & Technology

    2005-05-01

    imaging radar seeker • Aim point selection • Pulsed Doppler, polarisation diverse, pulse compression • Monopulse angular discrimination • LPI ...The Who, What, Where and When of Radar Targeting. Key Note speech/presentation, MATRIX 2005 workshop NATO SHAPE School, Oberammergau, Germany...review including: • The problems of ATR using mmW radar and some of the techniques traditionally applied. This establishes the state-of-the-art. This

  15. Acoustic Target Classification Using Multiscale Methods

    DTIC Science & Technology

    1998-01-01

    other vehicular activities well; because it represents dominant spectral peaks better than a short time Fourier transform. In the wavelet transform based...approach; multiscale features are obtained with a wavelet transform . Multiscale classification methods were applied to acoustic data collected at...This study considers the classification of acoustic signatures using features extracted at multiple scales from hierarchical models and a wavelet

  16. Pose-Angular Tracking of Maneuvering Targets With High Range Resolution (HRR) Radar

    DTIC Science & Technology

    2008-07-01

    useful for tracking maneuvering targets . For target identification (ID), range profiles obtained by a high range resolution (HRR) radar are...of moving targets . Keywords: Tracking, Maneuver, Target ID, Pose, HRR. 1 Introduction Compared to conventional tracking with post- detection ...range profile is generated. HRR range profiles have long been used for target identification (ID) or fingerprinting [8, 9, 13, 15]. It has also

  17. Using Shadows to Detect Targets In Synthetic Aperture Radar Imagery

    DTIC Science & Technology

    2009-03-01

    2.2.2 SAR Range and Cross Range Resolutions. The Projection-Slice Theo - rem provides a basis for discussing image resolution in SAR. If the radar...Radar: A Signal Processing Approach. Kluwer Academic Publishers Norwell, MA, USA, 1996. 12. Kersten, P.R., R.W. Jansen , K. Luc, and T.L. Ainsworth

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

    NASA Technical Reports Server (NTRS)

    Li, Jian

    1994-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Li, Jian

    1994-09-01

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

  20. K-means algorithm based on stochastic distances for polarimetric synthetic aperture radar image classification

    NASA Astrophysics Data System (ADS)

    Negri, Rogério Galante; da Silva, Wagner Barreto; Mendes, Tatiana Sussel Gonçalves

    2016-10-01

    The availability of polarimetric synthetic aperture radar (PolSAR) images has increased, and consequently, the classification of such images has received immense attention. Among different classification methods in the literature, it is possible to distinguish them according to learning paradigm and approach. Unsupervised methods have as advantage the independence of labeled data for training. Regarding the approach, image classification can be performed based on its individual pixels or on previously identified regions in the image. Previous studies verified that the region-based classification of PolSAR images using stochastic distances can produce better results in comparison with the pixel-based. Faced with the independence of training data by unsupervised methods and the potential of the region-based approach with stochastic distances, this study proposes a version of the unsupervised K-means algorithm for PolSAR region-based classification based on stochastic distances. The Bhattacharyya stochastic distance between Wishart distributions was adopted to measure the dissimilarity among regions of the PolSAR image. Additionally, a measure was proposed to compare unsupervised classification results. Two case studies that consider real and simulated images were conducted, and the results showed that the proposed version of K-means achieves higher accuracy values in comparison with the classic version.

  1. Neural networks for automated classification of ionospheric irregularities in HF radar backscattered signals

    NASA Astrophysics Data System (ADS)

    Wing, S.; Greenwald, R. A.; Meng, C.-I.; Sigillito, V. G.; Hutton, L. V.

    2003-08-01

    The classification of high frequency (HF) radar backscattered signals from the ionospheric irregularities (clutters) into those suitable, or not, for further analysis, is a time-consuming task even by experts in the field. We tested several different feedforward neural networks on this task, investigating the effects of network type (single layer versus multilayer) and number of hidden nodes upon performance. As expected, the multilayer feedforward networks (MLFNs) outperformed the single-layer networks. The MLFNs achieved performance levels of 100% correct on the training set and up to 98% correct on the testing set. Comparable figures for the single-layer networks were 94.5% and 92%, respectively. When measures of sensitivity, specificity, and proportion of variance accounted for by the model are considered, the superiority of the MLFNs over the single-layer networks is much more striking. Our results suggest that such neural networks could aid many HF radar operations such as frequency search, space weather, etc.

  2. Analysis of Features for Synthetic Aperture Radar Target Classification

    DTIC Science & Technology

    2015-03-26

    gradients HPC high performance computing LDA linear discriminant analysis PEC perfect electric conductor RVM relevance vector machine SAR synthetic...the polarization of the re-radiated field. When a linearly polarized electric field is incident on a flat perfect electric conductor (PEC), the

  3. Target Classification Using SAR (Synthetic Aperture Radar) Polarimetric Data

    DTIC Science & Technology

    1989-01-01

    concerned with studies which exarnine the ( ’c ht a, tcristics of dihedral corner reflectors [15]. However, the motive behind !III- ,. pIe-occupation...s excellent correlation between the predicted and the measured reaction of a dihedral 2-9 I I I I’ So e corner reflector to varying degrees of...Griesser’s article ti- tled Backscatter Analysis of Dihedral Corner Reflectors Using Physical Optics and the Physical Theory of Diffraction [17] in which he

  4. Moving target detection in foliage using along track monopulse synthetic aperture radar imaging.

    PubMed

    Soumekh, M

    1997-01-01

    This paper presents a method for detecting moving targets embedded in foliage from the monostatic and bistatic synthetic aperture radar (SAR) data obtained via two airborne radars. The two radars, which are mounted on the same aircraft, have different coordinates in the along track (cross-range) domain. However, unlike the interferometric SAR systems used for topographic mapping, the two radars possess a common range and altitude (i.e., slant range). The resultant monopulse SAR images are used to construct difference and interferometric images for moving target detection. It is shown that the signatures of the stationary targets are weakened in these images. Methods for estimating a moving target's motion parameters are discussed. Results for an ultrawideband UHF SAR system are presented.

  5. Using convolutional neural networks for human activity classification on micro-Doppler radar spectrograms

    NASA Astrophysics Data System (ADS)

    Jordan, Tyler S.

    2016-05-01

    This paper presents the findings of using convolutional neural networks (CNNs) to classify human activity from micro-Doppler features. An emphasis on activities involving potential security threats such as holding a gun are explored. An automotive 24 GHz radar on chip was used to collect the data and a CNN (normally applied to image classification) was trained on the resulting spectrograms. The CNN achieves an error rate of 1.65 % on classifying running vs. walking, 17.3 % error on armed walking vs. unarmed walking, and 22 % on classifying six different actions.

  6. Characterization and classification of freshwater marshy wetland using synthetic aperture radar polarimetry: a case study from Loktak wetland, Northeast India

    NASA Astrophysics Data System (ADS)

    Padalia, Hitendra; Musthafa, Mohamed

    2017-01-01

    Loktak is the largest natural wetland of Northeast India, the last home of endangered brow-antlered deer, and a site of global significance recognized under Ramsar convention. Ecological and human-meditated spatial patterns of Loktak wetland were characterized and classified using a Radarsat-2 C band synthetic aperture radar (SAR) satellite data. Radarsat-2 quad-pol scene of dry season was preprocessed and classified using PolSARpro software. Eigen vector-eigen value decomposition of coherency matrix (T3) was performed to characterize the scattering properties of wetland targets based on entropy (H)/anisotropy (A)/alpha angle (α) segmentation. Results illustrate that RGB color display of H/A/α images is a useful indicator of wetland structure and composition, and provide clear visual discrimination of open water, floating phumdi, permanent phumdi cover, and associated man-made features. Six classes, namely, floating phumdi, permanent phumdi, scrub/shrub, fallow land, built-up, and open water were mapped using Wishart classification of H/A/α images. Scattering mechanisms of natural and man-made targets synthesized from PolSAR data, and their classification using Wishart algorithm have been validated through a visually classified map and field reference points. The land cover generated would be useful for conservation and management of Loktak wetland and brow-antlered deer population.

  7. Marine Targets Classification in PolInSAR Data

    NASA Astrophysics Data System (ADS)

    Chen, Peng; Yang, Jingsong; Ren, Lin

    2014-11-01

    In this paper, marine stationary targets and moving targets are studied by Pol-In-SAR data of Radarsat-2. A new method of stationary targets detection is proposed. The method get the correlation coefficient image of the In-SAR data, and using the histogram of correlation coefficient image. Then, A Constant False Alarm Rate (CFAR) algorithm and The Probabilistic Neural Network model are imported to detect stationary targets. To find the moving targets, Azimuth Ambiguity is show as an important feature. We use the length of azimuth ambiguity to get the target's moving direction and speed. Make further efforts, Targets classification is studied by rebuild the surface elevation of marine targets.

  8. Marine Targets Classification in PolInSAR Data

    NASA Astrophysics Data System (ADS)

    Chen, Peng; Yang, Jingsong; Ren, Lin

    2014-11-01

    In this paper, marine stationary targets and moving targets are studied by Pol-In-SAR data of Radarsat-2. A new method of stationary targets detection is proposed. The method get the correlation coefficient image of the In-SAR data, and using the histogram of correlation coefficient image. Then , A Constant False Alarm Rate (CFAR) algorithm and The Probabilistic Neural Network model are imported to detect stationary targets. To find the moving targets, Azimuth Ambiguity is show as an important feature. We use the length of azimuth ambiguity to get the target's moving direction and speed. Make further efforts, Targets classification is studied by rebuild the surface elevation of marine targets.

  9. A system for the real-time display of radar and video images of targets

    NASA Technical Reports Server (NTRS)

    Allen, W. W.; Burnside, W. D.

    1990-01-01

    Described here is a software and hardware system for the real-time display of radar and video images for use in a measurement range. The main purpose is to give the reader a clear idea of the software and hardware design and its functions. This system is designed around a Tektronix XD88-30 graphics workstation, used to display radar images superimposed on video images of the actual target. The system's purpose is to provide a platform for tha analysis and documentation of radar images and their associated targets in a menu-driven, user oriented environment.

  10. System for Automatic Detection and Analysis of Targets in FMICW Radar Signal

    NASA Astrophysics Data System (ADS)

    Rejfek, Luboš; Mošna, Zbyšek; Urbář, Jaroslav; Koucká Knížová, Petra

    2016-01-01

    This paper presents the automatic system for the processing of the signals from the frequency modulated interrupted continuous wave (FMICW) radar and describes methods for the primary signal processing. Further, we present methods for the detection of the targets in strong noise. These methods are tested both on the real and simulated signals. The real signals were measured using the developed at the IAP CAS experimental prototype of FMICW radar with operational frequency 35.4 GHz. The measurement campaign took place at the TU Delft, the Netherlands. The obtained results were used for development of the system for the automatic detection and analysis of the targets measured by the FMICW radar.

  11. Electromagnetic modelling of Ground Penetrating Radar responses to complex targets

    NASA Astrophysics Data System (ADS)

    Pajewski, Lara; Giannopoulos, Antonis

    2014-05-01

    defined through a constant real value, or else its frequency-dispersion properties can be taken into account by incorporating into the model Debye approximations. The electromagnetic source can be represented as a simple line of current (in the case of two-dimensional models), a Hertzian dipole, a bow tie antenna, or else, the realistic description of a commercial antenna can be included in the model [2]. Preliminary results for some of the proposed cells are presented, obtained by using GprMax [3], a freeware tool which solves Maxwell's equations by using a second order in space and time Finite-Difference Time-Domain algorithm. B-Scans and A-Scans are calculated at 1.5 GHz, for the total electric field and for the field back-scattered by targets embedded in the cells. A detailed description of the structures, together with the relevant numerical results obtained to date, are available for the scientific community on the website of COST Action TU1208, www.GPRadar.eu. Research groups working on the development of electromagnetic forward- and inverse-scattering techniques, as well as on imaging methods, might test and compare the accuracy and applicability of their approaches on the proposed set of scenarios. The aim of this initiative is not that of identifying the best methods, but more properly to indicate the range of reliability of each approach, highlighting its advantages and drawbacks. In the future, the realisation of the proposed concrete cells and the acquisition of GPR experimental data would allow a very effective benchmark for forward and inverse scattering methods. References [1] R. Yelf, A. Ward, "Nine steps to concrete wisdom." Proc. 13th International Conference on Ground Penetrating Radar, Lecce, Italy, 21-25 June 2010, pp. 1-8. [2] C. Warren, A. Giannopoulos, "Creating FDTD models of commercial GPR antennas using Taguchi's optimisation method." Geophysics (2011), 76, article ID G37. [3] A. Giannopoulos, "Modelling ground penetrating radar by GPRMAX

  12. Classification of Ultra High Range Resolution Radar Using Decision Boundary Analysis.

    DTIC Science & Technology

    1994-12-01

    uncertainties in relative positions of target and radar, atmospheric effects, and equipment variations. Probability density functions (pdf’s) are...unimodal Gaussian distributions, but is analytically tractable. The decision rule or discriminant function , h(x) is defined to be (29): h(x_) = -lnC...Schematic the extent of the shaded region of the curve, which represents the density function of the Bernoulli, or binomial, random variable. In this case

  13. A model for forming airborne synthetic aperture radar images of underground targets

    SciTech Connect

    Doerry, A.W.

    1994-01-01

    Synthetic Aperture Radar (SAR) from an airborne platform has been proposed for imaging targets beneath the earth`s surface. The propagation of the radar`s energy within the ground, however, is much different than in the earth`s atmosphere. The result is signal refraction, echo delay, propagation losses, dispersion, and volumetric scattering. These all combine to make SAR image formation from an airborne platform much more challenging than a surface imaging counterpart. This report treats the ground as a lossy dispersive half-space, and presents a model for the radar echo based on measurable parameters. The model is then used to explore various imaging schemes, and image properties. Dynamic range is discussed, as is the impact of loss on dynamic range. Modified window functions are proposed to mitigate effects of sidelobes of shallow targets overwhelming deeper targets.

  14. Target profile identification of step frequency MMW radar based on wavelet neural network

    NASA Astrophysics Data System (ADS)

    Li, Yuehua; Gao, Duntang; Shen, Qinghong; Li, Xingguo

    2001-11-01

    With the increased availability of coherent wide band radar, there has been a renewed interest in the target recognition of MMW frequency step radar. A large bandwidth gives high resolution in range which means target recognition may be possible. In this paper, by integrating wavelet with neural network, a new adaptive wavelet function neural network is proposed. An artificial neural network with wavelet as weight coefficients is developed for pattern recognition. It is inspired by wavelet transform theory and feed forward neural network. The good localization characteristics of wavelet functions in both time and frequency space allow hierarchical multi-resolution learning of input-output data mappings. The wavelet shapes are adaptively computed to minimize an energy function for a specific application of radar targets. The mathematical frame of the neural network is introduced and error back propagation algorithm is used. The procedure of using wavelet neural network for identification is described in detail. Based on the target specific information offered by the range profiles of step frequency MMW radar targets, the wavelet neural network is applied to recognition of three kinds of practical radar targets. We find that we can reliably distinguish for three targets over a range of aspect angle. Experiment results indicate that the new feature vector in low dimension is valuable for target recognition, the wavelet neural network has faster convergence speed and higher correct recognition rate and the noise resistance character is good.

  15. Combined algorithm for improvement of fused radar and optical data classification accuracy

    NASA Astrophysics Data System (ADS)

    Karimi, Danya; Rangzan, Kazem; Akbarizadeh, Gholamreza; Kabolizadeh, Mostafa

    2017-01-01

    A new method, MICO-LDASR, is proposed to improve the classification accuracy of fused radar and optical data. The proposed algorithm combines three algorithms: multiplicative intrinsic component optimization (MICO), linear discriminant analysis (LDA), and sparse regularization (SR). MICO-LDASR first corrects the bias fields of the input images by an energy minimization process and then selects the most discriminative image features using a combination of LDA and SR (LDASR) based on a supervised feature selection and learning. Two pairs of fused radar and optical data were used in this study. Features, such as non-negative matrix factorization and textural features, were extracted from the original and bias corrected images, and, following the formation of two different types of feature matrices, the matrices were optimized based on LDASR and utilized in the two learned and unlearned forms as the inputs to rotation forest and support vector machine classifiers. The results showed that classification accuracy is greatly improved when implementing MICO-LDASR on feature matrices of Sentinel and ALOS-fused data.

  16. Polarimetric synthetic aperture radar image unsupervised classification method based on artificial immune system

    NASA Astrophysics Data System (ADS)

    Jie, Yu; Gang, Wang; Teng, Zhu; Xiaojuan, Li; Qin, Yan

    2014-01-01

    An unsupervised classification method based on the H/α classifier and artificial immune system (AIS) is proposed to overcome the inefficiencies that arise when traditional classification methods deal with polarimetric synthetic aperture radar (PolSAR) data having large numbers of overlapping pixels and excess polarimetric information. The method is composed of two steps. First, Cloude-Pottier decomposition is used to obtain the entropy H and the scattering angle α. The classification result based on the H/α plane is used to initialize the AIS algorithm. Second, to obtain accurate results, the AIS clonal selection algorithm is used to perform an iterative calculation. As a self-organizing, self-recognizing, and self-optimizing algorithm, the AIS is able to obtain a global optimal solution and better classification results by making use of both the scattering mechanism of ground features and polarimetric scattering characteristics. The effectiveness and feasibility of this method are demonstrated by experiments using a NASA-JPL PolSAR image and a high-resolution PolSAR image of Lingshui autonomous county in Hainan Province.

  17. Terrain classification of polarimetric synthetic aperture radar imagery based on polarimetric features and ensemble learning

    NASA Astrophysics Data System (ADS)

    Huang, Chuanbo

    2017-04-01

    An evolutionary classification system for terrain classification of polarimetric synthetic aperture radar (PolSAR) imagery based on ensemble learning with polarimetric and texture features is proposed. Polarimetric measurements cannot produce sufficient identification information for PolSAR terrain classification in some complex areas. To address this issue, texture features have been successfully used in image segmentation. The system classification feature has been adopted using a combination of Pauli features and the last principal component of Gabor texture-feature dimensionality reduction. The resulting feature combination assigned through experimental analysis is very suitable for describing structural and spatial information. To obtain a good integration effect, the basic classifier should be as precise as possible and the differences among the features should be as distinct as possible. We therefore examine and construct an ensemble-weighted voting classifier, including two support vector machine models that are constructed using kernel functions of the radial basis and sigmoid, extreme learning machine, k-nearest neighbor, and discriminant analysis classifier, which can avoid redundancy and bias because of different theoretical backgrounds. An experiment was performed to estimate the proposed algorithm's performance. The results verified that the algorithm can obtain better accuracy than the four classifiers mentioned in this paper.

  18. Electromagnetic Land Surface Classification by Integration of Optical and Radar Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Baek, Jin; Gu, Wei; Kim, Jeong Woo; Wang, Xin C.; Lim, Gye Jae; Lee, Dong Cheon

    2010-05-01

    Remotely sensed images, such as optical and radar (Synthetic Aperture Radar (SAR)) images have been playing important roles to retrieve crucial physical and chemical information on the land surface. With noticeable improvements of spatial, temporal, spectral, and radiometric resolutions of these satellite observations as well as with recent remarkable technical advances, it has been possible to observe and classify the land surface more accurately. By integration of satellite multi-spectral high-resolution optical and polarized radar images of central Alberta near Saskatchewan border, we present a non-hierarchical electromagnetic land surface classification method. We first adapt a conventional supervised land surface classification method using a commercial software ER-Mapper and also implement a Principal Component Analysis method (PCA) to the optical image to extract artificial facilities, such as access road and borehole site that are too small not to be recognized in the classification by any commercial software. The 11 electromagnetic (EM) properties suggested by Döttling and Wiesbeck (1999) on the basis of the U.S. Geological Survey (USGS) Level I and II land use classes are then assigned to the classified surfaces to produce hierarchical EM (e.g., dielectric constant, permittivity, etc) land classification maps. To further classify the hierarchical EM surface map, especially for dielectric constant, we calculate surface roughness with SRTM-3 Digital Elevation Model and at-sensor temperature from thermal band of Landsat-5. We also calculate backscattering coefficients and depolarization ratio from the polarimetric properties of the ALOS PALSAR images. Using these estimated values, we compute intrinsic weighting factors by Dubois (1995) model for less vegetated (NDVI <0.55) land area and Ulaby (1986) model for open water area. By multiplying these weight factors to the hierarchical EM surface, we generate a non-hierarchical higher-resolution EM surface map

  19. Automatic Target Recognition Classification System Evaluation Methodology

    DTIC Science & Technology

    2002-09-01

    Testing Example (α=0.1) ....................... 2-16 2.9 Binormal 2AFC ROC Curves...2-17 2.10 Target and Non-target Normal pdfs for a 2AFC Task....................................... 2-20 2.11 Sample N-N ROC Curve...2-23 2.13 Operating Curve Derived from 2AFC Task....................................................... 2-28 2.14 Example

  20. The effects of precipitation on radar target identification and imaging

    NASA Technical Reports Server (NTRS)

    Hodge, D. B.

    1975-01-01

    The properties of precipitation which will influence radar system design are discussed. The spatial characteristics of rainfall and the sizes and shapes of raindrops are described. The dielectric behavior of water is combined with these characteristics to determine the effects of rain on electromagnetic waves. These effects include: absorption, scatter, noise emission, phase shift, and depolarization.

  1. An experimental 0.2 THz stepped frequency radar system for the target detection

    NASA Astrophysics Data System (ADS)

    Zeng, Bangze; Liang, Meiyan; Zhang, Cunlin; Zhao, Yuejin

    2012-12-01

    Compared with traditional microwave and millimeter wave radars, Terahertz radar has wide signal bandwidth and a very narrow antenna beam, which is beneficial to the realization of high resolution imaging. And as an instantaneous narrowband and synthetic wideband waveform, stepped frequency radar signal has been widely exploited in many applications, since it allows high range resolution with modest requirements of the system bandwidth. As an instantaneous narrowband and synthetic wideband waveform, stepped frequency radar signal has been widely exploited in many applications, since it allows high range resolution with modest requirements of the system bandwidth. This paper presents the design of a 0.2THz stepped frequency imaging radar system with operating bandwidth of 12 GHz, thus, a theoretical range resolution below 1.25 cm. The simulation of the system is implemented by using system design parameters. An experimental trial has been performed, and one-dimensional range profile of the stationary target is obtained by Imaging Experiment using THz radar. Results show that the THz radar imaging system could achieve the target detection and centimeter-level range resolution.

  2. Micromotion feature extraction of radar target using tracking pulses with adaptive pulse repetition frequency adjustment

    NASA Astrophysics Data System (ADS)

    Chen, Yijun; Zhang, Qun; Ma, Changzheng; Luo, Ying; Yeo, Tat Soon

    2014-01-01

    In multifunction phased array radar systems, different activities (e.g., tracking, searching, imaging, feature extraction, recognition, etc.) would need to be performed simultaneously. To relieve the conflict of the radar resource distribution, a micromotion feature extraction method using tracking pulses with adaptive pulse repetition frequencies (PRFs) is proposed in this paper. In this method, the idea of a varying PRF is utilized to solve the frequency-domain aliasing problem of the micro-Doppler signal. With appropriate atom set construction, the micromotion feature can be extracted and the image of the target can be obtained based on the Orthogonal Matching Pursuit algorithm. In our algorithm, the micromotion feature of a radar target is extracted from the tracking pulses and the quality of the constructed image is fed back into the radar system to adaptively adjust the PRF of the tracking pulses. Finally, simulation results illustrate the effectiveness of the proposed method.

  3. Sea clutter reduction and target enhancement by neural networks in a marine radar system.

    PubMed

    Vicen-Bueno, Raúl; Carrasco-Álvarez, Rubén; Rosa-Zurera, Manuel; Nieto-Borge, José Carlos

    2009-01-01

    The presence of sea clutter in marine radar signals is sometimes not desired. So, efficient radar signal processing techniques are needed to reduce it. In this way, nonlinear signal processing techniques based on neural networks (NNs) are used in the proposed clutter reduction system. The developed experiments show promising results characterized by different subjective (visual analysis of the processed radar images) and objective (clutter reduction, target enhancement and signal-to-clutter ratio improvement) criteria. Moreover, a deep study of the NN structure is done, where the low computational cost and the high processing speed of the proposed NN structure are emphasized.

  4. Sea Clutter Reduction and Target Enhancement by Neural Networks in a Marine Radar System

    PubMed Central

    Vicen-Bueno, Raúl; Carrasco-Álvarez, Rubén; Rosa-Zurera, Manuel; Nieto-Borge, José Carlos

    2009-01-01

    The presence of sea clutter in marine radar signals is sometimes not desired. So, efficient radar signal processing techniques are needed to reduce it. In this way, nonlinear signal processing techniques based on neural networks (NNs) are used in the proposed clutter reduction system. The developed experiments show promising results characterized by different subjective (visual analysis of the processed radar images) and objective (clutter reduction, target enhancement and signal-to-clutter ratio improvement) criteria. Moreover, a deep study of the NN structure is done, where the low computational cost and the high processing speed of the proposed NN structure are emphasized. PMID:22573993

  5. Target Recognition Using Late-Time Returns from Ultra-Wideband, Short-Pulse Radar

    DTIC Science & Technology

    2004-06-01

    neglecting terms associated with surface resistance. The recognition sensor illuminates the target with a series of ultra-wideband, short radar pulses...the incident radar wave . Picture yourself looking into a mirror. If you can see your own face, you see the broadside of the mirror. Broadside is used...as an azimuth reference. Broadside illumination occurs when the incident wave approaches the object’s surface in a direction parallel to the surface

  6. A global search and rescue concept using synthetic aperture radar and passive user targets

    NASA Technical Reports Server (NTRS)

    Sivertson, W. E., Jr.

    1976-01-01

    A terrestrial search and rescue concept is defined embodying the use of passive radio-frequency reflectors in conjunction with an orbiting synthetic aperture radar to detect, identify, and locate users. An airborne radar test was conducted to evaluate the basic concept. In this test simple corner-reflector targets were successfully imaged. Results from this investigation were positive and indicate that the concept can be used to investigate new approaches focused on the development of a global search and rescue system.

  7. A rectangular-fit classifier for synthetic aperture radar automatic target recognition

    NASA Astrophysics Data System (ADS)

    Saghri, John A.; Cary, Daniel A.

    2007-09-01

    The utility of a rectangular-fit classifier for Synthetic Aperture Radar Automatic Target Recognition (SAR ATR) is examined. The target is fitted with and modeled as a rectangle that can best approximate its boundary. The rectangular fit procedure involves 1) a preprocessing phase to remove the background clutter and noise, 2) a pose detection phase to establish the alignment of the rectangle via a least squares straight line fitting algorithm, and 3) size determination phase via stretching the width and the height dimensions of the rectangle in order to encapsulate a pre-specified, e.g., 90%, of the points in the target. A training set composed of approximately half the total images in the MSTAR public imagery database are used to obtain and record the statistical variations in the width and height of the resulting rectangles for each potential target. The remaining half of the images is then used to assess the performance of this classifier. Preliminary results using minimum Euclidean and Mahalanobis distance classifiers show overall accuracies of 44% and 42%, respectively. Although the classification accuracy is relatively low, this technique can be successfully used in combination with other classifiers such as peaks, edges, corners, and shadow-based classifiers to enhance their performances. A unique feature of the rectangular fit classifier is that it is rotation invariant in its present form. However, observation of the dataset reveals that in general the shapes of the targets in SAR imagery are not fully rotation invariant. Thus, the classification accuracy is expected to improve considerably using multiple training sets, i.e., one training set generated and used for each possible pose. The tradeoff is the increased computation complexity which tends to be offset by ever increasing efficiency and speed of the processing hardware and software. The rectangular fit classifier can also be used as a pose detection routine and/or in conjunction with other ATR

  8. Micro-Doppler Radar Signatures for Itelligent Target Recognition

    DTIC Science & Technology

    2004-09-01

    es. En tant qu’outil d’identification et de reconnaissance, l’effet m-D semble prometteur pour les syst~mes op ~ rationnels susceptibles d’am~liorer...Defence Research and Recherche et developpement Development Canada pour la defense Canada DEFENCE DE7 DEFENS . Micro-Doppler radar signatures for... recherche permettant d’atteindre les objectifs techniques d6sir6s. ii DRDC Ottawa TM 2004-170 Executive summary Mechanical vibrations or rotations of

  9. Random Noise Monopulse Radar System for Covert Tracking of Targets

    NASA Astrophysics Data System (ADS)

    Narayanan, Ram M.

    2002-07-01

    The University of Nebraska is currently developing a unique monopulse radar concept based on the use of random noise signal for covert tracking applications. This project is funded by the Missile Defense Agency (MDA). The advantage of this system over conventional frequency-modulated continuous wave (FMCW) or short pulse systems is its covertness resulting from the random waveform's immunity from interception and jamming. The system integrates a novel heterodyne correlation receiver with conventional monopulse architecture. Based on the previous work such as random noise interferometry, a series of theoretical analysis and simulations were conducted to examine the potential performance of this monopulse system. Furthermore, a prototype system is under development to exploit practical design aspects of phase comparison angle measurement. It is revealed that random noise monopulse radar can provide the same function as traditional monopulse radar, i.e., implement range and angular estimation and tracking in real time. The bandwidth of random noise signal can be optimized to achieve the best range resolution as well as the angular accuracy.

  10. Through Wall Radar Classification of Human Micro-Doppler Using Singular Value Decomposition Analysis

    PubMed Central

    Ritchie, Matthew; Ash, Matthew; Chen, Qingchao; Chetty, Kevin

    2016-01-01

    The ability to detect the presence as well as classify the activities of individuals behind visually obscuring structures is of significant benefit to police, security and emergency services in many situations. This paper presents the analysis from a series of experimental results generated using a through-the-wall (TTW) Frequency Modulated Continuous Wave (FMCW) C-Band radar system named Soprano. The objective of this analysis was to classify whether an individual was carrying an item in both hands or not using micro-Doppler information from a FMCW sensor. The radar was deployed at a standoff distance, of approximately 0.5 m, outside a residential building and used to detect multiple people walking within a room. Through the application of digital filtering, it was shown that significant suppression of the primary wall reflection is possible, significantly enhancing the target signal to clutter ratio. Singular Value Decomposition (SVD) signal processing techniques were then applied to the micro-Doppler signatures from different individuals. Features from the SVD information have been used to classify whether the person was carrying an item or walking free handed. Excellent performance of the classifier was achieved in this challenging scenario with accuracies up to 94%, suggesting that future through wall radar sensors may have the ability to reliably recognize many different types of activities in TTW scenarios using these techniques. PMID:27589760

  11. Through Wall Radar Classification of Human Micro-Doppler Using Singular Value Decomposition Analysis.

    PubMed

    Ritchie, Matthew; Ash, Matthew; Chen, Qingchao; Chetty, Kevin

    2016-08-31

    The ability to detect the presence as well as classify the activities of individuals behind visually obscuring structures is of significant benefit to police, security and emergency services in many situations. This paper presents the analysis from a series of experimental results generated using a through-the-wall (TTW) Frequency Modulated Continuous Wave (FMCW) C-Band radar system named Soprano. The objective of this analysis was to classify whether an individual was carrying an item in both hands or not using micro-Doppler information from a FMCW sensor. The radar was deployed at a standoff distance, of approximately 0.5 m, outside a residential building and used to detect multiple people walking within a room. Through the application of digital filtering, it was shown that significant suppression of the primary wall reflection is possible, significantly enhancing the target signal to clutter ratio. Singular Value Decomposition (SVD) signal processing techniques were then applied to the micro-Doppler signatures from different individuals. Features from the SVD information have been used to classify whether the person was carrying an item or walking free handed. Excellent performance of the classifier was achieved in this challenging scenario with accuracies up to 94%, suggesting that future through wall radar sensors may have the ability to reliably recognize many different types of activities in TTW scenarios using these techniques.

  12. Ultrawideband radar echoes of land mine targets measured at oblique incidence using a 250-kW impulse radar system

    NASA Astrophysics Data System (ADS)

    Chant, Ian J.; Staines, Geoff

    1997-07-01

    United Nations Peacekeeping forces around the world need to transport food, personnel and medical supplies through disputed regions were land mines are in active use as road blocks and terror weapons. A method of fast, effective land mine detection is needed to combat this threat to road transport. The technique must operate from a vehicle travelling at a reasonable velocity and give warning far enough ahead for the vehicle to stop in time to avoid the land mine. There is particular interest in detecting low- metallic content land mines. One possible solutionis the use of ultra-wide-band (UWB) radar. The Australian Defence Department is investigating the feasibility of using UWB radar for land mine detection from a vehicle. A 3 GHz UWB system has been used to collect target response from a series of inert land mines and mine-like objects placed on the ground and buried in the ground. The targets measured were a subset of those in the target set described in Wong et al. with the addition of inert land mines corresponding to some of the surrogate targets in this set. The results are encouraging for the detection of metallic land mines and the larger non-metallic land mines. Smaller low-metallic- content anti-personnel land mines are less likely to be detected.

  13. A fast 3D image simulation algorithm of moving target for scanning laser radar

    NASA Astrophysics Data System (ADS)

    Li, Jicheng; Shi, Zhiguang; Chen, Xiao; Chen, Dong

    2014-10-01

    Scanning Laser Radar has been widely used in many military and civil areas. Usually there are relative movements between the target and the radar, so the moving target image modeling and simulation is an important research content in the field of signal processing and system design of scan-imaging laser radar. In order to improve the simulation speed and hold the accuracy of the image simulation simultaneously, a novel fast simulation algorithm is proposed in this paper. Firstly, for moving target or varying scene, an inequation that can judge the intersection relations between the pixel and target bins is obtained by deriving the projection of target motion trajectories on the image plane. Then, by utilizing the time subdivision and approximate treatments, the potential intersection relations of pixel and target bins are determined. Finally, the goal of reducing the number of intersection operations could be achieved by testing all the potential relations and finding which of them is real intersection. To test the method's performance, we perform computer simulations of both the new proposed algorithm and a literature's algorithm for six targets. The simulation results show that the two algorithm yield the same imaging result, whereas the number of intersection operations of former is equivalent to only 1% of the latter, and the calculation efficiency increases a hundredfold. The novel simulation acceleration idea can be applied extensively in other more complex application environments and provide equally acceleration effect. It is very suitable for the case to produce a great large number of laser radar images.

  14. Agent Collaborative Target Localization and Classification in Wireless Sensor Networks

    PubMed Central

    Wang, Xue; Bi, Dao-wei; Ding, Liang; Wang, Sheng

    2007-01-01

    Wireless sensor networks (WSNs) are autonomous networks that have been frequently deployed to collaboratively perform target localization and classification tasks. Their autonomous and collaborative features resemble the characteristics of agents. Such similarities inspire the development of heterogeneous agent architecture for WSN in this paper. The proposed agent architecture views WSN as multi-agent systems and mobile agents are employed to reduce in-network communication. According to the architecture, an energy based acoustic localization algorithm is proposed. In localization, estimate of target location is obtained by steepest descent search. The search algorithm adapts to measurement environments by dynamically adjusting its termination condition. With the agent architecture, target classification is accomplished by distributed support vector machine (SVM). Mobile agents are employed for feature extraction and distributed SVM learning to reduce communication load. Desirable learning performance is guaranteed by combining support vectors and convex hull vectors. Fusion algorithms are designed to merge SVM classification decisions made from various modalities. Real world experiments with MICAz sensor nodes are conducted for vehicle localization and classification. Experimental results show the proposed agent architecture remarkably facilitates WSN designs and algorithm implementation. The localization and classification algorithms also prove to be accurate and energy efficient.

  15. Bi-Spectral Method for Radar Target Recognition

    DTIC Science & Technology

    2006-12-01

    as a summation of the reflected echo signals from all of the multiple scatterers’ interactions: ( ) ( ) ninteractio order-higher eAH m pqq t tt i...tp+tq)/2+(tp+tq)/2 = tp+tq and the second major component of this signal can be rewritten as: ( ) ( ) ( )[ ] ninteractio order-higher . eAH m pqq ...amplitudes are frequency-independent, the radar backscattered signal, H(ω) is given as: 24 ( ) ( ) ( ) ( ) ( )[ ]∑ ∑∑ = ≠= +++− = +− += += m p m pqq

  16. Sleep stage classification by non-contact vital signs indices using Doppler radar sensors.

    PubMed

    Kagawa, Masayuki; Suzumura, Kazuki; Matsui, Takemi

    2016-08-01

    Disturbed sleep has become more common in recent years. To improve the quality of sleep, undergoing sleep observation has gained interest as a means to resolve possible problems. In this paper, we evaluate a non-restrictive and non-contact method for classifying real-time sleep stages and report on its potential applications. The proposed system measures heart rate (HR), heart rate variability (HRV), body movements, and respiratory signals of a sleeping person using two 24-GHz microwave radars placed beneath the mattress. We introduce a method that dynamically selects the window width of the moving average filter to extract the pulse waves from the radar output signals. The Pearson correlation coefficient between two HR measurements derived from the radars overnight, and the reference polysomnography was the average of 88.3% and the correlation coefficient for HRV parameters was the average of 71.2%. For identifying wake and sleep periods, the body-movement index reached sensitivity of 76.0%, and a specificity of 77.0% with 10 participants. Low-frequency (LF) components of HRV and the LF/HF ratio had a high degree of contribution and differed significantly across the three sleep stages (REM, LIGHT, and DEEP; p <; 0.01). In contrast, high-frequency (HF) components of HRV were not significantly different across the three sleep stages (p > 0.05). We applied a canonical discriminant analysis to identify wake or sleep periods and to classify the three sleep stages with leave-one-out cross validation. Classification accuracy was 66.4% for simply identifying wake and sleep, 57.1% for three stages (wake, REM, and NREM) and 34% for four stages (wake, REM, LIGHT, and DEEP). This is a novel system for measuring HRs, HRV, body movements, and respiratory intervals and for measuring high sensitivity pulse waves using two radar signals. It simplifies measurement of sleep stages and may be employed at nursing care facilities or by the general public to improve sleep quality.

  17. A Virtual Target Radar System for Small Arms Fire Training (Preprint)

    DTIC Science & Technology

    2014-10-09

    end in order to minimize the system Radar 1 (0,0,0) Radar 2 (d,0,0) y -axis Bullet trajectory Active area Aim point (d/2,d/2,0) 484 noise figure...dimensions as those of the bullet . The H/H target RCS of 0.001 m2 at a range of 4 metres would yield a SNR of 53 dB (assuming a noise limited detection...provides the miss distance of a bullet from an aim point in two axes as the bullet passes through the target plane. Initial work indicates that a low

  18. Target Detection and Classification Using Seismic and PIR Sensors

    DTIC Science & Technology

    2012-06-01

    time series analysis via wavelet - based partitioning,” Signal Process...regard, this paper presents a wavelet - based method for target detection and classification. The proposed method has been validated on data sets of...The work reported in this paper makes use of a wavelet - based feature extraction method , called Symbolic Dynamic Filtering (SDF) [12]–[14]. The

  19. Radar remote sensing for crop classification and canopy condition assessment: Ground-data documentation

    NASA Technical Reports Server (NTRS)

    Ulaby, F. T. (Principal Investigator); Jung, B.; Gillespie, K.; Hemmat, M.; Aslam, A.; Brunfeldt, D.; Dobson, M. C.

    1983-01-01

    A vegetation and soil-moisture experiment was conducted in order to examine the microwave emission and backscattering from vegetation canopies and soils. The data-acquisition methodology used in conjunction with the mobile radar scatterometer (MRS) systems is described and associated ground-truth data are documented. Test fields were located in the Kansas River floodplain north of Lawrence, Kansas. Ten fields each of wheat, corn, and soybeans were monitored over the greater part of their growing seasons. The tabulated data summarize measurements made by the sensor systems and represent target characteristics. Target parameters describing the vegetation and soil characteristics include plant moisture, density, height, and growth stage, as well as soil moisture and soil-bulk density. Complete listings of pertinent crop-canopy and soil measurements are given.

  20. Multiple target three-dimensional coordinate estimation for bistatic MIMO radar with uniform linear receive array

    NASA Astrophysics Data System (ADS)

    Li, Jun; Li, Huan; Long, Libing; Liao, Guisheng; Griffiths, Hugh

    2013-12-01

    A novel scheme to achieve three-dimensional (3D) target location in bistatic radar systems is evaluated. The proposed scheme develops the additional information of the bistatic radar, that is the transmit angles, to estimate the 3D coordinates of the targets by using multiple-input multiple-output techniques with a uniform circular array on transmit and a uniform linear array on receive. The transmit azimuth, transmit elevation angles and receive cone angle of the targets are first extracted from the receive data and the 3D coordinates are then calculated on the basis of these angles. The geometric dilution of precision which is based on the root Cramer-Rao bound of the angles, is derived to evaluate the performance bound of the proposed scheme. Further, an ESPRIT based algorithm is developed to estimate the 3D coordinates of the targets. The advantages of this scheme are that the hardware of the receive array is reduced and the 3D coordinates of the targets can be estimated in the absence of the range information in bistatic radar. Simulations and analysis show that the proposed scheme has potential to achieve good performance with low-frequency radar.

  1. Object-oriented classification using quasi-synchronous multispectral images (optical and radar) over agricultural surface

    NASA Astrophysics Data System (ADS)

    Marais Sicre, Claire; Baup, Frederic; Fieuzal, Remy

    2015-04-01

    In the context of climate change (with consequences on temperature and precipitation patterns), persons involved in agricultural management have the imperative to combine: sufficient productivity (as a response of the increment of the necessary foods) and durability of the resources (in order to restrain waste of water, fertilizer or environmental damages). To this end, a detailed knowledge of land use will improve the management of food and water, while preserving the ecosystems. Among the wide range of available monitoring tools, numerous studies demonstrated the interest of satellite images for agricultural mapping. Recently, the launch of several radar and optical sensors offer new perspectives for the multi-wavelength crop monitoring (Terrasar-X, Radarsat-2, Sentinel-1, Landsat-8…) allowing surface survey whatever the cloud conditions. Previous studies have demonstrated the interest of using multi-temporal approaches for crop classification, requiring several images for suitable classification results. Unfortunately, these approaches are limited (due to the satellite orbit cycle) and require waiting several days, week or month before offering an accurate land use map. The objective of this study is to compare the accuracy of object-oriented classification (random forest algorithm combined with vector layer coming from segmentation) to map winter crop (barley, rapeseed, grasslands and wheat) and soil states (bare soils with different surface roughness) using quasi-synchronous images. Satellite data are composed of multi-frequency and multi-polarization (HH, VV, HV and VH) images acquired near the 14th of April, 2010, over a studied area (90km²) located close to Toulouse in France. This is a region of alluvial plains and hills, which are mostly mixed farming and governed by a temperate climate. Remote sensing images are provided by Formosat-2 (04/18), Radarsat-2 (C-band, 04/15), Terrasar-X (X-band, 04/14) and ALOS (L-band, 04/14). Ground data are collected

  2. Development of Two-Dimensional Parametric Radar Signal Modeling and Estimation Techniques with Application to Target Identification

    DTIC Science & Technology

    1992-01-01

    domain point form: V x _(, 0 & 12 13 atVX W(R,t) = (Rt) V.9=t) 0. (2.1) The spatial position of the field quantities is denoted by R (R would be x, y, z ...radar-target orientation. This is a target fixed coordinate system; 18 Z 0 radar, pointed at target target Figure 2: Radar Target orientation. that is...from [1]. 24 z 0 point of interest r x Figure 3: Standard spherical coordinate system. This plot has three curves. The solid line is an approximation

  3. Sleep stage classification by body movement index and respiratory interval indices using multiple radar sensors.

    PubMed

    Kagawa, Masayuki; Sasaki, Noriyuki; Suzumura, Kazuki; Matsui, Takemi

    2015-01-01

    Disturbed sleep has become more common in recent years. To increase the quality of sleep, undergoing sleep observation has gained interest as an attempt to resolve possible problems. In this paper, we evaluate a non-restrictive and non-contact method for classifying real-time sleep stages and report on its potential applications. The proposed system measures body movements and respiratory signals of a sleeping person using a multiple 24-GHz microwave radar placed beneath the mattress. We determined a body-movement index to identify wake and sleep periods, and fluctuation indices of respiratory intervals to identify sleep stages. For identifying wake and sleep periods, the rate agreement between the body-movement index and the reference result using the R&K method was 83.5 ± 6.3%. One-minute standard deviations, one of the fluctuation indices of respiratory intervals, had a high degree of contribution and showed a significant difference across the three sleep stages (REM, LIGHT, and DEEP; p <; 0.001). Although the degree that the 5-min fractal dimension contributed-another fluctuation index-was not as high as expected, its difference between REM and DEEP sleep was significant (p <; 0.05). We applied a linear discriminant function to classify wake or sleep periods and to estimate the three sleep stages. The accuracy was 79.3% for classification and 71.9% for estimation. This is a novel system for measuring body movements and body-surface movements that are induced by respiration and for measuring high sensitivity pulse waves using multiple radar signals. This method simplifies measurement of sleep stages and may be employed at nursing care facilities or by the general public to increase sleep quality.

  4. A modal radar cross section of thin-wire targets via the singularity expansion method

    NASA Technical Reports Server (NTRS)

    Richards, M. A.; Shumpert, T. H.; Riggs, L. S.

    1992-01-01

    A modal radar cross section (RCS) of arbitrary wire scatterers is constructed in terms of SEM parameters. Numerical results are presented for both straight and L-shaped wire targets and are compared to computations performed in the frequency domain using the method of moments.

  5. Analyse multiechelle d'images radar: Application au filtrage, a la classification et a la fusion d'images radar et optique

    NASA Astrophysics Data System (ADS)

    Foucher, Samuel

    Les images radar sont perturbees par un bruit multiplicatif (chatoiement) reduisant sensiblement la resolution radiometrique des cibles homogenes etendues. Le but de cette these est d'etudier l'apport de l'analyse multiechelle, plus particulierement de la transformee en ondelettes, dans le probleme de la reduction du chatoiement et de la classification non dirigee des images radar. Dans le cadre de la transformee en ondelettes stationnaire, garantissant l'invariance par translation de la representation, les techniques usuelles de filtrage adaptatif sont etendues au domaine multiechelle. Nous proposons de prendre en compte les specificites statistiques de l'image radar (modele multiplicatif, loi K) afin de separer les coefficients d'ondelettes engendres par le bruit seul de ceux engendres par les structures significatives de l'image. Le systeme de distribution de Pearson est applique afin de modeliser la distribution de probabilites des coefficients d'ondelettes. Lorsque l'intensite observee obeit a une loi K, le systeme de Pearson conduit a une loi de type IV (loi Beta complexe). Le type IV de Pearson est mis en oeuvre dans une ponderation de type MAP (Maximum A Posteriori). L'influence de la correlation du chatoiement sur les moments d'ordre superieur est ensuite evaluee quantitativement a partir d'une modelisation MA ("Moving Average") de l'image radar correlee. Les resultats obtenus sur un ensemble d'images artificielles montrent que l'approche multiechelle permet d'atteindre un meilleur compromis entre preservation des details et lissage des regions homogenes par rapport aux methodes de filtrage traditionnelles. En classification, la representation multiechelle permet de faire fluctuer le compromis precision spatiale/incertitude radiometrique. La theorie des croyances fournit un cadre theorique afin de manipuler les notions d'incertitude et d'imprecision. Nous proposons de combiner directement les decisions multiechelles par la regle de Dempster en integrant l

  6. An assignment based algorithm for multiple target localization problems using widely-separated MIMO radars

    NASA Astrophysics Data System (ADS)

    Gorji, A. A.; Tharmarasa, R.; Kirubarajan, T.

    2010-04-01

    Multiple-Input Multiple-Output (MIMO) radars with widely-separated antennas have attracted much attention in recent literature. The highly efficient performance of widely-separated MIMO radars in target detection compared to multistatic radars have been widely studied by researchers. However, multiple target localization by the enlightened structure has not been sufficiently explored. While Multiple Hypothesis Tracking (MHT) based methods have been previously applied for target localization, in this paper, the well-known 2-D assignment method is used instead in order to handle the computational cost of MHT. The assignment based algorithm works in a signal-level mode. That is, signals in receivers are first matched to different transmitters and, then, outputs of matched filters are used to find the cost of each combination in the 2-D assignment method. The main benefit of 2-D assignment is to easily incorporate new targets that are suitable for targets with multiple scatters where a target may be otherwise unobservable in some pairs. Simulation results justify the capability of 2-D assignment method in tackling multiple target localization problems, even in relatively low SNRs.

  7. Non-Cooperative Target Imaging and Parameter Estimation with Narrowband Radar Echoes

    PubMed Central

    Yeh, Chun-mao; Zhou, Wei; Lu, Yao-bing; Yang, Jian

    2016-01-01

    This study focuses on the rotating target imaging and parameter estimation with narrowband radar echoes, which is essential for radar target recognition. First, a two-dimensional (2D) imaging model with narrowband echoes is established in this paper, and two images of the target are formed on the velocity-acceleration plane at two neighboring coherent processing intervals (CPIs). Then, the rotating velocity (RV) is proposed to be estimated by utilizing the relationship between the positions of the scattering centers among two images. Finally, the target image is rescaled to the range-cross-range plane with the estimated rotational parameter. The validity of the proposed approach is confirmed using numerical simulations. PMID:26805836

  8. Imaging and target detection with a heterodyne-reception optical radar.

    PubMed

    Shapiro, J H; Capron, B A; Harney, R C

    1981-10-01

    A mathematical system model for a compact heterodyne-reception infrared radar is developed. This model incorporates the statistical effects of propagation through atmospheric turbulence, target speckle and glint, and heterodyne-reception shot noise. It is used to find the image signal-to-noise ratio of a matched-filter envelope-detector receiver and the target detection probability of the optimum likelihood ratio processor. For realistic parameter values it is shown that turbulence-induced beam spreading and coherence loss may be neglected. Target speckle and atmospheric scintillation, however, present serious limitations on single-frame imaging and target-detection performance. Experimental turbulence strength measurements are reviewed, and selected results are used in sample performance calculations for a realistic infrared radar.

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

    SciTech Connect

    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 a single report hopes to offer some value in reducing the 'seek time'.

  10. A Novel Data-Driven Learning Method for Radar Target Detection in Nonstationary Environments

    DTIC Science & Technology

    2016-05-01

    Dec. 2006, pp. 1113–1118. [21] J. Z. Kolter and M. A. Maloof, “Dynamic weighted majority: An ensemble method for drifting concepts,” J. Mach. Learn...762 IEEE SIGNAL PROCESSING LETTERS, VOL. 23, NO. 5, MAY 2016 A Novel Data-Driven Learning Method for Radar Target Detection in Nonstationary...Therefore, to overcome such shortcomings, we develop a data-driven method for target detec- tion in nonstationary environments. In this method , the

  11. Outliers of the ASK classification as targets for GTC serendipity

    NASA Astrophysics Data System (ADS)

    Sánchez Almeida, J.; Aguerri, J. A. L.; Muñoz-Tuñón, C.

    2013-05-01

    We classified the ˜10^6 galaxy spectra in SDSS/DR7 (Abazajian et al. 2009) into only 17 major classes (ASK classification; Sánchez Almeida et al. 2010). The algorithm provides the goodness of the classification for each individual spectrum and, therefore, a straightforward way to identify those targets which do not fit in the ASK classes. A significant part of these outliers turn out to be failures of the automatic reduction pipelines. However, a fraction of them represents genuine unusual objects which deserve detailed follow up work to assess their nature. These targets provide a unique opportunity for GTC to carry out serendipitous discoveries. This contribution summarizes the main properties of the outliers.

  12. An algorithm for automatic target recognition using passive radar and an EKF for estimating aircraft orientation

    NASA Astrophysics Data System (ADS)

    Ehrman, Lisa M.

    2005-07-01

    Rather than emitting pulses, passive radar systems rely on "illuminators of opportunity," such as TV and FM radio, to illuminate potential targets. These systems are attractive since they allow receivers to operate without emitting energy, rendering them covert. Until recently, most of the research regarding passive radar has focused on detecting and tracking targets. This dissertation focuses on extending the capabilities of passive radar systems to include automatic target recognition. The target recognition algorithm described in this dissertation uses the radar cross section (RCS) of potential targets, collected over a short period of time, as the key information for target recognition. To make the simulated RCS as accurate as possible, the received signal model accounts for aircraft position and orientation, propagation losses, and antenna gain patterns. An extended Kalman filter (EKF) estimates the target's orientation (and uncertainty in the estimate) from velocity measurements obtained from the passive radar tracker. Coupling the aircraft orientation and state with the known antenna locations permits computation of the incident and observed azimuth and elevation angles. The Fast Illinois Solver Code (FISC) simulates the RCS of potential target classes as a function of these angles. Thus, the approximated incident and observed angles allow the appropriate RCS to be extracted from a database of FISC results. Using this process, the RCS of each aircraft in the target class is simulated as though each is executing the same maneuver as the target detected by the system. Two additional scaling processes are required to transform the RCS into a power profile (magnitude only) simulating the signal in the receiver. First, the RCS is scaled by the Advanced Refractive Effects Prediction System (AREPS) code to account for propagation losses that occur as functions of altitude and range. Then, the Numerical Electromagnetic Code (NEC2) computes the antenna gain pattern

  13. Dr. J. R. Huynen's main contributions in the development of polarimetric radar techniques and how the 'Radar Targets Phenomenological Concept' becomes a theory

    NASA Astrophysics Data System (ADS)

    Pottier, Eric

    1993-02-01

    Among the engineering scientists who have most decisively contributed toward forefront advances for the 'Development of POLARIMETRIC Radar Theory, Techniques and Target Phenomenology', Dr. Jean Richard HUYNEN stands out as one of the towering giants. This paper is dedicated to him, and it is a great honor for the author to present here a summary on some of the main Dr. J.R. HUYNEN's contributions in the development of Polarimetric Radar Techniques, including the 'Mueller Matrix Decomposition' approaches which this Senior Radar Polarimetrist considers as his 'life's main contribution'.

  14. A novel data-driven learning method for radar target detection in nonstationary environments

    DOE PAGES

    Akcakaya, Murat; Nehorai, Arye; Sen, Satyabrata

    2016-04-12

    Most existing radar algorithms are developed under the assumption that the environment (clutter) is stationary. However, in practice, the characteristics of the clutter can vary enormously depending on the radar-operational scenarios. If unaccounted for, these nonstationary variabilities may drastically hinder the radar performance. Therefore, to overcome such shortcomings, we develop a data-driven method for target detection in nonstationary environments. In this method, the radar dynamically detects changes in the environment and adapts to these changes by learning the new statistical characteristics of the environment and by intelligibly updating its statistical detection algorithm. Specifically, we employ drift detection algorithms to detectmore » changes in the environment; incremental learning, particularly learning under concept drift algorithms, to learn the new statistical characteristics of the environment from the new radar data that become available in batches over a period of time. The newly learned environment characteristics are then integrated in the detection algorithm. Furthermore, we use Monte Carlo simulations to demonstrate that the developed method provides a significant improvement in the detection performance compared with detection techniques that are not aware of the environmental changes.« less

  15. A novel data-driven learning method for radar target detection in nonstationary environments

    SciTech Connect

    Akcakaya, Murat; Nehorai, Arye; Sen, Satyabrata

    2016-04-12

    Most existing radar algorithms are developed under the assumption that the environment (clutter) is stationary. However, in practice, the characteristics of the clutter can vary enormously depending on the radar-operational scenarios. If unaccounted for, these nonstationary variabilities may drastically hinder the radar performance. Therefore, to overcome such shortcomings, we develop a data-driven method for target detection in nonstationary environments. In this method, the radar dynamically detects changes in the environment and adapts to these changes by learning the new statistical characteristics of the environment and by intelligibly updating its statistical detection algorithm. Specifically, we employ drift detection algorithms to detect changes in the environment; incremental learning, particularly learning under concept drift algorithms, to learn the new statistical characteristics of the environment from the new radar data that become available in batches over a period of time. The newly learned environment characteristics are then integrated in the detection algorithm. Furthermore, we use Monte Carlo simulations to demonstrate that the developed method provides a significant improvement in the detection performance compared with detection techniques that are not aware of the environmental changes.

  16. Studies of Target Detection Algorithms Which Use Polarimetric Radar Data

    DTIC Science & Technology

    1987-10-28

    are of the form problem (i.e., target-plus-clutter versus clutter) the likelihood ratio is [3] 1 0 P/ (3) f(Xi wt+c) > TD say (9) 1 = 0 0 0 where...we denote the target-plus-clutter class by P" / -Y 0 wt+c and the clutter only class by % c". TD is the detection threshold. The solution to this...it yields the best possible proba- 22112 bility of detection for a given false alarm proba- 41cftP - 2ct +t c I + t c bility. An alternative approach is

  17. Benchmark radar targets for the validation of computational electromagnetics programs

    NASA Technical Reports Server (NTRS)

    Woo, Alex C.; Wang, Helen T. G.; Schuh, Michael J.; Sanders, Michael L.

    1993-01-01

    Results are presented of a set of computational electromagnetics validation measurements referring to three-dimensional perfectly conducting smooth targets, performed for the Electromagnetic Code Consortium. Plots are presented for both the low- and high-frequency measurements of the NASA almond, an ogive, a double ogive, a cone-sphere, and a cone-sphere with a gap.

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

    PubMed

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

    2014-10-27

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

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

    PubMed Central

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

    2014-01-01

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

  20. A simulation-based approach towards automatic target recognition of high resolution space borne radar signatures

    NASA Astrophysics Data System (ADS)

    Anglberger, H.; Kempf, T.

    2016-10-01

    Specific imaging effects that are caused mainly by the range measurement principle of a radar device, its much lower frequency range as compared to the optical spectrum, the slanted imaging geometry and certainly the limited spatial resolution complicates the interpretation of radar signatures decisively. Especially the coherent image formation which causes unwanted speckle noise aggravates the problem of visually recognizing target objects. Fully automatic approaches with acceptable false alarm rates are therefore an even harder challenge. At the Microwaves and Radar Institute of the German Aerospace Center (DLR) the development of methods to implement a robust overall processing workflow for automatic target recognition (ATR) out of high resolution synthetic aperture radar (SAR) image data is under progress. The heart of the general approach is to use time series exploitation for the former detection step and simulation-based signature matching for the subsequent recognition. This paper will show the overall ATR chain as a proof of concept for the special case of airplane recognition on image data from the space borne SAR sensor TerraSAR-X.

  1. Target Tracking Using SePDAF under Ambiguous Angles for Distributed Array Radar

    PubMed Central

    Long, Teng; Zhang, Honggang; Zeng, Tao; Chen, Xinliang; Liu, Quanhua; Zheng, Le

    2016-01-01

    Distributed array radar can improve radar detection capability and measurement accuracy. However, it will suffer cyclic ambiguity in its angle estimates according to the spatial Nyquist sampling theorem since the large sparse array is undersampling. Consequently, the state estimation accuracy and track validity probability degrades when the ambiguous angles are directly used for target tracking. This paper proposes a second probability data association filter (SePDAF)-based tracking method for distributed array radar. Firstly, the target motion model and radar measurement model is built. Secondly, the fusion result of each radar’s estimation is employed to the extended Kalman filter (EKF) to finish the first filtering. Thirdly, taking this result as prior knowledge, and associating with the array-processed ambiguous angles, the SePDAF is applied to accomplish the second filtering, and then achieving a high accuracy and stable trajectory with relatively low computational complexity. Moreover, the azimuth filtering accuracy will be promoted dramatically and the position filtering accuracy will also improve. Finally, simulations illustrate the effectiveness of the proposed method. PMID:27618058

  2. Mapping forested wetlands in the Great Zhan River Basin through integrating optical, radar, and topographical data classification techniques.

    PubMed

    Na, X D; Zang, S Y; Wu, C S; Li, W L

    2015-11-01

    Knowledge of the spatial extent of forested wetlands is essential to many studies including wetland functioning assessment, greenhouse gas flux estimation, and wildlife suitable habitat identification. For discriminating forested wetlands from their adjacent land cover types, researchers have resorted to image analysis techniques applied to numerous remotely sensed data. While with some success, there is still no consensus on the optimal approaches for mapping forested wetlands. To address this problem, we examined two machine learning approaches, random forest (RF) and K-nearest neighbor (KNN) algorithms, and applied these two approaches to the framework of pixel-based and object-based classifications. The RF and KNN algorithms were constructed using predictors derived from Landsat 8 imagery, Radarsat-2 advanced synthetic aperture radar (SAR), and topographical indices. The results show that the objected-based classifications performed better than per-pixel classifications using the same algorithm (RF) in terms of overall accuracy and the difference of their kappa coefficients are statistically significant (p<0.01). There were noticeably omissions for forested and herbaceous wetlands based on the per-pixel classifications using the RF algorithm. As for the object-based image analysis, there were also statistically significant differences (p<0.01) of Kappa coefficient between results performed based on RF and KNN algorithms. The object-based classification using RF provided a more visually adequate distribution of interested land cover types, while the object classifications based on the KNN algorithm showed noticeably commissions for forested wetlands and omissions for agriculture land. This research proves that the object-based classification with RF using optical, radar, and topographical data improved the mapping accuracy of land covers and provided a feasible approach to discriminate the forested wetlands from the other land cover types in forestry area.

  3. Multi-Mode, Multi-Antenna Software Defined Radar for Adaptive Tracking and Identification of Targets in Urban Environments

    DTIC Science & Technology

    2011-10-31

    signatures. Multiple - input multiple - output ( MIMO ) radars with spatially diverse transmitters and receivers have the potential to provide target...serve as a testbed to implement and test multi- input , multi- output ( MIMO ) and waveform adaptive radar concepts. Although many traditional multi... Multiple phase centers facilitate polarimetric and interferometric operation as well as serve as a testbed to implement and test multi- input , multi

  4. Classification of Traumatic Brain Injury for Targeted Therapies

    PubMed Central

    Saatman, Kathryn E.; Duhaime, Ann-Christine; Bullock, Ross; Maas, Andrew I.R.; Valadka, Alex

    2008-01-01

    Abstract The heterogeneity of traumatic brain injury (TBI) is considered one of the most significant barriers to finding effective therapeutic interventions. In October, 2007, the National Institute of Neurological Disorders and Stroke, with support from the Brain Injury Association of America, the Defense and Veterans Brain Injury Center, and the National Institute of Disability and Rehabilitation Research, convened a workshop to outline the steps needed to develop a reliable, efficient and valid classification system for TBI that could be used to link specific patterns of brain and neurovascular injury with appropriate therapeutic interventions. Currently, the Glasgow Coma Scale (GCS) is the primary selection criterion for inclusion in most TBI clinical trials. While the GCS is extremely useful in the clinical management and prognosis of TBI, it does not provide specific information about the pathophysiologic mechanisms which are responsible for neurological deficits and targeted by interventions. On the premise that brain injuries with similar pathoanatomic features are likely to share common pathophysiologic mechanisms, participants proposed that a new, multidimensional classification system should be developed for TBI clinical trials. It was agreed that preclinical models were vital in establishing pathophysiologic mechanisms relevant to specific pathoanatomic types of TBI and verifying that a given therapeutic approach improves outcome in these targeted TBI types. In a clinical trial, patients with the targeted pathoanatomic injury type would be selected using an initial diagnostic entry criterion, including their severity of injury. Coexisting brain injury types would be identified and multivariate prognostic modeling used for refinement of inclusion/exclusion criteria and patient stratification. Outcome assessment would utilize endpoints relevant to the targeted injury type. Advantages and disadvantages of currently available diagnostic, monitoring, and

  5. Nonlinear feature extraction and Bayesian mixture model approaches to target classification using MMW ISAR imagery: a preliminary study

    NASA Astrophysics Data System (ADS)

    Britton, Adrian; Copsey, Keith D.; Maskall, Guy T.; Webb, Andrew R.; West, Karl

    2000-07-01

    The problem we are addressing is one of generalization: given training data characterizing a set of targets (in specific configurations), how can we design a classifier that is robust to changes in target configuration and can generalize to other targets of the same generic class? The specific problem is identifying land vehicles from an inverse synthetic aperture radar image of the target. Issues in data modeling, experimental design and exploratory data analysis are discussed. Two complementary approaches are described: one that seeks to capture structure in the high- dimensional data space by projecting the data nonlinearly to a reduced dimensional feature space prior to classification; and a second that models the data in the data space using a Bayesian mixture model approach. Preliminary results for the mixture model approach are presented.

  6. Surveillance radars - State of the art, research and perspectives

    NASA Astrophysics Data System (ADS)

    Farina, A.; Galati, G.

    1985-08-01

    An assessment is made of the signal processing techniques currently employed by ground-based surveillance radars, and a projection is made of those techniques that are likely to be applied to such radars in the future. Further applications of such techniques in such diverse fields as multistatic and dispersed radars, AEW, and space-based radars are also considered. Attention is given to prospective technological advancements that will facilitate radar systems' future dealings with antiradiation missiles and stealth aircraft, which may include digital beam forming, adaptivity, and high resolution multidimensional processing and target classification. The advantages of multistatic radar are examined in detail.

  7. Deep transfer learning for automatic target classification: MWIR to LWIR

    NASA Astrophysics Data System (ADS)

    Ding, Zhengming; Nasrabadi, Nasser; Fu, Yun

    2016-05-01

    Publisher's Note: This paper, originally published on 5/12/2016, was replaced with a corrected/revised version on 5/18/2016. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. When dealing with sparse or no labeled data in the target domain, transfer learning shows its appealing performance by borrowing the supervised knowledge from external domains. Recently deep structure learning has been exploited in transfer learning due to its attractive power in extracting effective knowledge through multi-layer strategy, so that deep transfer learning is promising to address the cross-domain mismatch. In general, cross-domain disparity can be resulted from the difference between source and target distributions or different modalities, e.g., Midwave IR (MWIR) and Longwave IR (LWIR). In this paper, we propose a Weighted Deep Transfer Learning framework for automatic target classification through a task-driven fashion. Specifically, deep features and classifier parameters are obtained simultaneously for optimal classification performance. In this way, the proposed deep structures can extract more effective features with the guidance of the classifier performance; on the other hand, the classifier performance is further improved since it is optimized on more discriminative features. Furthermore, we build a weighted scheme to couple source and target output by assigning pseudo labels to target data, therefore we can transfer knowledge from source (i.e., MWIR) to target (i.e., LWIR). Experimental results on real databases demonstrate the superiority of the proposed algorithm by comparing with others.

  8. Sparse representation discretization errors in multi-sensor radar target motion estimation

    NASA Astrophysics Data System (ADS)

    Azodi, Hossein; Siart, Uwe; Eibert, Thomas F.

    2017-09-01

    In a multi-sensor radar for the estimation of the targets motion states, more than one module of transmitter and receiver are utilized to estimate the positions and velocities of targets, also known as motion states. By applying the compressed sensing (CS) reconstruction algorithms, the surveillance space needs to be discretized. The effect of the additive errors due to the discretization are studied in this paper. The errors are considered as an additive noise in the well-known under-determined CS problem. By employing properties of these errors, analytical models for its average and variance are derived. Numerous simulations are carried out to verify the analytical model empirically. Furthermore, the probability density functions of discretization errors are estimated. The analytical model is useful for the optimization of the performance, the efficiency and the success rate in CS reconstruction for radar as well as many other applications.

  9. Radar Constant-Modulus Waveform Design with Prior Information of the Extended Target and Clutter.

    PubMed

    Yue, Wenzhen; Zhang, Yan; Liu, Yimin; Xie, Jingwen

    2016-06-17

    Radar waveform design is of great importance for radar system performances and has drawn considerable attention recently. Constant modulus is an important waveform design consideration, both from the point of view of hardware realization and to allow for full utilization of the transmitter's power. In this paper, we consider the problem of constant-modulus waveform design for extended target detection with prior information about the extended target and clutter. At first, we propose an arbitrary-phase unimodular waveform design method via joint transmitter-receiver optimization. We exploit a semi-definite relaxation technique to transform an intractable non-convex problem into a convex problem, which can then be efficiently solved. Furthermore, quadrature phase shift keying waveform is designed, which is easier to implement than arbitrary-phase waveforms. Numerical results demonstrate the effectiveness of the proposed methods.

  10. Multiclass multiple kernel learning for HRRP-based radar target recognition

    NASA Astrophysics Data System (ADS)

    Guo, Yu; Xiao, Huaitie; Fan, Hongqi; Zhu, Yongfeng

    2017-06-01

    A novel machine learning method named multiclass multiple kernel learning based on support vector data description with negative (MMKL-NSVDD) is developed to classify the FFT-magnitude feature of complex high-resolution range profile (HRRP), motivated by the problem of radar automatic target recognition (RATR). The proposed method not only inherits the close nonlinear boundary advantage of SVDD-neg model, which is applied with no assumptions regarding to the distribution of data and prior information, but also incorporates multiple kernel into the mode, avoiding fussy choice of kernel parameters and fusing multiple kernel information. Hence, it leads to a remarkable improvement of recognition rate, demonstrated by experimental results based on HRRPs of four aircrafts. The MMKL-NSVDD is ideal for HRRPBased radar target recognition.

  11. Radar Constant-Modulus Waveform Design with Prior Information of the Extended Target and Clutter

    PubMed Central

    Yue, Wenzhen; Zhang, Yan; Liu, Yimin; Xie, Jingwen

    2016-01-01

    Radar waveform design is of great importance for radar system performances and has drawn considerable attention recently. Constant modulus is an important waveform design consideration, both from the point of view of hardware realization and to allow for full utilization of the transmitter’s power. In this paper, we consider the problem of constant-modulus waveform design for extended target detection with prior information about the extended target and clutter. At first, we propose an arbitrary-phase unimodular waveform design method via joint transmitter-receiver optimization. We exploit a semi-definite relaxation technique to transform an intractable non-convex problem into a convex problem, which can then be efficiently solved. Furthermore, quadrature phase shift keying waveform is designed, which is easier to implement than arbitrary-phase waveforms. Numerical results demonstrate the effectiveness of the proposed methods. PMID:27322275

  12. Target detection using radar images of an airport surface

    NASA Astrophysics Data System (ADS)

    Schultz, Hayden B.; Wyschogrod, Daniel; Harman, William H.; Sasiela, Richard J.; Bush, Richard W.

    1994-07-01

    Automation aids which increase the efficiency of the controller and enhance safety are being sought by the Federal Aviation Administration (FAA). This paper describes the target detection algorithms developed by the MIT Lincoln Laboratory as part of the airport surface traffic automation (ASTA) and runway surface safety light system (RSLS) programs sponsored by the FAA that were demonstrated at Logan International Airport in Boston, Mass. from September 1992 through December 1993. A companion paper to this conference describes the ASTA and RSLS system demonstration. Another companion paper describes the tracking algorithms. Real-time, parallel processing implementations of these surveillance algorithms are written in C++ on a Silicon Graphics Inc. Unix multiprocessor. The heavy reliance on commercial hardware, standard operating systems, object oriented design, and high-level computer languages allows a rapid transition from a research environment to a production environment.

  13. Broadband sensor system and technique for detection and classification of targets and subsurface targets

    NASA Astrophysics Data System (ADS)

    Goo, Gee-In

    1999-10-01

    In this paper, the author discusses a Broadband Bionic Sonar Sensor System and a signal processing technique for detection and identification of underwater targets. This bionic sonar system with the resonance detection technique for detection and identification of underwater objects appears to mimic a dolphin's sensory system. The dolphin's sonar system transmits a very short broadband pulse. It detects and classifies a target by processing the modulation of the echo's (back scattering) broadband spectrum. This spectral modulation is directly related to the target's natural resonance. Using the G-Transform technique, the author has successfully showed that target resonance exists and it is unique to target size, shape, structure and material composition. Furthermore, this natural resonance exists in both (active sonar) acoustic echoes, back scattering and (passive sonar) acoustic scattering in acoustic noise background. Using trained neural networks, these targets' resonances/signatures can be correctly identified for the respective targets. It is conceivable that a broadband radar system, similar to a dolphin's sonar system, can be developed for targets and subsurface targets.

  14. Through-the-Wall Localization of a Moving Target by Two Independent Ultra Wideband (UWB) Radar Systems

    PubMed Central

    Kocur, Dušan; Švecová, Mária; Rovňáková, Jana

    2013-01-01

    In the case of through-the-wall localization of moving targets by ultra wideband (UWB) radars, there are applications in which handheld sensors equipped only with one transmitting and two receiving antennas are applied. Sometimes, the radar using such a small antenna array is not able to localize the target with the required accuracy. With a view to improve through-the-wall target localization, cooperative positioning based on a fusion of data retrieved from two independent radar systems can be used. In this paper, the novel method of the cooperative localization referred to as joining intersections of the ellipses is introduced. This method is based on a geometrical interpretation of target localization where the target position is estimated using a properly created cluster of the ellipse intersections representing potential positions of the target. The performance of the proposed method is compared with the direct calculation method and two alternative methods of cooperative localization using data obtained by measurements with the M-sequence UWB radars. The direct calculation method is applied for the target localization by particular radar systems. As alternative methods of cooperative localization, the arithmetic average of the target coordinates estimated by two single independent UWB radars and the Taylor series method is considered. PMID:24021968

  15. Through-the-wall localization of a moving target by two independent ultra wideband (UWB) radar systems.

    PubMed

    Kocur, Dušan; Svecová, Mária; Rovňáková, Jana

    2013-09-09

    In the case of through-the-wall localization of moving targets by ultra wideband (UWB) radars, there are applications in which handheld sensors equipped only with one transmitting and two receiving antennas are applied. Sometimes, the radar using such a small antenna array is not able to localize the target with the required accuracy. With a view to improve through-the-wall target localization, cooperative positioning based on a fusion of data retrieved from two independent radar systems can be used. In this paper, the novel method of the cooperative localization referred to as joining intersections of the ellipses is introduced. This method is based on a geometrical interpretation of target localization where the target position is estimated using a properly created cluster of the ellipse intersections representing potential positions of the target. The performance of the proposed method is compared with the direct calculation method and two alternative methods of cooperative localization using data obtained by measurements with the M-sequence UWB radars. The direct calculation method is applied for the target localization by particular radar systems. As alternative methods of cooperative localization, the arithmetic average of the target coordinates estimated by two single independent UWB radars and the Taylor series method is considered.

  16. Stellar classification of CoRoT targets

    NASA Astrophysics Data System (ADS)

    Damiani, C.; Meunier, J.-C.; Moutou, C.; Deleuil, M.; Ysard, N.; Baudin, F.; Deeg, H.

    2016-11-01

    Context. The CoRoT mission was the first dedicated to the search for exoplanets from space. The CoRoT exoplanet channel observed about 163 600 targets to detect transiting planetary companions. In addition to the search for exoplanets, the extremely precise photometric time series provided by CoRoT for this vast number of stars is an invaluable resource for stellar studies. Because CoRoT targets are faint (11 ≤ r ≤ 16) and close to the galactic plane, only a small subsample has been observed spectroscopically. Consequently, the stellar classification of CoRoT targets required the design of a classification method suited for the needs and time frame of the mission. Aims: We describe the latest classification scheme used to derive the spectral type of CoRoT targets, which is based on broadband multi-colour photometry. We assess the accuracy of this spectral classification for the first time. Methods: We validated the method on simulated data. This allows the quantification of the effect of different sources of uncertainty on the spectral type. Using galaxy population synthesis models, we produced a synthetic catalogue that has the same properties as the CoRoT targets. In this way, we are able to predict typical errors depending on the estimated luminosity class and spectral type. We also compared our results with independent estimates of the spectral type. Cross-checking those results allows us to identify the systematics of the method and to characterise the stellar populations observed by CoRoT. Results: We find that the classification method performs better for stars that were observed during the mission-dedicated photometric ground-based campaigns.The luminosity class is wrong for less than 7% of the targets. Generally, the effective temperature of stars classified as early type (O, B, and A) is overestimated. Conversely, the temperature of stars classified as later type tends to be underestimated. This is mainly due to the adverse effect of interstellar

  17. Radar principles

    NASA Technical Reports Server (NTRS)

    Sato, Toru

    1989-01-01

    Discussed here is a kind of radar called atmospheric radar, which has as its target clear air echoes from the earth's atmosphere produced by fluctuations of the atmospheric index of refraction. Topics reviewed include the vertical structure of the atmosphere, the radio refractive index and its fluctuations, the radar equation (a relation between transmitted and received power), radar equations for distributed targets and spectral echoes, near field correction, pulsed waveforms, the Doppler principle, and velocity field measurements.

  18. Target-classification approach applied to active UXO sites

    NASA Astrophysics Data System (ADS)

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

    2013-06-01

    This study is designed to illustrate the discrimination performance at two UXO active sites (Oklahoma's Fort Sill and the Massachusetts Military Reservation) of a set of advanced electromagnetic induction (EMI) inversion/discrimination models which include the orthonormalized volume magnetic source (ONVMS), joint diagonalization (JD), and differential evolution (DE) approaches and whose power and flexibility greatly exceed those of the simple dipole model. The Fort Sill site is highly contaminated by a mix of the following types of munitions: 37-mm target practice tracers, 60-mm illumination mortars, 75-mm and 4.5'' projectiles, 3.5'', 2.36'', and LAAW rockets, antitank mine fuzes with and without hex nuts, practice MK2 and M67 grenades, 2.5'' ballistic windshields, M2A1-mines with/without bases, M19-14 time fuzes, and 40-mm practice grenades with/without cartridges. The site at the MMR site contains targets of yet different sizes. In this work we apply our models to EMI data collected using the MetalMapper (MM) and 2 × 2 TEMTADS sensors. The data for each anomaly are inverted to extract estimates of the extrinsic and intrinsic parameters associated with each buried target. (The latter include the total volume magnetic source or NVMS, which relates to size, shape, and material properties; the former includes location, depth, and orientation). The estimated intrinsic parameters are then used for classification performed via library matching and the use of statistical classification algorithms; this process yielded prioritized dig-lists that were submitted to the Institute for Defense Analyses (IDA) for independent scoring. The models' classification performance is illustrated and assessed based on these independent evaluations.

  19. A Novel Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking in an LPI Radar Network

    PubMed Central

    She, Ji; Wang, Fei; Zhou, Jianjiang

    2016-01-01

    Radar networks are proven to have numerous advantages over traditional monostatic and bistatic radar. With recent developments, radar networks have become an attractive platform due to their low probability of intercept (LPI) performance for target tracking. In this paper, a joint sensor selection and power allocation algorithm for multiple-target tracking in a radar network based on LPI is proposed. It is found that this algorithm can minimize the total transmitted power of a radar network on the basis of a predetermined mutual information (MI) threshold between the target impulse response and the reflected signal. The MI is required by the radar network system to estimate target parameters, and it can be calculated predictively with the estimation of target state. The optimization problem of sensor selection and power allocation, which contains two variables, is non-convex and it can be solved by separating power allocation problem from sensor selection problem. To be specific, the optimization problem of power allocation can be solved by using the bisection method for each sensor selection scheme. Also, the optimization problem of sensor selection can be solved by a lower complexity algorithm based on the allocated powers. According to the simulation results, it can be found that the proposed algorithm can effectively reduce the total transmitted power of a radar network, which can be conducive to improving LPI performance. PMID:28009819

  20. A Novel Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking in an LPI Radar Network.

    PubMed

    She, Ji; Wang, Fei; Zhou, Jianjiang

    2016-12-21

    Radar networks are proven to have numerous advantages over traditional monostatic and bistatic radar. With recent developments, radar networks have become an attractive platform due to their low probability of intercept (LPI) performance for target tracking. In this paper, a joint sensor selection and power allocation algorithm for multiple-target tracking in a radar network based on LPI is proposed. It is found that this algorithm can minimize the total transmitted power of a radar network on the basis of a predetermined mutual information (MI) threshold between the target impulse response and the reflected signal. The MI is required by the radar network system to estimate target parameters, and it can be calculated predictively with the estimation of target state. The optimization problem of sensor selection and power allocation, which contains two variables, is non-convex and it can be solved by separating power allocation problem from sensor selection problem. To be specific, the optimization problem of power allocation can be solved by using the bisection method for each sensor selection scheme. Also, the optimization problem of sensor selection can be solved by a lower complexity algorithm based on the allocated powers. According to the simulation results, it can be found that the proposed algorithm can effectively reduce the total transmitted power of a radar network, which can be conducive to improving LPI performance.

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

    PubMed

    Nguyen, Van-Han; Pyun, Jae-Young

    2015-03-19

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

  2. Location Detection and Tracking of Moving Targets by a 2D IR-UWB Radar System

    PubMed Central

    Nguyen, Van-Han; Pyun, Jae-Young

    2015-01-01

    In indoor environments, the Global Positioning System (GPS) and long-range tracking radar systems are not optimal, because of signal propagation limitations in the indoor environment. In recent years, the use of ultra-wide band (UWB) technology has become a possible solution for object detection, localization and tracking in indoor environments, because of its high range resolution, compact size and low cost. This paper presents improved target detection and tracking techniques for moving objects with impulse-radio UWB (IR-UWB) radar in a short-range indoor area. This is achieved through signal-processing steps, such as clutter reduction, target detection, target localization and tracking. In this paper, we introduce a new combination consisting of our proposed signal-processing procedures. In the clutter-reduction step, a filtering method that uses a Kalman filter (KF) is proposed. Then, in the target detection step, a modification of the conventional CLEAN algorithm which is used to estimate the impulse response from observation region is applied for the advanced elimination of false alarms. Then, the output is fed into the target localization and tracking step, in which the target location and trajectory are determined and tracked by using unscented KF in two-dimensional coordinates. In each step, the proposed methods are compared to conventional methods to demonstrate the differences in performance. The experiments are carried out using actual IR-UWB radar under different scenarios. The results verify that the proposed methods can improve the probability and efficiency of target detection and tracking. PMID:25808773

  3. Moving target detection method for bistatic radar using random stepped-frequency chirp signal

    NASA Astrophysics Data System (ADS)

    Lin, Caiyong; Tian, Ruiqi; Wang, Dinghe; Bao, Qinglong; Chen, Zengping

    2016-10-01

    As random stepped-frequency chirp (RSFC) signal is used in wide-band radar applications such as synthetic aperture radar (SAR) and inverse SAR. RSFC has advantages over the linear stepped-frequency chirp, including suppressing the range ambiguity, decoupling the range-Doppler coupling, and reducing the signal interference. RSFC is usually descrambled and then fed to the inverse fast Fourier transform (IFFT) to achieve a coherent integration as well as a high-resolution range. However, this method needs frequency descrambling and accurate velocity pre-estimation for moving target detection. We propose a coherent integration method based on time-dechirping for bistatic radar. This method can detect moving targets without frequency descrambling or accurate velocity pre-estimation. This paper first models the target echo mathematically and outlines the difficulties associated with the processing of IFFT for RSFC. Then the detailed principles of the proposed method are introduced and the flowchart is given. Finally, numerical simulations are conducted to verify the effectiveness of the proposed method and show its detecting ability in the presence of noise.

  4. Acoustic target detection and classification using neural networks

    NASA Technical Reports Server (NTRS)

    Robertson, James A.; Conlon, Mark

    1993-01-01

    A neural network approach to the classification of acoustic emissions of ground vehicles and helicopters is demonstrated. Data collected during the Joint Acoustic Propagation Experiment conducted in July of l991 at White Sands Missile Range, New Mexico was used to train a classifier to distinguish between the spectrums of a UH-1, M60, M1 and M114. An output node was also included that would recognize background (i.e. no target) data. Analysis revealed specific hidden nodes responding to the features input into the classifier. Initial results using the neural network were encouraging with high correct identification rates accompanied by high levels of confidence.

  5. Supervised Classification Method with Efficient Filter Techniques to Detect Anomalies on Earthen Levees Using Synthetic Aperture Radar Imagery

    NASA Astrophysics Data System (ADS)

    Marapareddy, Ramakalavathi; Anastoos, James V.; Younan, Nicolas H.

    2016-08-01

    The dynamics of surface and subsurface water events can lead to slope instability resulting in slough slides or other anomalies on earthen levees. These slough slides are the primary cause for creating levee areas which are vulnerable to seepage and failure during high water events. Early detection of these anomalies by a remote sensing approach could save time versus direct assessment. In this paper, we implemented a supervised classification algorithm the minimum distance classifier with a majority filter and morphology filter for the identification of anomalies on levees using polarimetric Synthetic Aperture Radar (polSAR) data. This study employed remote sensing data from the NASA Jet Propulsion Laboratory's (JPL's) Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) instrument, using its fully quad-polarimetric L-band polSAR data. The study area is a section of the lower Mississippi River in the southern USA.

  6. Fixed lag smoothing target tracking in clutter for a high pulse repetition frequency radar

    NASA Astrophysics Data System (ADS)

    Khan, Uzair; Shi, Yi Fang; Song, Taek Lyul

    2015-12-01

    A new method to smooth the target hybrid state with Gaussian mixture measurement likelihood-integrated track splitting (GMM-ITS) in the presence of clutter for a high pulse repetition frequency (HPRF) radar is proposed. This method smooths the target state at fixed lag N and considers all feasible multi-scan target existence sequences in the temporal window of scans in order to smooth the target hybrid state. The smoothing window can be of any length N. The proposed method to smooth the target hybrid state at fixed lag is also applied to the enhanced multiple model (EMM) tracking algorithm. Simulation results indicate that the performance of fixed lag smoothing GMM-ITS significantly improves false track discrimination and root mean square errors (RMSEs).

  7. Analysis of influential factors on a space target's laser radar cross-section

    NASA Astrophysics Data System (ADS)

    Han, Yi; Sun, Huayan; Guo, Huichao

    2014-03-01

    This paper utilises the idea of theoretical analysis to introduce a fast and visual laser radar cross-section (LRCS) calculation method for space targets that is implemented with OpenGL. We chose the cube, cylinder and cone as targets based on the general characteristics of satellite shapes. The four-parameter mono-station BRDF is used, and we assume the surface materials are either purely diffuse, purely specular or mixed. The degree of influence on a target's total LRCS of the target's shape and size and the surface materials' BRDF are described. We describe the general laws governing influential factors by comparing simulated results. These conclusions can provide a reference for new research directions and methods to determine a target's laser scattering characteristics.

  8. Passive radar tracking of a maneuvering target using variable structure multiple-model algorithm

    NASA Astrophysics Data System (ADS)

    Mao, Yunxiang; Zhou, Xiaohui; Zhang, Jin

    2013-03-01

    The variable structure multiple-model (VSMM) algorithm to passive radar maneuvering target tracking problem is considered. A new VSMM design, expected mode augmentation based on likely model set (LMS-EMA) algorithm is presented. The LMS-EMA algorithm adaptively determines the fixed grid model set using likely model set (LMS) algorithm, and generates the expected mode based on this set. Then, the union of fixed grid model set and expected model is used to perform multiple-model estimation. The performance of the LMS-EMA algorithm is evaluated via simulation of a highly maneuvering target tracking problem.

  9. Classification of rain types using drop size distributions and polarimetric radar: Case study of a 2014 flooding event in Korea

    NASA Astrophysics Data System (ADS)

    You, C.-H.; Lee, D.-I.; Kang, M.-Y.; Kim, H.-J.

    2016-11-01

    To classify precipitation types as either convective or stratiform, drop size distributions (DSDs) measured by the Parsivel (PARticle size VELocity) instrument, and DSD parameters including median volume diameter (D0) and normalized number concentration (Nw) retrieved by S-band polarimetric radar (BSL), were analyzed for a heavy rainfall event that occurred in southern Korea on 25 August 2014. The rainfall system was clearly identified as stratiform or convective rain at various times of day, at measurement sites at Changwon and Busan. New rainfall classification lines were derived from the Parsivel and BSL data, and were compared with existing classification methods based on climatological rainfall data. The classification methods using logNw-D0, logN0-rainrate, and slope-rainrate domain proposed in previous two studies performed well when applied to the new data if the slope and/or intercept values were changed. Another method using logN0-slope domain was not possible to classify the precipitation types well in the study area, as the best-fit line could not be obtained. The average measured D0 and Nw values obtained from polarimetric radar were compared with climatological precipitation data, measured in both the tropics and mid-latitudes. And new separation line was obtained for the rainfall at the southern part of Korea.

  10. Spencer Range live-site portable EMI sensors target classification

    NASA Astrophysics Data System (ADS)

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

    2013-06-01

    ESTCP live-site UXO classification results are presented for cued data collected by the Man Portable Vector (MPV) handheld sensor, at the Former Spencer Artillery Range in Tennessee. The site was contaminated with assorted munitions, ranging in caliber from 37 mm to 155 mm. The MPV data were collected in two areas: dynamic and wooded. The data sets are inverted using an advanced forward EMI model, the ortho-normalized volume magnetic source (ONVMS) model, combined with a direct-search optimization algorithm known as differential evolution. All data are inverted assuming one, two, and three sources. For each inversion, the targets' intrinsic parameters are extracted and used in a library matching technique. Anomalies are classified as targets of interest (TOI) or clutter. Prioritized dig lists were constructed and submitted to the Institute for Defense Analysis for independent scoring. The result revealed an excellent classification performance by the advanced EMI models when applied to the Spencer Range MPV data. This paper describes the MPV sensor and the advanced models and demonstrates the Receiver Operating Characteristic curves for the cued MPV data collected at the Spencer Range.

  11. Imaging targets embedded in a lossy half space with Synthetic Aperture Radar

    SciTech Connect

    Doerry, A.W.; Brock, B.C.; Boverie, B.; Cress, D.

    1994-05-01

    This paper addresses theoretical aspects of forming images from an airborne Synthetic Aperture Radar (SAR) of targets buried below the earth`s surface. Soil is generally a lossy, dispersive medium, with wide ranging variability in these attributes depending on soil type, moisture content, and a host of other physical properties. Focussing a SAR subsurface image presents new dimensions of complexity relative to its surface-image counterpart, even when the soil`s properties are known. This paper treats the soil as a lossy, dispersive half space, and presents a practical model for the radar echo-delay time to point scatterers within it. This model is then used to illustrate effects of refraction, dispersion, and attenuation on a SAR`s phase histories, and the resulting image. Various data collection geometries and processing strategies are examined for both 2-Dimensional and 3-Dimensional SAR images. The conclusions from this work are that (1) focussing a SAR image must generally take into account both refraction and dispersion, (2) resolving targets at different depths in lossy soils requires perhaps unprecedented sidelobe attenuation, that for some soils may only be achievable with specialized window functions, (3) the impulse response of the soil itself places a practical limit on the usable bandwidth of the radar, and (4) dynamic ranges and sensitivities will need to be orders of magnitude greater than typical surface-imaging SARs, leading to significant impact on SAR parameters, for example compressing the usable range of pulse repetition frequencies (PRFs).

  12. Improving angular resolution with Scan-MUSIC algorithm for real complex targets using 35-GHz millimeter-wave radar

    NASA Astrophysics Data System (ADS)

    Ly, Canh

    2004-08-01

    Scan-MUSIC algorithm, developed by the U.S. Army Research Laboratory (ARL), improves angular resolution for target detection with the use of a single rotatable radar scanning the angular region of interest. This algorithm has been adapted and extended from the MUSIC algorithm that has been used for a linear sensor array. Previously, it was shown that the SMUSIC algorithm and a Millimeter Wave radar can be used to resolve two closely spaced point targets that exhibited constructive interference, but not for the targets that exhibited destructive interference. Therefore, there were some limitations of the algorithm for the point targets. In this paper, the SMUSIC algorithm is applied to a problem of resolving real complex scatterer-type targets, which is more useful and of greater practical interest, particular for the future Army radar system. The paper presents results of the angular resolution of the targets, an M60 tank and an M113 Armored Personnel Carrier (APC), that are within the mainlobe of a Κα-band radar antenna. In particular, we applied the algorithm to resolve centroids of the targets that were placed within the beamwidth of the antenna. The collected coherent data using the stepped-frequency radar were compute magnitudely for the SMUSIC calculation. Even though there were significantly different signal returns for different orientations and offsets of the two targets, we resolved those two target centroids when they were as close as about 1/3 of the antenna beamwidth.

  13. 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

  14. Theoretical and computational analysis of the quantum radar cross section for simple geometrical targets

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

    The concept of the quantum radar cross section (QRCS) has generated interest due to its promising feature of enhanced side lobe target visibility in comparison to the classical radar cross section. Researchers have simulated the QRCS for very limited geometries and even developed approximations to reduce the computational complexity of the simulations. This paper develops an alternate theoretical framework for calculating the QRCS. This new framework yields an alternative form of the QRCS expression in terms of Fourier transforms. This formulation is much easier to work with mathematically and allows one to derive analytical solutions for various geometries, which provides an explanation for the aforementioned sidelobe advantage. We also verify the resulting equations by comparing with numerical simulations, as well as provide an error analysis of these simulations to ensure the accuracy of the results. Comparison of our simulation results with the analytical solutions reveal that they agree with one another extremely well.

  15. Multi-Frequency Target Detection Techniques for DVB-T Based Passive Radar Sensors.

    PubMed

    Martelli, Tatiana; Colone, Fabiola; Tilli, Enrico; Di Lallo, Annarita

    2016-09-28

    This paper investigates the possibility to improve target detection capability in a DVB-T- based passive radar sensor by jointly exploiting multiple digital television channels broadcast by the same transmitter of opportunity. Based on the remarkable results obtained by such a multi-frequency approach using other signals of opportunity (i.e., FM radio broadcast transmissions), we propose appropriate modifications to the previously devised signal processing techniques for them to be effective in the newly considered scenarios. The resulting processing schemes are extensively applied against experimental DVB-T-based passive radar data pertaining to different surveillance applications. The obtained results clearly show the effectiveness of the proposed multi-frequency approaches and demonstrate their suitability for application in the considered scenarios.

  16. Multi-Frequency Target Detection Techniques for DVB-T Based Passive Radar Sensors

    PubMed Central

    Martelli, Tatiana; Colone, Fabiola; Tilli, Enrico; Di Lallo, Annarita

    2016-01-01

    This paper investigates the possibility to improve target detection capability in a DVB-T- based passive radar sensor by jointly exploiting multiple digital television channels broadcast by the same transmitter of opportunity. Based on the remarkable results obtained by such a multi-frequency approach using other signals of opportunity (i.e., FM radio broadcast transmissions), we propose appropriate modifications to the previously devised signal processing techniques for them to be effective in the newly considered scenarios. The resulting processing schemes are extensively applied against experimental DVB-T-based passive radar data pertaining to different surveillance applications. The obtained results clearly show the effectiveness of the proposed multi-frequency approaches and demonstrate their suitability for application in the considered scenarios. PMID:27690036

  17. Using Centimetric Visible Imagery Obtained from an UAV Quadrotor for Classification of Radar Images

    NASA Astrophysics Data System (ADS)

    Gademer, A.; Petitpas, B.; Beaudoin, L.; Roux, M.; Tanzi, T.; Riera, B.; Rudant, J. P.

    2010-12-01

    Interpreting remote sensing images, and SAR images in particular, is often a challenging task. The aim of this article is to explore how visible centimetre information taken from an Unmanned Vehicle System (UAS) could help in interpretation of radar images. After nearly two decades of operational use, it is very common to work with radar images like the ERS ones. Obtaining visible centimetre images on a particular scene is a more complicated task. To face this difficulty, we have developed a small scale UAV dedicated to low altitude aerial remote sensing. From the stereo pair acquired, we have computed dense disparity maps and deduced some roughness parameters. As there is a direct link between the soil roughness, the soil moisture and the radar backscattering, we think that theses measures can have a high added-valued to interpret generic radar images and even the amplitude and coherence images obtained during the interferometric treatment.

  18. Quad-polarized synthetic aperture radar and multispectral data classification using classification and regression tree and support vector machine-based data fusion system

    NASA Astrophysics Data System (ADS)

    Bigdeli, Behnaz; Pahlavani, Parham

    2017-01-01

    Interpretation of synthetic aperture radar (SAR) data processing is difficult because the geometry and spectral range of SAR are different from optical imagery. Consequently, SAR imaging can be a complementary data to multispectral (MS) optical remote sensing techniques because it does not depend on solar illumination and weather conditions. This study presents a multisensor fusion of SAR and MS data based on the use of classification and regression tree (CART) and support vector machine (SVM) through a decision fusion system. First, different feature extraction strategies were applied on SAR and MS data to produce more spectral and textural information. To overcome the redundancy and correlation between features, an intrinsic dimension estimation method based on noise-whitened Harsanyi, Farrand, and Chang determines the proper dimension of the features. Then, principal component analysis and independent component analysis were utilized on stacked feature space of two data. Afterward, SVM and CART classified each reduced feature space. Finally, a fusion strategy was utilized to fuse the classification results. To show the effectiveness of the proposed methodology, single classification on each data was compared to the obtained results. A coregistered Radarsat-2 and WorldView-2 data set from San Francisco, USA, was available to examine the effectiveness of the proposed method. The results show that combinations of SAR data with optical sensor based on the proposed methodology improve the classification results for most of the classes. The proposed fusion method provided approximately 93.24% and 95.44% for two different areas of the data.

  19. A study of some FMCW radar algorithms for target location at low frequencies

    NASA Astrophysics Data System (ADS)

    Sandström, Sven-Erik; Akeab, Imad K.

    2016-10-01

    FMCW (frequency-modulated continuous wave) radar is a simple and inexpensive technique for target location. The resolution is given by the available bandwidth and the directivity of the antenna. Resolution is not a problem at high frequencies, while at low frequencies (the HF and VHF band), and especially for mobile platforms, the required size of the antenna becomes impractical. In order to obtain the bearing of the targets, without relying on directivity, one may use a simple two-dimensional trilateration method that involves several platforms. Since this approach covers an area, rather than a sector, the range is reduced to some tens of kilometers. The VHF band and a bandwidth below 10 MHz is a good choice if the priority is to reduce radio interference. Fast targets, corresponding to a significant Doppler shift, have not been considered. The problem of ghost targets has been studied for both monostatic and multistatic radar. When there is a confluence of echoes, more bandwidth is required to maintain the accuracy of a few meters that is normally obtained in the simulation.

  20. Autonomous underwater vehicle adaptive path planning for target classification

    NASA Astrophysics Data System (ADS)

    Edwards, Joseph R.; Schmidt, Henrik

    2002-11-01

    Autonomous underwater vehicles (AUVs) are being rapidly developed to carry sensors into the sea in ways that have previously not been possible. The full use of the vehicles, however, is still not near realization due to lack of the true vehicle autonomy that is promised in the label (AUV). AUVs today primarily attempt to follow as closely as possible a preplanned trajectory. The key to increasing the autonomy of the AUV is to provide the vehicle with a means to make decisions based on its sensor receptions. The current work examines the use of active sonar returns from mine-like objects (MLOs) as a basis for sensor-based adaptive path planning, where the path planning objective is to discriminate between real mines and rocks. Once a target is detected in the mine hunting phase, the mine classification phase is initialized with a derivative cost function to emphasize signal differences and enhance classification capability. The AUV moves adaptively to minimize the cost function. The algorithm is verified using at-sea data derived from the joint MIT/SACLANTCEN GOATS experiments and advanced acoustic simulation using SEALAB. The mission oriented operating system (MOOS) real-time simulator is then used to test the onboard implementation of the algorithm.

  1. Automated target classification in high resolution dual frequency sonar imagery

    NASA Astrophysics Data System (ADS)

    Aridgides, Tom; Fernández, Manuel

    2007-04-01

    An improved computer-aided-detection / computer-aided-classification (CAD/CAC) processing string has been developed. The classified objects of 2 distinct strings are fused using the classification confidence values and their expansions as features, and using "summing" or log-likelihood-ratio-test (LLRT) based fusion rules. The utility of the overall processing strings and their fusion was demonstrated with new high-resolution dual frequency sonar imagery. Three significant fusion algorithm improvements were made. First, a nonlinear 2nd order (Volterra) feature LLRT fusion algorithm was developed. Second, a Box-Cox nonlinear feature LLRT fusion algorithm was developed. The Box-Cox transformation consists of raising the features to a to-be-determined power. Third, a repeated application of a subset feature selection / feature orthogonalization / Volterra feature LLRT fusion block was utilized. It was shown that cascaded Volterra feature LLRT fusion of the CAD/CAC processing strings outperforms summing, baseline single-stage Volterra and Box-Cox feature LLRT algorithms, yielding significant improvements over the best single CAD/CAC processing string results, and providing the capability to correctly call the majority of targets while maintaining a very low false alarm rate. Additionally, the robustness of cascaded Volterra feature fusion was demonstrated, by showing that the algorithm yields similar performance with the training and test sets.

  2. Compressive Sensing for Radar and Radar Sensor Networks

    DTIC Science & Technology

    2013-12-02

    27] Hong-Sam Le, Qilian Liang, “Joint Multi-target Identification and Classification in Cognitive Radar Sensor Networks,” International Journal of Wireless Information Networks , vol...Networks," International Journal of Wireless Information Networks , vol. 18, no. 2, pp. 100-107, 2011. 8. Sukhvinder Singh, Qilian Liang, Dechang

  3. The effect of target and non-target similarity on neural classification performance: a boost from confidence

    PubMed Central

    Marathe, Amar R.; Ries, Anthony J.; Lawhern, Vernon J.; Lance, Brent J.; Touryan, Jonathan; McDowell, Kaleb; Cecotti, Hubert

    2015-01-01

    Brain computer interaction (BCI) technologies have proven effective in utilizing single-trial classification algorithms to detect target images in rapid serial visualization presentation tasks. While many factors contribute to the accuracy of these algorithms, a critical aspect that is often overlooked concerns the feature similarity between target and non-target images. In most real-world environments there are likely to be many shared features between targets and non-targets resulting in similar neural activity between the two classes. It is unknown how current neural-based target classification algorithms perform when qualitatively similar target and non-target images are presented. This study address this question by comparing behavioral and neural classification performance across two conditions: first, when targets were the only infrequent stimulus presented amongst frequent background distracters; and second when targets were presented together with infrequent non-targets containing similar visual features to the targets. The resulting findings show that behavior is slower and less accurate when targets are presented together with similar non-targets; moreover, single-trial classification yielded high levels of misclassification when infrequent non-targets are included. Furthermore, we present an approach to mitigate the image misclassification. We use confidence measures to assess the quality of single-trial classification, and demonstrate that a system in which low confidence trials are reclassified through a secondary process can result in improved performance. PMID:26347597

  4. The effect of target and non-target similarity on neural classification performance: a boost from confidence.

    PubMed

    Marathe, Amar R; Ries, Anthony J; Lawhern, Vernon J; Lance, Brent J; Touryan, Jonathan; McDowell, Kaleb; Cecotti, Hubert

    2015-01-01

    Brain computer interaction (BCI) technologies have proven effective in utilizing single-trial classification algorithms to detect target images in rapid serial visualization presentation tasks. While many factors contribute to the accuracy of these algorithms, a critical aspect that is often overlooked concerns the feature similarity between target and non-target images. In most real-world environments there are likely to be many shared features between targets and non-targets resulting in similar neural activity between the two classes. It is unknown how current neural-based target classification algorithms perform when qualitatively similar target and non-target images are presented. This study address this question by comparing behavioral and neural classification performance across two conditions: first, when targets were the only infrequent stimulus presented amongst frequent background distracters; and second when targets were presented together with infrequent non-targets containing similar visual features to the targets. The resulting findings show that behavior is slower and less accurate when targets are presented together with similar non-targets; moreover, single-trial classification yielded high levels of misclassification when infrequent non-targets are included. Furthermore, we present an approach to mitigate the image misclassification. We use confidence measures to assess the quality of single-trial classification, and demonstrate that a system in which low confidence trials are reclassified through a secondary process can result in improved performance.

  5. Analysis of the Chirplet Transform-Based Algorithm for Radar Detection of Accelerated Targets

    NASA Astrophysics Data System (ADS)

    Galushko, V. G.; Vavriv, D. M.

    2017-06-01

    Purpose: Efficiency analysis of an optimal algorithm of chirp signal processing based on the chirplet transform as applied to detection of radar targets in uniformly accelerated motion. Design/methodology/approach: Standard methods of the optimal filtration theory are used to investigate the ambiguity function of chirp signals. Findings: An analytical expression has been derived for the ambiguity function of chirp signals that is analyzed with respect to detection of radar targets moving at a constant acceleration. Sidelobe level and characteristic width of the ambiguity function with respect to the coordinates frequency and rate of its change have been estimated. The gain in the signal-to-noise ratio has been assessed that is provided by the algorithm under consideration as compared with application of the standard Fourier transform to detection of chirp signals against a “white” noise background. It is shown that already with a comparatively small (<20) number of processing channels (elementary filters with respect to the frequency change rate) the gain in the signal-tonoise ratio exceeds 10 dB. A block diagram of implementation of the algorithm under consideration is suggested on the basis of a multichannel weighted Fourier transform. Recommendations as for selection of the detection algorithm parameters have been developed. Conclusions: The obtained results testify to efficiency of application of the algorithm under consideration to detection of radar targets moving at a constant acceleration. Nevertheless, it seems expedient to perform computer simulations of its operability with account for the noise impact along with trial measurements in real conditions.

  6. Polarimetric synthetic aperture radar application for tropical peatlands classification: a case study in Siak River Transect, Riau Province, Indonesia

    NASA Astrophysics Data System (ADS)

    Novresiandi, Dandy Aditya; Nagasawa, Ryota

    2017-01-01

    Mapping spatial distributions of tropical peatlands is important for properly estimating carbon emissions and for providing information that aids in the sustainable management of tropical peatlands, particularly in Indonesia. This study evaluated the performance of phased array type L-band synthetic aperture radar (SAR) (PALSAR) dual-polarization and fully polarimetric data for tropical peatlands classification. The study area was in Siak River Transect, Riau Province, Indonesia, a rapidly developing region, where the peatland has been intensively converted mostly into oil palm plantations over the last two decades. Thus, polarimetric features derived after polarimetric decompositions, backscatter coefficients measurements, and the radar vegetation index were evaluated to classify tropical peatlands using the decision tree classifier. Overall, polarimetric features generated by the combination of dual-polarization and fully polarimetric data yielded an overall accuracy (OA) of 69% and a kappa coefficient (K) of 0.57. The integration of an additional feature, "distance to river," to the algorithm increased the OA to 76% and K to 0.66. These results indicated that the methodology in this study might serve as an efficient tool in tropical peatlands classification, especially when involving the use of L-band SAR dual-polarization and fully polarimetric data.

  7. MIMO radar for through-wall target identification in single and two wall scenarios

    NASA Astrophysics Data System (ADS)

    Gebhardt, Evan T.; Narayanan, Ram M.; Broderick, Sean P.

    2016-05-01

    MIMO radar provides improvement over traditional phased array radars for through wall imaging. By transmitting independent waveforms from a transmit array to a receive array an effective virtual array is created. This array has improved degrees of freedom over phased arrays and mono-static MIMO systems. This virtual array allows us to achieve the same effective aperture length as a phased array with less elements because the virtual array can be described as the convolution of transmit and receive array positions. In addition, data from multiple walls of the same room can be used to collect target information. If two walls are perpendicular to each other and the geometry of transmit and receive arrays is known, then data can be processed independently of each other. Since the geometry of the arrays is known, a target scene can be created where the two data sets overlap. The overlapped scene can then be processed so that image artifacts that do not correlate between the data sets can be excised. The result gives improved target detection, reduction in false alarms, robustness to noise, and robustness against errors such as improperly aligned antennas.

  8. Measurement of projectile trajectory in dielectric target with micropower-impluse radar

    SciTech Connect

    Baum, D.W.; Kuklo, R.M.; Rosenbury, E.T.; Simonson, S.C.

    1997-11-20

    The micropower-impulse radar has been adapted for non-intrusive tracking of projectiles in dielectric targets. The main application of this technique is intended to be the validation of continuum mechanics simulation codes and material models used in the study of the interaction between high-velocity penetrators and concrete targets. Two experiments have been conducted in which a gun-launched 90-mm-diameter projectile was fired at velocities of 160 and 230 m/s into a cubical box filled with dry sand and tracked with the micropower-impulse radar. The system was adjusted so that a 2-m range in sand was divided into 511 timing intervals, which were swept every 0.1 ms. As the projectile took approximately 40 ms to come to rest this meant that there were 400measurements of its position. The CALE continuum mechanics simulation was used to model the projectile motion in the target, and close agreement was found with the measured trajectory.

  9. Nonlinear techniques in optical synthetic aperture radar image generation and target recognition.

    PubMed

    Weaver, S; Wagner, K

    1995-07-10

    One of the most successful optical signal-processing applications to date has been the use of optical processors to convert synthetic aperture radar (SAR) data into images of the radar reflectivity of the ground. We have demonstrated real-time input to a high-space-bandwidth optical SAR imagegeneration system by using a dynamic organic holographic recording medium and SAR phase-history data. Real-time speckle reduction in optically processed SAR imagery has been accomplished by the use of multilook averaging to achieve nonlinear modulus-squared accumulation of subaperture images. We designed and assembled an all-optical system that accomplished real-time target recognition in SAR imagery. This system employed a simple square-law nonlinearity in the form of an optically addressed spatial light modulator at the SAR image plane to remove the effects of speckle phase profiles returned from complex SAR targets. The detection stage enabled the creation of an optical SAR automatic target recognition system as a nonlinear cascade of an optical SAR image generator and an optical correlator.

  10. Modified linear predictive coding approach for moving target tracking by Doppler radar

    NASA Astrophysics Data System (ADS)

    Ding, Yipeng; Lin, Xiaoyi; Sun, Ke-Hui; Xu, Xue-Mei; Liu, Xi-Yao

    2016-07-01

    Doppler radar is a cost-effective tool for moving target tracking, which can support a large range of civilian and military applications. A modified linear predictive coding (LPC) approach is proposed to increase the target localization accuracy of the Doppler radar. Based on the time-frequency analysis of the received echo, the proposed approach first real-time estimates the noise statistical parameters and constructs an adaptive filter to intelligently suppress the noise interference. Then, a linear predictive model is applied to extend the available data, which can help improve the resolution of the target localization result. Compared with the traditional LPC method, which empirically decides the extension data length, the proposed approach develops an error array to evaluate the prediction accuracy and thus, adjust the optimum extension data length intelligently. Finally, the prediction error array is superimposed with the predictor output to correct the prediction error. A series of experiments are conducted to illustrate the validity and performance of the proposed techniques.

  11. Occluded target viewing and identification high-resolution 2D imaging laser radar

    NASA Astrophysics Data System (ADS)

    Grasso, Robert J.; Dippel, George F.; Cecchetti, Kristen D.; Wikman, John C.; Drouin, David P.; Egbert, Paul I.

    2007-09-01

    BAE SYSTEMS has developed a high-resolution 2D imaging laser radar (LADAR) system that has proven its ability to detect and identify hard targets in occluded environments, through battlefield obscurants, and through naturally occurring image-degrading atmospheres. Limitations of passive infrared imaging for target identification using medium wavelength infrared (MWIR) and long wavelength infrared (LWIR) atmospheric windows are well known. Of particular concern is that as wavelength is increased the aperture must be increased to maintain resolution, hence, driving apertures to be very larger for long-range identification; impractical because of size, weight, and optics cost. Conversely, at smaller apertures and with large f-numbers images may become photon starved with long integration times. Here, images are most susceptible to distortion from atmospheric turbulence, platform vibration, or both. Additionally, long-range identification using passive thermal imaging is clutter limited arising from objects in close proximity to the target object.

  12. A revisitation of the phenomenological approach with applications to radar target decomposition

    NASA Astrophysics Data System (ADS)

    Huynen, J. R.

    1982-05-01

    This report highlights some results of a phenomenological approach to radar targets, with applications. The approach grew out of the common sense realization that only those target data are acceptable for discrimination and identification purposes which can be shown to relate in a physically meaningful way to basic target structure. Only then can data, often gathered at great expense, obtained for one type of system, be expected to be useful productively for a new system and hence improve efficiency and cost factors. Although these comments are almost self-evident and common sensical in nature, examples are given to show how this systematic approach has an important effect on the mathematical and practical development toward target identification (inverse) problems. The effect of antenna and target orientation angle on corrupting target information is stressed, in contrast to common practice to allow single H or V polarization data to be accepted as meaningful. The report summarizes the general target decomposition theorems, proved by the author in 1970. It shows that a single-coherent object is electromagnetically irreducible (it cannot be broken down mathematically as the incoherent sum of the smaller parts without violating physical principles). All this opens up new vistas for optimal signal processing schemes which extend the present predominantly scalar case to include vector scattering problems. It is hoped that by these efforts improved reliability with reduced costs for target discrimination and identification purposes can be achieved.

  13. Binary integration nonparametric detection for range-spread targets in distributed terahertz radar network under unknown clutter

    NASA Astrophysics Data System (ADS)

    Liu, Tong; Min, Rui; Pi, Yiming; Long, Keyu; Huang, Zhongtao

    2016-12-01

    In this study, to detect person-borne concealed threats in range profiles under the circumstance of unknown clutter, we propose a binary integration nonparametric detection method based on the generalized sign (GS) detector for range-spread targets in a distributed terahertz radar network (DTRN). In the detection, the length of range-spread targets and the number of dominant scatterers on range-spread targets are considered and adaptively estimated. Furthermore, the GS detection method is applied to maintain a constant false alarm rate (CFAR) under the circumstance of unknown clutter. The detection performance of the proposed method for single terahertz radar and DTRN are both examined with the data synthesized by real range-spread targets data and real clutter data. Experimental results show that the proposed method is effective, and for a given false alarm probability, the DTRN exhibits better detection performance than the single terahertz radar.

  14. Enhanced synthetic aperture radar automatic target recognition method based on novel features.

    PubMed

    Ning, Chen; Liu, Wenbo; Zhang, Gong; Yin, Jiejun; Ji, Xiuxia

    2016-11-01

    This paper proposes a set of uncommonly rich feature representations for automatic target recognition (ATR) in synthetic aperture radar (SAR) images. The proposed novel feature representations capture both the spatial and spectral properties of a target in a unified framework, while simultaneously offering discrimination and robustness to aspect variations. Specifically, the proposed features are mainly derived from the ideas of the monogenic signal and polar mapping. The applicability of the monogenic signal within the field of SAR target recognition is demonstrated by its capability of capturing both the broad spectral information and spatial localization with compact support. Further, to reduce the influence of inevitable variations due to aspect changes in SAR images, the monogenic components are transformed from Cartesian to polar coordinates through polar mapping. Additionally, a new target-shadow feature is also presented to compensate for the important discriminative information about target geometry, which exists in the shadow area. Finally, the proposed features are jointly considered into a unified multiple kernel learning framework for target recognition. Experiments on the moving and stationary target acquisition and recognition (MSTAR) public dataset demonstrate the strength and applicability of the proposed representations to SAR ATR. Moreover, it is also shown that overall high recognition accuracy can be obtained by the established unified framework.

  15. Precision targeting in guided munition using infrared sensor and millimeter wave radar

    NASA Astrophysics Data System (ADS)

    Sulochana, Sreeja; Hablani, Hari B.; Arya, Hemendra

    2016-07-01

    Conventional munitions are not guided with sensors and therefore miss the target, particularly if the target is mobile. The miss distance of these munitions can be decreased by incorporating sensors to detect the target and guide the munition during flight. This paper is concerned with a precision guided munition equipped with an infrared (IR) sensor and a millimeter wave radar (MmW). Three-dimensional flight of the munition and its pitch and yaw motion models are developed and simulated. The forward and lateral motion of a target tank on the ground is modeled as two independent second-order Gauss-Markov processes. To estimate the target location on the ground and the line-of-sight (LOS) rate to intercept it, an extended Kalman filter is composed whose state vector consists of cascaded state vectors of missile dynamics and target dynamics. The LOS angle measurement from the IR seeker is by centroiding the target image in 40 Hz. The centroid estimation of the images in the focal plane is at a frequency of 10 Hz. Every 10 Hz, centroids of four consecutive images are averaged, yielding a time-averaged centroid, implying some measurement delay. The miss distance achieved by including image processing delays is 1.45 m.

  16. Precision targeting in guided munition using IR sensor and MmW radar

    NASA Astrophysics Data System (ADS)

    Sreeja, S.; Hablani, H. B.; Arya, H.

    2015-10-01

    Conventional munitions are not guided with sensors and therefore miss the target, particularly if the target is mobile. The miss distance of these munitions can be decreased by incorporating sensors to detect the target and guide the munition during flight. This paper is concerned with a Precision Guided Munition(PGM) equipped with an infrared sensor and a millimeter wave radar [IR and MmW, for short]. Three-dimensional flight of the munition and its pitch and yaw motion models are developed and simulated. The forward and lateral motion of a target tank on the ground is modeled as two independent second-order Gauss-Markov process. To estimate the target location on the ground and the line-of-sight rate to intercept it an Extended Kalman Filter is composed whose state vector consists of cascaded state vectors of missile dynamics and target dynamics. The line-of-sight angle measurement from the infrared seeker is by centroiding the target image in 40 Hz. The centroid estimation of the images in the focal plane is at a frequency of 10 Hz. Every 10 Hz, centroids of four consecutive images are averaged, yielding a time-averaged centroid, implying some measurement delay. The miss distance achieved by including by image processing delays is 1:45m.

  17. Using ground-penetrating radar, topography and classification of vegetation to model the sediment and active layer thickness in a periglacial lake catchment, western Greenland

    NASA Astrophysics Data System (ADS)

    Petrone, Johannes; Sohlenius, Gustav; Johansson, Emma; Lindborg, Tobias; Näslund, Jens-Ove; Strömgren, Mårten; Brydsten, Lars

    2016-11-01

    The geometries of a catchment constitute the basis for distributed physically based numerical modeling of different geoscientific disciplines. In this paper results from ground-penetrating radar (GPR) measurements, in terms of a 3-D model of total sediment thickness and active layer thickness in a periglacial catchment in western Greenland, are presented. Using the topography, the thickness and distribution of sediments are calculated. Vegetation classification and GPR measurements are used to scale active layer thickness from local measurements to catchment-scale models. Annual maximum active layer thickness varies from 0.3 m in wetlands to 2.0 m in barren areas and areas of exposed bedrock. Maximum sediment thickness is estimated to be 12.3 m in the major valleys of the catchment. A method to correlate surface vegetation with active layer thickness is also presented. By using relatively simple methods, such as probing and vegetation classification, it is possible to upscale local point measurements to catchment-scale models, in areas where the upper subsurface is relatively homogeneous. The resulting spatial model of active layer thickness can be used in combination with the sediment model as a geometrical input to further studies of subsurface mass transport and hydrological flow paths in the periglacial catchment through numerical modeling. The data set is available for all users via the PANGAEA database, target="_blank">doi:10.1594/PANGAEA.845258.

  18. Signal Processing of Ground Penetrating Radar Using Spectral Estimation Techniques to Estimate the Position of Buried Targets

    NASA Astrophysics Data System (ADS)

    Shrestha, Shanker Man; Arai, Ikuo

    2003-12-01

    Super-resolution is very important for the signal processing of GPR (ground penetration radar) to resolve closely buried targets. However, it is not easy to get high resolution as GPR signals are very weak and enveloped by the noise. The MUSIC (multiple signal classification) algorithm, which is well known for its super-resolution capacity, has been implemented for signal and image processing of GPR. In addition, conventional spectral estimation technique, FFT (fast Fourier transform), has also been implemented for high-precision receiving signal level. In this paper, we propose CPM (combined processing method), which combines time domain response of MUSIC algorithm and conventional IFFT (inverse fast Fourier transform) to obtain a super-resolution and high-precision signal level. In order to support the proposal, detailed simulation was performed analyzing SNR (signal-to-noise ratio). Moreover, a field experiment at a research field and a laboratory experiment at the University of Electro-Communications, Tokyo, were also performed for thorough investigation and supported the proposed method. All the simulation and experimental results are presented.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-04-29

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

  1. Design and implementation of random noise radar with spectral-domain correlation for moving target detection

    NASA Astrophysics Data System (ADS)

    Kim, Jeong Phill; Jeong, Chi Hyun; Kim, Cheol Hoo

    2011-06-01

    A correlation processing algorithm in the spectral domain is proposed for detecting moving targets with random noise radar. AD converted reference and Rx signals are passed through FFT block, and they are multiplied after the reference signal is complex conjugated. Now inverse FFT yields the sub-correlation results, and range and velocity information can be accurately extracted by an additional FFT processing. In this design procedure, specific considerations have to be made for correlation length, averaging number, and number of sub-correlation data for Doppler processing. The proposed algorithm was verified by Simulink (Mathworks) simulation, and its logic was implemented with Xilinx FPGA device (Vertex5 series) by System Generator block sets (Xilinx) in the Simulink environment. A CW X-band random-FM noise radar prototype with an instantaneous bandwidth of 100 MHz was designed and implemented, and laboratory and field tests were conducted to detect moving targets, and the observed results showed the validity of the proposed algorithm and the operation of implemented FPGA logics.

  2. MMW target and clutter characterization using the range instrumentation synthetic aperture radar

    NASA Astrophysics Data System (ADS)

    Ray, Jerry A.; Barr, Douglas

    2010-04-01

    The U.S. Army Research, Development and Engineering Command (AMRDEC) and Redstone Test Center (RTC) at Redstone Arsenal, Alabama have developed a Ka band, range instrumentation synthetic aperture radar (RISAR) for the purpose of millimeter wave (MMW) target and scene characterization. RISAR was developed as one element of the Advanced Multi-Spectral Sensor and Subsystem Test Capabilities (AMSSTC) program funded and managed by the U.S. Army Program Executive Office for Simulation, Training and Instrumentation (PEO STRI), Project Manager for Instrumentation, Targets and Threat Simulators (PM ITTS). The key objective of RISAR is the collection of MMW SAR data that can be used to develop high resolution target and terrain models for use in digital and real-time hardwarein- the-loop simulations. The purpose of this presentation is to provide an overview of RISAR development and implementation. Example results of funded data collections will be presented with an emphasis on the system's 3D target modeling capabilities for ground targets, and wake characterization capabilities for littoral targets.

  3. Heterodyne efficiency for a coherent laser radar with diffuse or aerosol targets

    NASA Technical Reports Server (NTRS)

    Frehlich, R. G.

    1993-01-01

    The performance of a Coherent Laser Radar is determined by the statistics of the coherent Doppler signal. The heterodyne efficiency is an excellent indication of performance because it is an absolute measure of beam alignment and is independent of the transmitter power, the target backscatter coefficient, the atmospheric attenuation, and the detector quantum efficiency and gain. The theoretical calculation of heterodyne efficiency for an optimal monostatic lidar with a circular aperture and Gaussian transmit laser is presented including beam misalignment in the far-field and near-field regimes. The statistical behavior of estimates of the heterodyne efficiency using a calibration hard target are considered. For space based applications, a biased estimate of heterodyne efficiency is proposed that removes the variability due to the random surface return but retains the sensitivity to misalignment. Physical insight is provided by simulation of the fields on the detector surface. The required detector calibration is also discussed.

  4. Monopulse joint parameter estimation of multiple unresolved targets within the radar beam

    NASA Astrophysics Data System (ADS)

    Yuan, Hui; Wang, Chunyang; An, Lei; Li, Xin

    2017-06-01

    Aiming at the problem of the parameter estimation of multiple unresolved targets within the radar beam, using the joint bin processing model, a method of jointly estimating the number and the position of the targets is proposed based on reversible jump Markov Chain Monte Carlo (RJ-MCMC). Reasonable assumptions of the prior distributions and Bayesian theory are adopted to obtain the posterior probability density function of the estimated parameters from the conditional likelihood function of the observation, and then the acceptance ratios of the birth, death and update moves are given. During the update move, a hybrid Metropolis-Hastings (MH) sampling algorithm is used to make a better exploration of the parameter space. The simulation results show that this new method outperforms the method of ML-MLD [11] proposed by X.Zhang for similar estimation accuracy is achieved while fewer sub-pulses are needed.

  5. Toward Efficient Quality of Information Estimation in Simultaneous Acoustic Tracking and Classification of Multiple Targets

    DTIC Science & Technology

    2009-07-01

    different target classifications are depicted using different colors: black for target #1, cyan for target #2, green for target #3, and pink for target...data quality, and its shape is seen in our results. In further work we hope to derive this function from first principles. We define a straw- doll

  6. radR: an open-source platform for acquiring and analysing data on biological targets observed by surveillance radar

    PubMed Central

    2010-01-01

    Background Radar has been used for decades to study movement of insects, birds and bats. In spite of this, there are few readily available software tools for the acquisition, storage and processing of such data. Program radR was developed to solve this problem. Results Program radR is an open source software tool for the acquisition, storage and analysis of data from marine radars operating in surveillance mode. radR takes time series data with a two-dimensional spatial component as input from some source (typically a radar digitizing card) and extracts and retains information of biological relevance (i.e. moving targets). Low-level data processing is implemented in "C" code, but user-defined functions written in the "R" statistical programming language can be called at pre-defined steps in the calculations. Output data formats are designed to allow for future inclusion of additional data items without requiring change to C code. Two brands of radar digitizing card are currently supported as data sources. We also provide an overview of the basic considerations of setting up and running a biological radar study. Conclusions Program radR provides a convenient, open source platform for the acquisition and analysis of radar data of biological targets. PMID:20977735

  7. radR: an open-source platform for acquiring and analysing data on biological targets observed by surveillance radar.

    PubMed

    Taylor, Philip D; Brzustowski, John M; Matkovich, Carolyn; Peckford, Michael L; Wilson, Dave

    2010-10-26

    Radar has been used for decades to study movement of insects, birds and bats. In spite of this, there are few readily available software tools for the acquisition, storage and processing of such data. Program radR was developed to solve this problem. Program radR is an open source software tool for the acquisition, storage and analysis of data from marine radars operating in surveillance mode. radR takes time series data with a two-dimensional spatial component as input from some source (typically a radar digitizing card) and extracts and retains information of biological relevance (i.e. moving targets). Low-level data processing is implemented in "C" code, but user-defined functions written in the "R" statistical programming language can be called at pre-defined steps in the calculations. Output data formats are designed to allow for future inclusion of additional data items without requiring change to C code. Two brands of radar digitizing card are currently supported as data sources. We also provide an overview of the basic considerations of setting up and running a biological radar study. Program radR provides a convenient, open source platform for the acquisition and analysis of radar data of biological targets.

  8. Experimental demonstration of a multi-target detection technique using an X-band optically steered phased array radar.

    PubMed

    Shi, Nuannuan; Li, Ming; Deng, Ye; Zhang, Lihong; Sun, Shuqian; Tang, Jian; Li, Wei; Zhu, Ninghua

    2016-06-27

    An X-band optically-steered phased array radar is developed to demonstrate high resolution multi-target detection. The beam forming is implemented based on wavelength-swept true time delay (TTD) technique. The beam forming system has a wide direction tuning range of ± 54 degree, low magnitude ripple of ± 0.5 dB and small delay error of 0.13 ps/nm. To further verify performance of the proposed optically-steered phased array radar, three experiments are then carried out to implement the single and multiple target detection. A linearly chirped X-band microwave signal is used as radar signal which is finally compressed at the receiver to improve the detection accuracy. The ranging resolution for multi-target detection is up to 2 cm within the measuring distance over 4 m and the azimuth angle error is less than 4 degree.

  9. Parameterized Pseudo-Localization for Accurate and Efficient Moving Targets Imaging in Synthetic Aperture Radar

    PubMed Central

    Zhang, Xuepan; Liu, Lu; Zhang, Xuejing

    2017-01-01

    Accurate and efficient moving target imaging is an important challenge for targets recognition in current synthetic aperture radar (SAR) combined with a ground moving target indication (GMTI) system. As the key but unknown parameter, the Doppler rates are estimated conventionally by searching any possible values for moving targets imaging. However, this conventional estimation method suffers from low accuracy or low efficiency due to the searching procedure. Focusing on these, we present a method to efficiently image the moving targets without the Doppler rate by Doppler delayed interferometry, and the imaged localization, which is parameterized pseudo-localization, is used to estimate the Doppler rate. In order to improve the estimation accuracy, an improved method based on the Newton method of approximation is proposed by exploiting the unused amplitude information. Compared with the conventional methods, the proposed improved method capable of high accuracy and low computation complexity simultaneously can meet the accurate and efficient requirements in the practical applications. Comparison simulations and real data processing results demonstrate the effectiveness of the proposed methods.

  10. Performance analysis of weak target detection via ground-based synthetic aperture radar

    NASA Astrophysics Data System (ADS)

    Zhou, Yong-sheng; Zhou, Mei; Tang, Ling-li; Li, Chuan-rong

    2011-10-01

    Polarimetric Interferometric Synthetic Aperture Radar (Pol-InSAR) is an emerging technique that combines interferometric SAR and polarimetric SAR techniques and has shown its effectiveness in the detection of buried weak targets. The detection performance is affected by the SAR parameters as well as the covering characteristics. In this paper, the effects of covering characteristics on the detection performance were emphasized and experimentally investigated by a ground-based Pol-InSAR system. Firstly, the detection principle for buried weak target by Pol-InSAR technique was presented, which is based on the use of interferometric coherence variation with polarization. Then the ground-based two dimensional rail (TDR) SAR used for investigation was introduced. Furthermore, the experiment target scene was designed and the effects of different covering type, different covering moisture, and different covering depth on the detection performance of weak targets were shown and analyzed. Preliminary results confirmed the effectiveness of Pol-InSAR technique used for weak target detection and it would be helpful for the further investigation of this technique.

  11. The Effect of Synthetic Aperture Radar Image Resolution on Target Discrimination

    NASA Astrophysics Data System (ADS)

    Terzuoli, Andrew; McGowan, John; Gustafson, Steven; Jackson, Julie; Martin, Richard

    This research details the effect of spatial resolution on target discrimination in Synthetic Aper-ture Radar (SAR) images. Multiple SAR image chips containing targets and non-targets are used to test a baseline Automatic Target Recognition (ATR) system with reduced spatial reso-lution obtained by lowering the pixel count or synthesizing a degraded image. The pixel count is lowered by averaging groups of adjoining pixels to form a new single value. The degraded image is synthesized by low-pass filtering the image frequency space and then lowering the pixel count. A two parameter Constant False Alarm Rate (CFAR) detector is tested, and three different types of feature spaces; size, contrast, and texture; are used to train a linear classifier. The results are scored using the Area Under the Receiver Operator Characteristic (AUROC) curve. The CFAR detector is shown to perform better at lower resolution. All three feature sets together performed well with the degradation of resolution; separately the sets had different performances. The texture features performed best because they do not rely on the number of pixels on the target, while the size features performed worst for the same reason. The contrast features yielded improved performance when the resolution was slightly reduced. The views expressed in this article are those of the authors and do not reflect the official policy of the U.S. Air Force, U.S. Department of Defense, or the U.S. Government.

  12. The effect of synthetic aperture radar image resolution on target discrimination

    NASA Astrophysics Data System (ADS)

    McGowan, John E.; Gustafson, Steven C.; Jackson, Julie A.; Terzuoli, Andrew J., Jr.

    2010-04-01

    This paper details the effect of spatial resolution on target discrimination in Synthetic Aperture Radar (SAR) images. Multiple SAR image chips, containing targets and non-targets, are used to test a baseline Automatic Target Recognition (ATR) system with reduced spatial resolution obtained by lowering the pixel count or synthesizing a degraded image. The pixel count is lowered by averaging groups of adjoining pixels to form a new single value. The degraded image is synthesized by low-pass-filtering the image frequency space and then lowering the pixel count. To train a linear classifier, a two-parameter Constant False Alarm Rate (CFAR) detector is tested, and three different types of feature spaces, are used: size, contrast, and texture. The results are scored using the Area Under the Receiver Operator Characteristic (AUROC) curve. The CFAR detector is shown to perform better at lower resolution. All three feature sets together performed well with the degradation of resolution; separately the sets had different performances. The texture features performed best because they do not rely on the number of pixels on the target, while the size features performed the worst for the same reason. The contrast features yielded improved performance when the resolution was slightly reduced.

  13. A range-to-target algorithm for a continuous-wave ground penetrating radar

    SciTech Connect

    Caffey, T.W.

    1998-02-01

    Many geologic situations of interest to oil and gas exploration, and to enhanced recover methods, occur in media whose conductivity is too large to permit the use of pulsed GPRs because of severe dispersion. A continuous-wave radar is not affected by dispersion, and can use the round-trip phase, rather than time, to give an estimate of range. In this paper a range to target algorithms is developed for targets which exhibit a crude hyperbolic phase response. This new algorithm minimizes a difference function over both a 2n {pi}-phase interval and a wavelength interval to provide the range. Only crude initial estimates of the electrical parameters of the host media are required to initiate the algorithm. The furnished range may be the distance to some point within the target rather than to a point upon the illuminated surface because the target is three-dimensional and its electrical parameters can take on any value. This error can be reduced by a sufficiently high operating frequency. Examples are given for a variety of targets, media, range and operating frequency using simulated data.

  14. Automatic Modulation Classification of Common Communication and Pulse Compression Radar Waveforms using Cyclic Features

    DTIC Science & Technology

    2013-03-01

    from estimated duty cycle, cyclic spectral correlation, and cyclic cumulants. The modulations considered in this research are BPSK, QPSK, 16- QAM , 64- QAM ...spectral density PSK phase shift keying QAM quadrature amplitude modulation QPSK quadrature phase shift keying RADAR radio detection and ranging RF radio...spectrum sensing research, automatic modulation recognition has emerged as an important process in cognitive spectrum management and EW applications

  15. Fly eye radar or micro-radar sensor technology

    NASA Astrophysics Data System (ADS)

    Molchanov, Pavlo; Asmolova, Olga

    2014-05-01

    To compensate for its eye's inability to point its eye at a target, the fly's eye consists of multiple angularly spaced sensors giving the fly the wide-area visual coverage it needs to detect and avoid the threats around him. Based on a similar concept a revolutionary new micro-radar sensor technology is proposed for detecting and tracking ground and/or airborne low profile low altitude targets in harsh urban environments. Distributed along a border or around a protected object (military facility and buildings, camp, stadium) small size, low power unattended radar sensors can be used for target detection and tracking, threat warning, pre-shot sniper protection and provides effective support for homeland security. In addition it can provide 3D recognition and targets classification due to its use of five orders more pulses than any scanning radar to each space point, by using few points of view, diversity signals and intelligent processing. The application of an array of directional antennas eliminates the need for a mechanical scanning antenna or phase processor. It radically decreases radar size and increases bearing accuracy several folds. The proposed micro-radar sensors can be easy connected to one or several operators by point-to-point invisible protected communication. The directional antennas have higher gain, can be multi-frequency and connected to a multi-functional network. Fly eye micro-radars are inexpensive, can be expendable and will reduce cost of defense.

  16. Small battery operated unattended radar sensor for security systems

    NASA Astrophysics Data System (ADS)

    Plummer, Thomas J.; Brady, Stephen; Raines, Robert

    2013-06-01

    McQ has developed, tested, and is supplying to Unattended Ground Sensor (UGS) customers a new radar sensor. This radar sensor is designed for short range target detection and classification. The design emphasis was to have low power consumption, totally automated operation, a very high probability of detection coupled with a very low false alarm rate, be able to locate and track targets, and have a price compatible with the UGS market. The radar sensor complements traditional UGS sensors by providing solutions for scenarios that are difficult for UGS. The design of this radar sensor and the testing are presented in this paper.

  17. High Bandwidth, Multi-Purpose Passive Radar Receiver Design For Aerospace and Geoscience Targets

    NASA Astrophysics Data System (ADS)

    Vertatschitsch, Laura

    Passive radar permits inexpensive and stealthy detection and tracking of aerospace and geoscience targets. Transmitters of opportunity such as commercial FM broadcast, DTV broadcast, and cell phone towers are already illuminating many populated areas with continuous power. Passive radar receivers can be located at a distance from the transmitter, and can sense this direct transmission as well as any reflections from ground clutter, aircraft, ionospheric turbulence and meteor trails. The 100% duty cycle allows for long coherent integration, increasing the sensitivity of these instruments greatly. Traditional radar receivers employ analog front end downconverters to translate the radio frequency spectrum to an intermediate frequency (IF) for sampling and signal processing. Such downconverters limit the spectrum available for study, and can introduce nonlinearities which limit the detectability of weak signals in the presence of strong signals. With suitably fast digitizers one can bypass the downconversion stage completely. Very fast digitizers may have relatively few bits, but precision is recovered in subsequent signal processing. We present a new passive radar receiver designed to utilize a broad spectrum of commercial transmitters without the use of a front end analog downconverter. The receiver centers around a Reconfigurable Open Architecture Computing Hardware (ROACH) board developed by the Collaboration for Astronomy Signal Processing and Electronics Research (CASPER) group. Fast sampling rates (8-bit samples as fast as 3 GSps) combined with 640 multiply/addition operations on the Virtex-5 FPGA centered on the ROACH allows for coherent processing of broad spectrum and dynamic decision-making on one device all while sharing a single front end, putting this device on the cutting edge of wideband receiver technology. The radar is also designed to support mobile operation. It fits within a 19'' rack, it is equipped with solid state hard drives, and can run off an

  18. Moving Target Indication via RADARSAT-2 Multichannel Synthetic Aperture Radar Processing

    NASA Astrophysics Data System (ADS)

    Chiu, S.; Dragošević, M. V.

    2009-12-01

    With the recent launches of the German TerraSAR-X and the Canadian RADARSAT-2, both equipped with phased array antennas and multiple receiver channels, synthetic aperture radar, ground moving target indication (SAR-GMTI) data are now routinely being acquired from space. Defence R&D Canada has been conducting SAR-GMTI trials to assess the performance and limitations of the RADARSAT-2 GMTI system. Several SAR-GMTI modes developed for RADARSAT-2 are described and preliminary test results of these modes are presented. Detailed equations of motion of a moving target for multiaperture spaceborne SAR geometry are derived and a moving target parameter estimation algorithm developed for RADARSAT-2 (called the Fractrum Estimator) is presented. Limitations of the simple dual-aperture SAR-GMTI mode are analysed as a function of the signal-to-noise ratio and target speed. Recently acquired RADARSAT-2 GMTI data are used to demonstrate the capability of different system modes and to validate the signal model and the algorithm.

  19. Parameter estimation and imaging of moving targets in bistatic synthetic aperture radar

    NASA Astrophysics Data System (ADS)

    Li, Yu; Huang, Puming; Yang, Zhimei; Lin, Chenchen

    2016-01-01

    In high-resolution bistatic synthetic aperture radar (SAR) systems, parameter estimation is essential to moving target imaging quality. However, precise parameters are difficult to obtain without priori information due to the relative along-track and across-track velocities between the moving target and platforms that change with time. A parameter estimation and imaging approach for moving targets is proposed. First, slant range and relative velocities expression are deduced based on the geometry of bistatic SAR model with one stationary configuration. Then, range curvature term are compensated skillfully by fitting the range-compressed curve in two-dimensional time domain, meanwhile, the initial estimated range walk slope can be achieved. Finally, precise Doppler centroid is estimated through searching for the maximum contrast with folding search algorithm, which is giving consideration to both searching precision and computational complexity. Thus, the proposed algorithm provides an effective way for parameter estimation and imaging of moving target without prior information and interpolation operation. Experimental results show the effectiveness of the proposed method.

  20. Adaptive multiparameter spectral feature analysis for synthetic aperture radar target recognition

    NASA Astrophysics Data System (ADS)

    Zhang, Xiangrong; Jiao, Licheng; Zhou, Sisi; Zhou, Nan; Feng, Jie

    2012-08-01

    A feature extraction algorithm based on spectral clustering with adaptive multiparameters is proposed for synthetic aperture radar automatic target recognition (SAR-ATR). Spectral clustering has been widely applied in computer vision for its good performance. Meanwhile, the spectral mapping step in it has the property of feature space transformation. Spectral clustering based target feature extraction for SAR-ATR is constructed according to the framework of out-of-sample extensions in weighted kernel principal component analysis. To avoid the scaling parameter selection in spectral feature analysis (SFA) and eliminate the influence of scaling parameter on feature extraction performance as well, the multiple scaling parameters are calculated adaptively by local neighborhoods. Because the local statistics of the neighborhood of each point are taken into consideration, its performance is better than using only one fixed parameter. Based on the extracted features, target recognition is performed by the support vector machine for its good generalization capability. The experimental results show that the multiparameter SFA outperforms the principal component analysis, kernel principal component analysis and SFA with the selected scaling parameter for SAR target recognition in terms of recognition accuracy.

  1. Human activity classification using Hilbert-Huang transform analysis of radar Doppler data

    NASA Astrophysics Data System (ADS)

    Fairchild, Dustin P.; Narayanan, Ram M.

    2011-06-01

    The automatic identification of human activities has become an area of interest in recent years. Identifying human activities is useful in various applications, such as through-barrier identification of intruders and non-contact monitoring of patients in hospitals. Numerous methods of human activity classification have been proposed in the past, including the use of Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs). Most research in this area thus far has utilized the Short-Time Fourier Transform (STFT) as a method of obtaining the feature vectors necessary for classification. In this paper, we propose the use of the Empirical Mode Decomposition (EMD) algorithm as an alternative approach for obtaining feature vectors from human micro-Doppler signals and utilize an SVM for classification. Since the micro-Doppler signature is unique to a specific activity, the EMD outputs can be utilized as feature vectors. By utilizing the EMD algorithm in conjunction with an SVM, binary classification of human activities have shown to yield accurate results. Because SVMs were originally developed to solve the binary classification problem, additional steps must be taken in order to extend the problem to identify multiple classes. In this paper, two methods for multi-class classification will be demonstrated and compared. The first method is the one-against-all approach and the second is a decision tree based approach. In both cases, a high degree of accuracy is achieved.

  2. Radar Target Discrimination and Identification Using Extinction-Pulses and Single-Mode Extraction Pulses

    DTIC Science & Technology

    1991-01-31

    T-15 model ( home made and arbitrarily named) of length 30 cm, (3) a big B707 model of length 64.5 cm and (4) a big F-18 model of length 72 cm as shown...0018-926X/86/0700-0896501.00 © 1986 IEEE 87 CHEN et al. RADAR TARGET DISCRIMINATION 897 Fortunately, for most space vehicles , such as rockets and...and complex permittivities7 37 Jare defined as Eo=- 1’ 8 H. (6) E;=e2+ O/S (19) where 1h = S2 ;Z + M2S (20) V2H , -PH, = 0 (7) el = el + aIs (21) SUN ET

  3. Advanced Polarimetric Concepts - Part 2 (Polarimetric Target Classification)

    DTIC Science & Technology

    2007-02-01

    polarization and single polarization /single polarization modes, and the C- band RADARSAT II [Meisl 2000] and L- band ALOS ...likelihood classifiers to a. Each individual polarization , | HH |2, |VV|2 and |HV|2, for all three bands . b. Combinations of dual polarizations without the...advanced satellite radar systems such as PALSAR, an L- band SAR sensor on board the NASDA ALOS satellite and Radarsat II, a C- band polarimetric

  4. A point target model for the synthetic aperture radar detection of ships and ice conditions during a swell

    NASA Technical Reports Server (NTRS)

    Evans, D. D.

    1979-01-01

    A running swell affects the synthetic aperture radar (SAR) imagery of ships, smaller icebergs, and other floating objects because the targets signal is no longer matched with the azimuth processor. This effect is analyzed analytically and numerically for the case of conventional image processing.

  5. A point target model for the synthetic aperture radar detection of ships and ice conditions during a swell

    NASA Technical Reports Server (NTRS)

    Evans, D. D.

    1979-01-01

    A running swell affects the synthetic aperture radar (SAR) imagery of ships, smaller icebergs, and other floating objects because the targets signal is no longer matched with the azimuth processor. This effect is analyzed analytically and numerically for the case of conventional image processing.

  6. Target detection in synthetic aperture radar imagery: a state-of-the-art survey

    NASA Astrophysics Data System (ADS)

    El-Darymli, Khalid; McGuire, Peter; Power, Desmond; Moloney, Cecilia

    2013-01-01

    Target detection is the front-end stage in any automatic target recognition system for synthetic aperture radar (SAR) imagery (SAR-ATR). The efficacy of the detector directly impacts the succeeding stages in the SAR-ATR processing chain. There are numerous methods reported in the literature for implementing the detector. We offer an umbrella under which the various research activities in the field are broadly probed and taxonomized. First, a taxonomy for the various detection methods is proposed. Second, the underlying assumptions for different implementation strategies are overviewed. Third, a tabular comparison between careful selections of representative examples is introduced. Finally, a novel discussion is presented, wherein the issues covered include suitability of SAR data models, understanding the multiplicative SAR data models, and two unique perspectives on constant false alarm rate (CFAR) detection: signal processing and pattern recognition. From a signal processing perspective, CFAR is shown to be a finite impulse response band-pass filter. From a statistical pattern recognition perspective, CFAR is shown to be a suboptimal one-class classifier: a Euclidean distance classifier and a quadratic discriminant with a missing term for one-parameter and two-parameter CFAR, respectively. We make a contribution toward enabling an objective design and implementation for target detection in SAR imagery.

  7. Distributed micro-radar system for detection and tracking of low-profile, low-altitude targets

    NASA Astrophysics Data System (ADS)

    Gorwara, Ashok; Molchanov, Pavlo

    2016-05-01

    Proposed airborne surveillance radar system can detect, locate, track, and classify low-profile, low-altitude targets: from traditional fixed and rotary wing aircraft to non-traditional targets like unmanned aircraft systems (drones) and even small projectiles. Distributed micro-radar system is the next step in the development of passive monopulse direction finder proposed by Stephen E. Lipsky in the 80s. To extend high frequency limit and provide high sensitivity over the broadband of frequencies, multiple angularly spaced directional antennas are coupled with front end circuits and separately connected to a direction finder processor by a digital interface. Integration of antennas with front end circuits allows to exclude waveguide lines which limits system bandwidth and creates frequency dependent phase errors. Digitizing of received signals proximate to antennas allows loose distribution of antennas and dramatically decrease phase errors connected with waveguides. Accuracy of direction finding in proposed micro-radar in this case will be determined by time accuracy of digital processor and sampling frequency. Multi-band, multi-functional antennas can be distributed around the perimeter of a Unmanned Aircraft System (UAS) and connected to the processor by digital interface or can be distributed between swarm/formation of mini/micro UAS and connected wirelessly. Expendable micro-radars can be distributed by perimeter of defense object and create multi-static radar network. Low-profile, lowaltitude, high speed targets, like small projectiles, create a Doppler shift in a narrow frequency band. This signal can be effectively filtrated and detected with high probability. Proposed micro-radar can work in passive, monostatic or bistatic regime.

  8. 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.

  9. 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.

  10. Planetary Radar

    NASA Technical Reports Server (NTRS)

    Neish, Catherine D.; Carter, Lynn M.

    2015-01-01

    This chapter describes the principles of planetary radar, and the primary scientific discoveries that have been made using this technique. The chapter starts by describing the different types of radar systems and how they are used to acquire images and accurate topography of planetary surfaces and probe their subsurface structure. It then explains how these products can be used to understand the properties of the target being investigated. Several examples of discoveries made with planetary radar are then summarized, covering solar system objects from Mercury to Saturn. Finally, opportunities for future discoveries in planetary radar are outlined and discussed.

  11. Planetary Radar

    NASA Technical Reports Server (NTRS)

    Neish, Catherine D.; Carter, Lynn M.

    2015-01-01

    This chapter describes the principles of planetary radar, and the primary scientific discoveries that have been made using this technique. The chapter starts by describing the different types of radar systems and how they are used to acquire images and accurate topography of planetary surfaces and probe their subsurface structure. It then explains how these products can be used to understand the properties of the target being investigated. Several examples of discoveries made with planetary radar are then summarized, covering solar system objects from Mercury to Saturn. Finally, opportunities for future discoveries in planetary radar are outlined and discussed.

  12. An Intercomparison Between Radar Reflectivity and the IR Cloud Classification Technique for the TOGA-COARE Area

    NASA Technical Reports Server (NTRS)

    Carvalho, L. M. V.; Rickenbach, T.

    1999-01-01

    Satellite infrared (IR) and visible (VIS) images from the Tropical Ocean Global Atmosphere - Coupled Ocean Atmosphere Response Experiment (TOGA-COARE) experiment are investigated through the use of Clustering Analysis. The clusters are obtained from the values of IR and VIS counts and the local variance for both channels. The clustering procedure is based on the standardized histogram of each variable obtained from 179 pairs of images. A new approach to classify high clouds using only IR and the clustering technique is proposed. This method allows the separation of the enhanced convection in two main classes: convective tops, more closely related to the most active core of the storm, and convective systems, which produce regions of merged, thick anvil clouds. The resulting classification of different portions of cloudiness is compared to the radar reflectivity field for intensive events. Convective Systems and Convective Tops are followed during their life cycle using the IR clustering method. The areal coverage of precipitation and features related to convective and stratiform rain is obtained from the radar for each stage of the evolving Mesoscale Convective Systems (MCS). In order to compare the IR clustering method with a simple threshold technique, two IR thresholds (Tir) were used to identify different portions of cloudiness, Tir=240K which roughly defines the extent of all cloudiness associated with the MCS, and Tir=220K which indicates the presence of deep convection. It is shown that the IR clustering technique can be used as a simple alternative to identify the actual portion of convective and stratiform rainfall.

  13. Target parameter estimation for spatial and temporal formulations in MIMO radars using compressive sensing

    NASA Astrophysics Data System (ADS)

    Ali, Hussain; Ahmed, Sajid; Al-Naffouri, Tareq Y.; Sharawi, Mohammad S.; Alouini, Mohamed-S.

    2017-01-01

    Conventional algorithms used for parameter estimation in colocated multiple-input-multiple-output (MIMO) radars require the inversion of the covariance matrix of the received spatial samples. In these algorithms, the number of received snapshots should be at least equal to the size of the covariance matrix. For large size MIMO antenna arrays, the inversion of the covariance matrix becomes computationally very expensive. Compressive sensing (CS) algorithms which do not require the inversion of the complete covariance matrix can be used for parameter estimation with fewer number of received snapshots. In this work, it is shown that the spatial formulation is best suitable for large MIMO arrays when CS algorithms are used. A temporal formulation is proposed which fits the CS algorithms framework, especially for small size MIMO arrays. A recently proposed low-complexity CS algorithm named support agnostic Bayesian matching pursuit (SABMP) is used to estimate target parameters for both spatial and temporal formulations for the unknown number of targets. The simulation results show the advantage of SABMP algorithm utilizing low number of snapshots and better parameter estimation for both small and large number of antenna elements. Moreover, it is shown by simulations that SABMP is more effective than other existing algorithms at high signal-to-noise ratio.

  14. Simple estimation of late-time response for radar target identification

    NASA Astrophysics Data System (ADS)

    Boonpoonga, Akkarat; Chomdee, Pongsathorn; Burintramart, Santana; Akkaraekthalin, Prayoot

    2017-06-01

    This paper proposes a conceptual technique for the simple estimation of the late-time response for radar target identification without a priori knowledge of the target geometry or orientation. In the proposed technique, the cross correlation between the backscattering response and transmitted wave is performed. Peaks will occur in the cross-correlation output when the transmitted wave is aligned with the same features in the received backscattering response. The commencement of the late-time response corresponds with the peak resulting from a superimposed pattern between the transmitted wave and late-time response. The matrix pencil method was exploited in order to extract the poles from the received backscattering response. Several simulations were performed to evaluate the performance of the proposed estimation technique. The simulation results confirmed the superiority of the proposed approach. In the special case of the transmission with a monocycle pulse, the commencement of the late-time response can be automatically selected from the third peak of the resulting cross-correlation output.

  15. Land cover classification accuracy from electro-optical, X, C, and L-band Synthetic Aperture Radar data fusion

    NASA Astrophysics Data System (ADS)

    Hammann, Mark Gregory

    The fusion of electro-optical (EO) multi-spectral satellite imagery with Synthetic Aperture Radar (SAR) data was explored with the working hypothesis that the addition of multi-band SAR will increase the land-cover (LC) classification accuracy compared to EO alone. Three satellite sources for SAR imagery were used: X-band from TerraSAR-X, C-band from RADARSAT-2, and L-band from PALSAR. Images from the RapidEye satellites were the source of the EO imagery. Imagery from the GeoEye-1 and WorldView-2 satellites aided the selection of ground truth. Three study areas were chosen: Wad Medani, Sudan; Campinas, Brazil; and Fresno- Kings Counties, USA. EO imagery were radiometrically calibrated, atmospherically compensated, orthorectifed, co-registered, and clipped to a common area of interest (AOI). SAR imagery were radiometrically calibrated, and geometrically corrected for terrain and incidence angle by converting to ground range and Sigma Naught (?0). The original SAR HH data were included in the fused image stack after despeckling with a 3x3 Enhanced Lee filter. The variance and Gray-Level-Co-occurrence Matrix (GLCM) texture measures of contrast, entropy, and correlation were derived from the non-despeckled SAR HH bands. Data fusion was done with layer stacking and all data were resampled to a common spatial resolution. The Support Vector Machine (SVM) decision rule was used for the supervised classifications. Similar LC classes were identified and tested for each study area. For Wad Medani, nine classes were tested: low and medium intensity urban, sparse forest, water, barren ground, and four agriculture classes (fallow, bare agricultural ground, green crops, and orchards). For Campinas, Brazil, five generic classes were tested: urban, agriculture, forest, water, and barren ground. For the Fresno-Kings Counties location 11 classes were studied: three generic classes (urban, water, barren land), and eight specific crops. In all cases the addition of SAR to EO resulted

  16. Inverse synthetic aperture radar imaging of maneuvering target based on cubic chirps model with time-varying amplitudes

    NASA Astrophysics Data System (ADS)

    Wang, Yong; Zhang, Qingxiang; Zhao, Bin

    2016-01-01

    Inverse synthetic aperture radar (ISAR) imaging of maneuvering target is a main topic in the field of radar signal processing, and the received signal in a range bin can usually be characterized as multicomponent cubic chirps with constant amplitudes after motion compensation. In fact, the phenomenon of migration through resolution cell (MTRC) often occurs for the target's complex motion, and this will induce the time-varying character for the amplitudes of cubic chirps. An algorithm for the parameters estimation of multicomponent cubic chirps with time-varying amplitudes based on the extension form of match Fourier transform is proposed, and by using it in ISAR imaging of maneuvering target, the quality of images can be improved significantly compared with the constant amplitudes model. Results of simulated and real data validate the effectiveness of the algorithm in this paper.

  17. Non-linear molecular pattern classification using molecular beacons with multiple targets.

    PubMed

    Lee, In-Hee; Lee, Seung Hwan; Park, Tai Hyun; Zhang, Byoung-Tak

    2013-12-01

    In vitro pattern classification has been highlighted as an important future application of DNA computing. Previous work has demonstrated the feasibility of linear classifiers using DNA-based molecular computing. However, complex tasks require non-linear classification capability. Here we design a molecular beacon that can interact with multiple targets and experimentally shows that its fluorescent signals form a complex radial-basis function, enabling it to be used as a building block for non-linear molecular classification in vitro. The proposed method was successfully applied to solving artificial and real-world classification problems: XOR and microRNA expression patterns. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  18. Per-point and per-field contextual classification of multipolarization and multiple incidence angle aircraft L-band radar data

    NASA Technical Reports Server (NTRS)

    Hoffer, Roger M.; Hussin, Yousif Ali

    1989-01-01

    Multipolarized aircraft L-band radar data are classified using two different image classification algorithms: (1) a per-point classifier, and (2) a contextual, or per-field, classifier. Due to the distinct variations in radar backscatter as a function of incidence angle, the data are stratified into three incidence-angle groupings, and training and test data are defined for each stratum. A low-pass digital mean filter with varied window size (i.e., 3x3, 5x5, and 7x7 pixels) is applied to the data prior to the classification. A predominately forested area in northern Florida was the study site. The results obtained by using these image classifiers are then presented and discussed.

  19. Non-target adjacent stimuli classification improves performance of classical ERP-based brain computer interface

    NASA Astrophysics Data System (ADS)

    Ceballos, G. A.; Hernández, L. F.

    2015-04-01

    Objective. The classical ERP-based speller, or P300 Speller, is one of the most commonly used paradigms in the field of Brain Computer Interfaces (BCI). Several alterations to the visual stimuli presentation system have been developed to avoid unfavorable effects elicited by adjacent stimuli. However, there has been little, if any, regard to useful information contained in responses to adjacent stimuli about spatial location of target symbols. This paper aims to demonstrate that combining the classification of non-target adjacent stimuli with standard classification (target versus non-target) significantly improves classical ERP-based speller efficiency. Approach. Four SWLDA classifiers were trained and combined with the standard classifier: the lower row, upper row, right column and left column classifiers. This new feature extraction procedure and the classification method were carried out on three open databases: the UAM P300 database (Universidad Autonoma Metropolitana, Mexico), BCI competition II (dataset IIb) and BCI competition III (dataset II). Main results. The inclusion of the classification of non-target adjacent stimuli improves target classification in the classical row/column paradigm. A gain in mean single trial classification of 9.6% and an overall improvement of 25% in simulated spelling speed was achieved. Significance. We have provided further evidence that the ERPs produced by adjacent stimuli present discriminable features, which could provide additional information about the spatial location of intended symbols. This work promotes the searching of information on the peripheral stimulation responses to improve the performance of emerging visual ERP-based spellers.

  20. Tensor Invariant Processing of Multistatic EMI Data for Target Classification

    DTIC Science & Technology

    2015-05-01

    items in blue. .........................................8 Figure 7. Decision metric distributions for a data set from the Pole Mountain demonstration...rifle grenade, Right (anomaly 1030) is a small piece of wire. If the data can support inversion , principal axis polarizabilities are calculated using a...signal to noise ratio (SNR) weighted [7] inversion algorithm. The principal axis polarizabilities are the basis for classification. Figure 5 Shows

  1. Advanced Concepts In Polarimetry. Part 2: Polarimetric Target Classification

    DTIC Science & Technology

    2005-02-01

    polarization , | HH |2, |VV|2 and |HV|2, for all three bands . b. Combinations of dual polarizations without the phase differences... polarization complex data with phase differences, complex ( HH , VV), ( HH , HV) and (HV, VV). d. P- band , L- band or C- band fully polarimetric data. e...HV (d) P- band HH and HV intensities (without phase) Fig. 6: Comparisons of dual polarization tree age classifications. 5 - 10

  2. Full-polarization radar remote sensing and data mining for tropical crops mapping: a successful SVM-based classification model

    NASA Astrophysics Data System (ADS)

    Denize, J.; Corgne, S.; Todoroff, P.; LE Mezo, L.

    2015-12-01

    In Reunion, a tropical island of 2,512 km², 700 km east of Madagascar in the Indian Ocean, constrained by a rugged relief, agricultural sectors are competing in highly fragmented agricultural land constituted by heterogeneous farming systems from corporate to small-scale farming. Policymakers, planners and institutions are in dire need of reliable and updated land use references. Actually conventional land use mapping methods are inefficient under the tropic with frequent cloud cover and loosely synchronous vegetative cycles of the crops due to a constant temperature. This study aims to provide an appropriate method for the identification and mapping of tropical crops by remote sensing. For this purpose, we assess the potential of polarimetric SAR imagery associated with associated with machine learning algorithms. The method has been developed and tested on a study area of 25*25 km thanks to 6 RADARSAT-2 images in 2014 in full-polarization. A set of radar indicators (backscatter coefficient, bands ratios, indices, polarimetric decompositions (Freeman-Durden, Van zyl, Yamaguchi, Cloude and Pottier, Krogager), texture, etc.) was calculated from the coherency matrix. A random forest procedure allowed the selection of the most important variables on each images to reduce the dimension of the dataset and the processing time. Support Vector Machines (SVM), allowed the classification of these indicators based on a learning database created from field observations in 2013. The method shows an overall accuracy of 88% with a Kappa index of 0.82 for the identification of four major crops.

  3. Modified Cramér-Rao lower bounds for joint position and velocity estimation of a Rician target in OFDM-based passive radar networks

    NASA Astrophysics Data System (ADS)

    Shi, C. G.; Salous, S.; Wang, F.; Zhou, J. J.

    2017-01-01

    Owing to the increased deployment and the favorable range and Doppler resolutions, orthogonal frequency-division multiplexing (OFDM)-based L band digital aeronautical communication system type 1 (LDACS1) stations have become attractive systems for target surveillance in passive radar applications. This paper investigates the problem of joint parameter (position and velocity) estimation of a Rician target in OFDM-based passive radar network systems with multichannel receivers placed on moving platforms, which are composed of multiple OFDM-based LDACS1 transmitters of opportunity and multiple radar receivers. The modified Cramér-Rao lower bounds (MCRLBs) on the Cartesian coordinates of target position and velocity are computed, where the received signal from the target is composed of dominant scatterer (DS) component and weak isotropic scatterers (WIS) component. Simulation results are provided to demonstrate that the target parameter estimation accuracy can be improved by exploiting the DS component. It also shows that the joint MCRLB is not only a function of the transmitted waveform parameters, target radar cross section, and signal-to-noise ratio but also a function of the relative geometry between the target and the passive radar networks. The analytical expressions of MCRLB can be utilized as a performance metric to access the target parameter estimation in OFDM-based passive radar networks in that they enable the selection of optimal transmitter-receiver pairs for target estimation.

  4. Passive position-adaptive radar modes for non-LOS interrogation of embedded targets

    NASA Astrophysics Data System (ADS)

    Mitra, Atindra K.

    2004-08-01

    A position-adaptive radar system concept is presented for purposes of interrogating difficult and obscured targets via the application of low-altitude smart or robotic-type UAV platforms. Under this concept, a high-altitude radiating platform is denoted as a HUAV and a low-altitude "position-adaptive" platform is denoted as a LUAV. The system concept is described by two modes. In Mode-1, real-time onboard LUAV computation of a phase parameter denoted as "signal differential path length" allows the LUAV to position-adaptively isolate a "signal leakage point", for example, between two buildings. After the LUAV position-adaptively converges to an optimum location, the system enters Mode-2. Under this Mode-2 concept, a technique denoted as "exploitation of leakage signals via path trajectory diversity" (E-LS-PTD) is developed. This technique is based on modulating scattering centers on embedded objects by implementing a fast trajectory on the HUAV while the LUAV is hovering in front of an "obscuration channel." Analytical results include sample outputs from an initial set numerical electromagnetic simulations.

  5. Nonsearching Doppler parameter and velocity estimation method for synthetic aperture radar ground moving target imaging

    NASA Astrophysics Data System (ADS)

    Li, Zhongyu; Wu, Junjie; Huang, Yunlin; Yang, Haiguang; Yang, Jianyu

    2016-07-01

    For synthetic aperture radar (SAR), ground moving target (GMT) imaging necessitates the compensation of the additional azimuth modulation contributed by the unknown movement of the GMT. That is to say, it is necessary to estimate the Doppler parameters of the GMT without a priori knowledge of the GMT's motion parameters. This paper presents a Doppler parameter and velocity estimation method to refocus the GMT from its smeared response in SAR image. The main idea of this method is that an azimuth reference function is constructed to do the correlation integral with the azimuth signal of the GMT. And in general, the Doppler parameters of the presumed azimuth reference function are different from those of the GMT's azimuth signal since the velocity parameters of the GMT are unknown. Therefore, the correlation operation referred to here is actually mismatched, and the processing result of is shifted and defocused. The shifted and defocused result is utilized to get the real Doppler parameters and the velocity parameters of the GMT. One advantage of this method is that it is a nonsearching method. Another advantage is that both the Doppler centroid and the Doppler frequency rate of the GMT can be simultaneously estimated according to the relationships between the Doppler parameters and the smeared response of the GMT. In addition, the velocity of the GMT can also be obtained based on the estimated Doppler parameters. Numerical simulations and experimental data processing verify the validity of the method proposed.

  6. Optimization of neural network architecture for classification of radar jamming FM signals

    NASA Astrophysics Data System (ADS)

    Soto, Alberto; Mendoza, Ariadna; Flores, Benjamin C.

    2017-05-01

    The purpose of this study is to investigate several artificial Neural Network (NN) architectures in order to design a cognitive radar system capable of optimally distinguishing linear Frequency-Modulated (FM) signals from bandlimited Additive White Gaussian Noise (AWGN). The goal is to create a theoretical framework to determine an optimal NN architecture to achieve a Probability of Detection (PD) of 95% or higher and a Probability of False Alarm (PFA) of 1.5% or lower at 5 dB Signal to Noise Ratio (SNR). Literature research reveals that the frequency-domain power spectral densities characterize a signal more efficiently than its time-domain counterparts. Therefore, the input data is preprocessed by calculating the magnitude square of the Discrete Fourier Transform of the digitally sampled bandlimited AWGN and linear FM signals to populate a matrix containing N number of samples and M number of spectra. This matrix is used as input for the NN, and the spectra are divided as follows: 70% for training, 15% for validation, and 15% for testing. The study begins by experimentally deducing the optimal number of hidden neurons (1-40 neurons), then the optimal number of hidden layers (1-5 layers), and lastly, the most efficient learning algorithm. The training algorithms examined are: Resilient Backpropagation, Scaled Conjugate Gradient, Conjugate Gradient with Powell/Beale Restarts, Polak-Ribiére Conjugate Gradient, and Variable Learning Rate Backpropagation. We determine that an architecture with ten hidden neurons (or higher), one hidden layer, and a Scaled Conjugate Gradient for training algorithm encapsulates an optimal architecture for our application.

  7. Exercise Narwhal: Visibility of Deployed Radar Targets and Change Detection with RADARSAT-1 Fine Beam Mode SAR Imagery

    DTIC Science & Technology

    2005-12-01

    Defence Research and Recherche et developpemenr Development Canada pour la defense Canada DEFENCE DEFENSE Exercise Narwhal : Visibility of deployed...December 2005 CanadaY Exercise Narwhal : Visibility of deployed Radar Targets and Change Detection with RADARSAT-1 fine beam mode SAR imagery Karim E...2005 Abstract In August 2004 the Canadian Forces undertook Exercise Narwhal near Pangnirtung on Baffin Island. DRDC Ottawa participated in a

  8. Extracting Micro-Doppler Radar Signatures from Rotating Targets Using Fourier-Bessel Transform and Time-Frequency Analysis

    DTIC Science & Technology

    2014-10-16

    1 Extracting micro-Doppler radar signatures from rotating targets using Fourier- Bessel Transform and Time-Frequency analysis P. Suresh1,T...kvenkataramanaiah@sssihl.edu.in Abstract In this paper, we report the efficiency of Fourier Bessel transform and time-frequency based method in conjunction with...decomposed into stationary and non-stationary components using Fourier Bessel transform in conjunction with the fractional Fourier transform. The

  9. 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.

  10. Domain definition and target classification for CASP6.

    PubMed

    Tress, Michael; Tai, Chin-Hsien; Wang, Guoli; Ezkurdia, Iakes; López, Gonzalo; Valencia, Alfonso; Lee, Byungkook; Dunbrack, Roland L

    2005-01-01

    Assessment of structure predictions in CASP6 was based on single domains isolated from experimentally determined structures, which were categorized into comparative modeling, fold recognition, and new fold targets. Domain definitions were defined upon visual examination of the structures with the aid of automated domain-parsing programs. Domain categorization was determined by comparison of the target structures with those in the Protein Data Bank at the time each target expired and a variety of sequence and structure-based methods to determine potential homologous relationships. 2005 Wiley-Liss, Inc.

  11. Polarization Utilization in Radar Target Reconstruction: C-Wide (Multi-Frequency) Band Relationship of a Target’s Characteristic Operators with Its Unique Set of Natural Eigenfrequencies.

    DTIC Science & Technology

    1983-12-14

    Weapons Center, China Lake , CA, 1983. J.R. Huynen, "Phenomenological Theory of Radar Targets," Ph.D. Dissertation, Technical University, Delft, The...Eaves Georgia Institute of Technology Dr. William A. Holm Atlanta, GA 30332 (404) 424-9609 Dr. Otto E. Rausch Electromagnetics Research Lab Dr. Georges A...Sudbury, MA 01776 Bell Aerospace Tektronix Dr. Lionel Shub P.O. Box 1 (716) 297-1000 Buffalo, NY 14240 Raytheon Company Dr. Edwin R. Hiller Hartwell

  12. Detection of urban environments using advanced land observing satellite phased array type L-band synthetic aperture radar data through different classification techniques

    NASA Astrophysics Data System (ADS)

    Pradhan, Biswajeet; Abdullahi, Saleh; Seddighi, Younes

    2016-07-01

    Urban environments are very dynamic phenomena, and it is essential to update urban-related information for various applications. In this regard, remotely sensed data have been utilized widely to extract and monitor urban land use and land cover changes. Particularly, synthetic aperture radar (SAR) data, due to several advantages of this technology in comparison to passive sensors, provides better performance especially in tropical regions. However, the methodological approaches for extraction of information from SAR images are another important task that needs to be considered appropriately. This paper attempts to investigate and compare the performance of different image classification techniques for extracting urban areas using advanced land observing satellite phased array type L-band synthetic aperture radar imagery. Several object- [such as rule based (RB), support vector machine (SVM) and K-nearest neighbor (K-NN)] and pixel-based [decision tree (DT)] classification techniques were implemented, and their results were compared in detail. The overall results indicated RB classification performed better than other techniques. Furthermore, DT method, due to its predefined rules, distinguished the land cover classes better than SVM and K-NN, which were based on training datasets. Nevertheless, this study confirms the potential of SAR data and object-based classification techniques in urban detection and land cover mapping.

  13. Transitive, Anti-Symmetric Relational Attributes in Structural Description Matching with Applications to Radar Target Identification

    DTIC Science & Technology

    1990-10-01

    Based Parametric Estimation .... ............. 18 Ii 2.2.1 The Frequency Domain Parametric Model ...... ... 18 2.2.2 The Range Profile . . . .1.9...3.7 Metric Inter-Node-Set Distances ..... ............... 58 4 APPLICATION TO RADAR OBJECT IDENTIFICATION 62 4.1 Parametric Estimation as a...derived from it. 7 Segmentation of the radar measurement vector is accomplished via a parametric estimation procedure. The chosen procedure is a

  14. Preparations of Proceedings Manuscript for NATO-ARW-DIMRP 88 Direct and Inverse Methods in Radar Polarimetry, Bad Windsheim, FRG, 18-24 September 1988

    DTIC Science & Technology

    1991-08-30

    rapproachment between Eastern and Western Radar polarimetrists be visibly strengthened; and (iii) a true end is made to "LENINIST-MARX- ENGEL -COMMUNIST...RADAR Alfonso Farina, Federico Scannapieco & Francesco Vinelli 1021 IV-9 PLASMA RESONANCE EFFECTS IN RADAR BACKSCATTERING FROM METEOR TRAILS AS...TECHNIQUES William A. Holm 1011 IV-8 TARGET DETECTION AND CLASSIFICATION WITH POLARIMETRIC HIGH RANGE RESOLUTION RADAR Alfonso Farina, Federico

  15. Classification of underwater targets from autonomous underwater vehicle sampled bistatic acoustic scattered fields.

    PubMed

    Fischell, Erin M; Schmidt, Henrik

    2015-12-01

    One of the long term goals of autonomous underwater vehicle (AUV) minehunting is to have multiple inexpensive AUVs in a harbor autonomously classify hazards. Existing acoustic methods for target classification using AUV-based sensing, such as sidescan and synthetic aperture sonar, require an expensive payload on each outfitted vehicle and post-processing and/or image interpretation. A vehicle payload and machine learning classification methodology using bistatic angle dependence of target scattering amplitudes between a fixed acoustic source and target has been developed for onboard, fully autonomous classification with lower cost-per-vehicle. To achieve the high-quality, densely sampled three-dimensional (3D) bistatic scattering data required by this research, vehicle sampling behaviors and an acoustic payload for precision timed data acquisition with a 16 element nose array were demonstrated. 3D bistatic scattered field data were collected by an AUV around spherical and cylindrical targets insonified by a 7-9 kHz fixed source. The collected data were compared to simulated scattering models. Classification and confidence estimation were shown for the sphere versus cylinder case on the resulting real and simulated bistatic amplitude data. The final models were used for classification of simulated targets in real time in the LAMSS MOOS-IvP simulation package [M. Benjamin, H. Schmidt, P. Newman, and J. Leonard, J. Field Rob. 27, 834-875 (2010)].

  16. Evaluation of synthetic aperture radar image segmentation algorithms in the context of automatic target recognition

    NASA Astrophysics Data System (ADS)

    Xue, Kefu; Power, Gregory J.; Gregga, Jason B.

    2002-11-01

    Image segmentation is a process to extract and organize information energy in the image pixel space according to a prescribed feature set. It is often a key preprocess in automatic target recognition (ATR) algorithms. In many cases, the performance of image segmentation algorithms will have significant impact on the performance of ATR algorithms. Due to the variations in feature set definitions and the innovations in the segmentation processes, there is large number of image segmentation algorithms existing in ATR world. Recently, the authors have investigated a number of measures to evaluate the performance of segmentation algorithms, such as Percentage Pixels Same (pps), Partial Directed Hausdorff (pdh) and Complex Inner Product (cip). In the research, we found that the combination of the three measures shows effectiveness in the evaluation of segmentation algorithms against truth data (human master segmentation). However, we still don't know what are the impact of those measures in the performance of ATR algorithms that are commonly measured by Probability of detection (PDet), Probability of false alarm (PFA), Probability of identification (PID), etc. In all practical situations, ATR boxes are implemented without human observer in the loop. The performance of synthetic aperture radar (SAR) image segmentation should be evaluated in the context of ATR rather than human observers. This research establishes a segmentation algorithm evaluation suite involving segmentation algorithm performance measures as well as the ATR algorithm performance measures. It provides a practical quantitative evaluation method to judge which SAR image segmentation algorithm is the best for a particular ATR application. The results are tabulated based on some baseline ATR algorithms and a typical image segmentation algorithm used in ATR applications.

  17. Performance Evaluation of Target Detection with a Near-Space Vehicle-Borne Radar in Blackout Condition

    PubMed Central

    Li, Yanpeng; Li, Xiang; Wang, Hongqiang; Deng, Bin; Qin, Yuliang

    2016-01-01

    Radar is a very important sensor in surveillance applications. Near-space vehicle-borne radar (NSVBR) is a novel installation of a radar system, which offers many benefits, like being highly suited to the remote sensing of extremely large areas, having a rapidly deployable capability and having low vulnerability to electronic countermeasures. Unfortunately, a target detection challenge arises because of complicated scenarios, such as nuclear blackout, rain attenuation, etc. In these cases, extra care is needed to evaluate the detection performance in blackout situations, since this a classical problem along with the application of an NSVBR. However, the existing evaluation measures are the probability of detection and the receiver operating curve (ROC), which cannot offer detailed information in such a complicated application. This work focuses on such requirements. We first investigate the effect of blackout on an electromagnetic wave. Performance evaluation indexes are then built: three evaluation indexes on the detection capability and two evaluation indexes on the robustness of the detection process. Simulation results show that the proposed measure will offer information on the detailed performance of detection. These measures are therefore very useful in detecting the target of interest in a remote sensing system and are helpful for both the NSVBR designers and users. PMID:26751445

  18. Performance Evaluation of Target Detection with a Near-Space Vehicle-Borne Radar in Blackout Condition.

    PubMed

    Li, Yanpeng; Li, Xiang; Wang, Hongqiang; Deng, Bin; Qin, Yuliang

    2016-01-06

    Radar is a very important sensor in surveillance applications. Near-space vehicle-borne radar (NSVBR) is a novel installation of a radar system, which offers many benefits, like being highly suited to the remote sensing of extremely large areas, having a rapidly deployable capability and having low vulnerability to electronic countermeasures. Unfortunately, a target detection challenge arises because of complicated scenarios, such as nuclear blackout, rain attenuation, etc. In these cases, extra care is needed to evaluate the detection performance in blackout situations, since this a classical problem along with the application of an NSVBR. However, the existing evaluation measures are the probability of detection and the receiver operating curve (ROC), which cannot offer detailed information in such a complicated application. This work focuses on such requirements. We first investigate the effect of blackout on an electromagnetic wave. Performance evaluation indexes are then built: three evaluation indexes on the detection capability and two evaluation indexes on the robustness of the detection process. Simulation results show that the proposed measure will offer information on the detailed performance of detection. These measures are therefore very useful in detecting the target of interest in a remote sensing system and are helpful for both the NSVBR designers and users.

  19. KNN classification of metallic targets using the magnetic polarizability tensor

    NASA Astrophysics Data System (ADS)

    Makkonen, J.; Marsh, L. A.; Vihonen, J.; Järvi, A.; Armitage, D. W.; Visa, A.; Peyton, A. J.

    2014-05-01

    Walk-through metal detectors are used at check points for preventing personnel and passengers from carrying threatening metallic objects, such as knives and guns, into a secure area. These systems are capable of detecting small metallic items, such as handcuff keys and blades, but are unable to distinguish accurately between threatening objects and innocuous items. This paper studies the extent to which a K-nearest-neighbour classifier can distinguish various kinds of metallic objects, such as knives, shoe shanks, belts and containers. The classifier uses features extracted from the magnetic polarizability tensor, which represents the electromagnetic properties of the object. The tests include distinguishing threatening objects from innocuous ones, classifying a set of objects into 13 classes, and distinguishing between several similar objects within an object class. A walk-through metal detection system is used as source for the test data, which consist of 835 scans and 67 objects. The results presented show a typical success rate of over 95% for recognizing threats, and over 85% for correct classification. In addition, we have shown that the system is capable of distinguishing between similar objects reliably. Overall, the method shows promise for the field of security screening and suggests the need for further research.

  20. Optical correlator based target detection, recognition, classification, and tracking.

    PubMed

    Manzur, Tariq; Zeller, John; Serati, Steve

    2012-07-20

    A dedicated automatic target recognition and tracking optical correlator (OC) system using advanced processing technology has been developed. Rapidly cycling data-cubes with size, shape, and orientation are employed with software algorithms to isolate correlation peaks and enable tracking of targets in maritime environments with future track prediction. The method has been found superior to employing maximum average correlation height filters for which the correlation peak intensity drops off in proportion to the number of training images. The physical dimensions of the OC system may be reduced to as small as 2 in. × 2 in. × 3 in. (51 mm × 51 mm × 76 mm) by modifying and minimizing the OC components.

  1. Data fusion for target tracking and classification with wireless sensor network

    NASA Astrophysics Data System (ADS)

    Pannetier, Benjamin; Doumerc, Robin; Moras, Julien; Dezert, Jean; Canevet, Loic

    2016-10-01

    In this paper, we address the problem of multiple ground target tracking and classification with information obtained from a unattended wireless sensor network. A multiple target tracking (MTT) algorithm, taking into account road and vegetation information, is proposed based on a centralized architecture. One of the key issue is how to adapt classical MTT approach to satisfy embedded processing. Based on track statistics, the classification algorithm uses estimated location, velocity and acceleration to help to classify targets. The algorithms enables tracking human and vehicles driving both on and off road. We integrate road or trail width and vegetation cover, as constraints in target motion models to improve performance of tracking under constraint with classification fusion. Our algorithm also presents different dynamic models, to palliate the maneuvers of targets. The tracking and classification algorithms are integrated into an operational platform (the fusion node). In order to handle realistic ground target tracking scenarios, we use an autonomous smart computer deposited in the surveillance area. After the calibration step of the heterogeneous sensor network, our system is able to handle real data from a wireless ground sensor network. The performance of system is evaluated in a real exercise for intelligence operation ("hunter hunt" scenario).

  2. Detection and classification of underwater targets by echolocating dolphins

    NASA Astrophysics Data System (ADS)

    Au, Whitlow

    2003-10-01

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

  3. Biosonar acoustic images for target localization and classification by bats

    NASA Astrophysics Data System (ADS)

    Simmons, James A.

    1997-07-01

    Echolocating bats use sonar to guide interception of insects, recognize objects by shape, and even track prey in clutter. Broadcasts of the big brown bat are 0.5 to 20 ms FM signals in the 20-100 kHz ultrasonic band. Insects consist of several reflecting glints, each equivalent in cross- section to a small sphere of 2 mm to 2 cm radius, while clutter is typically composed of numerous glints distributed over a large volume. The bats' signals extend in space for many target lengths, while ka values for each glint are 0.5 to 30 across the broadcast band. Bats perceive acoustic images having echo delay as their primary dimension, and space is perceived in terms of the distribution of target glints in range. Range disparities between the ears provide two 'looks' at each target from slightly different locations as well as information about azimuth. The bats auditory system encodes the FM sweeps of broadcasts and echoes as linear-period spectrograms with integration-times of 300-400 micrometers . Bats nevertheless perceive individual glints in targets for echo-delay separations well inside the integration-time window. Deconvolution is achieved by spectrogram correlation in the time domain and spectral shape transformation in the frequency-domain, with all output evidently being displayed in the time domina. Neural responses in the bat's auditory system seem limited in time precision to 20-50 micrometers at best and 300 microsecond(s) to 3 ms in a broader sample, and stimulus phase is thought to be lost for frequencies above 1-3 kHz. Yet bats perceive echo delay with an accuracy of 10-15 ns and have two-echo resolution of about 2 microsecond(s) . Moreover, bats perceive echo phase-shifts as the correctly corresponding shifts in echo delay. Successive images are subtracted to enhance perception of shape from multiple 'looks', and echo phase is an integral part of this critical process. Utterly novel time-scale magnification appears in the bat's neural responses to

  4. Robust method for the matching of attributed scattering centers with application to synthetic aperture radar automatic target recognition

    NASA Astrophysics Data System (ADS)

    Ding, Baiyuan; Wen, Gongjian; Zhong, Jinrong; Ma, Conghui; Yang, Xiaoliang

    2016-01-01

    This paper proposes a robust method for the matching of attributed scattering centers (ASCs) with application to synthetic aperture radar automatic target recognition (ATR). For the testing image to be classified, ASCs are extracted to match with the ones predicted by templates. First, Hungarian algorithm is employed to match those two ASC sets initially. Then, a precise matching is carried out through a threshold method. Point similarity and structure similarity are calculated, which are fused to evaluate the overall similarity of the two ASC sets based on the Dempster-Shafer theory of evidence. Finally, the target type is determined by such similarities between the testing image and various types of targets. Experiments on the moving and stationary target acquisition and recognition data verify the validity of the proposed method.

  5. Target Localization by Resolving the Time Synchronization Problem in Bistatic Radar Systems Using Space Fast-Time Adaptive Processor

    NASA Astrophysics Data System (ADS)

    Madurasinghe, D.; Shaw, A. P.

    2009-12-01

    The proposed technique allows the radar receiver to accurately estimate the range of a large number of targets using a transmitter of opportunity as long as the location of the transmitter is known. The technique does not depend on the use of communication satellites or GPS systems, instead it relies on the availability of the direct transmit copy of the signal from the transmitter and the reflected paths off the various targets. An array-based space-fast time adaptive processor is implemented in order to estimate the path difference between the direct signal and the delayed signal, which bounces off the target. This procedure allows us to estimate the target distance as well as bearing.

  6. Adaptive sparse reconstruction with joint parametric estimation for high-speed uniformly moving targets in coincidence imaging radar

    NASA Astrophysics Data System (ADS)

    Zha, Guofeng; Wang, Hongqiang; Yang, Zhaocheng; Cheng, Yongqiang; Qin, Yuliang

    2016-04-01

    As a complementary imaging technology, coincidence imaging radar (CIR) achieves high resolution for stationary or low-speed targets under the assumption of ignoring the influence of the original position mismatching. As to high-speed moving targets moving from the original imaging cell to other imaging cells during imaging, it is inaccurate to reconstruct the target using the previous imaging plane. We focus on the recovery problem for high-speed moving targets in the CIR system based on the intrapulse frequency random modulation signal in a single pulse. The effects induced by the motion on the imaging performance are analyzed. Because the basis matrix in the CIR imaging equation is determined by the unknown velocity parameter of the moving target, both the target images and basis matrix should be estimated jointly. We propose an adaptive joint parametric estimation recovery algorithm based on the Tikhonov regularization method to update the target velocity and basis matrix adaptively and recover the target images synchronously. Finally, the target velocity and target images are obtained in an iterative manner. Simulation results are presented to demonstrate the efficiency of the proposed algorithm.

  7. Application of Cloude's target decomposition theorem to polarimetric imaging radar data

    NASA Technical Reports Server (NTRS)

    Vanzyl, Jakob J.

    1993-01-01

    In this paper we applied Cloude's decomposition to imaging radar polarimetry. We show in detail how the decomposition results can guide the interpretation of scattering from vegetated areas. For multifrequency polarimetric radar measurements of a clear-cut area, the decomposition leads us to conclude that the vegetation is probably thin compared to even the C-band radar wavelength of 6 cm. For a frosted area, we notice an increased amount of even number of reflection scattering at P-band and L-band, probably the result of penetration through the coniferous canopy resulting in trunk-ground double reflection scattering. However, the scattering for the forested area is still dominated by scattering from randomly oriented cylinders. It is found that these cylinders are thicker than in the case of clear-cut areas, leading us to conclude that scattering from the branches probably dominates in this case.

  8. Manmade target extraction based on multistage decision and its application for change detection in polarimetric synthetic aperture radar image

    NASA Astrophysics Data System (ADS)

    Cong, Runmin; Han, Ping; Li, Chongyi; He, Jiaji; Zhang, Zaiji

    2016-09-01

    Targets of interest are different in various applications in which manmade targets, such as aircraft, ships, and buildings, are given more attention. Manmade target extraction methods using synthetic aperture radar (SAR) images are designed in response to various demands, which include civil uses, business purposes, and military industries. This plays an increasingly vital role in monitoring, military reconnaissance, and precision strikes. Achieving accurate and complete results through traditional methods is becoming more challenging because of the scattered complexity of polarization in polarimetric synthetic aperture radar (PolSAR) image. A multistage decision-based method is proposed composed of power decision, dominant scattering mechanism decision, and reflection symmetry decision. In addition, the theories of polarimetric contrast enhancement, generalized Y decomposition, and maximum eigenvalue ratio are applied to assist the decision. Fully PolSAR data are adopted to evaluate and verify the approach. Experimental results show that the method can achieve an effective result with a lower false alarm rate and clear contours. Finally, on this basis, a universal framework of change detection for manmade targets is presented as an application of our method. Two sets of measured data are also used to evaluate and verify the effectiveness of the change-detection algorithm.

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

    PubMed Central

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

    2016-01-01

    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. PMID:26999140

  10. Misclassification Errors in Unsupervised Classification Methods. Comparison Based on the Simulation of Targeted Proteomics Data

    PubMed Central

    Andreev, Victor P; Gillespie, Brenda W; Helfand, Brian T; Merion, Robert M

    2016-01-01

    Unsupervised classification methods are gaining acceptance in omics studies of complex common diseases, which are often vaguely defined and are likely the collections of disease subtypes. Unsupervised classification based on the molecular signatures identified in omics studies have the potential to reflect molecular mechanisms of the subtypes of the disease and to lead to more targeted and successful interventions for the identified subtypes. Multiple classification algorithms exist but none is ideal for all types of data. Importantly, there are no established methods to estimate sample size in unsupervised classification (unlike power analysis in hypothesis testing). Therefore, we developed a simulation approach allowing comparison of misclassification errors and estimating the required sample size for a given effect size, number, and correlation matrix of the differentially abundant proteins in targeted proteomics studies. All the experiments were performed in silico. The simulated data imitated the expected one from the study of the plasma of patients with lower urinary tract dysfunction with the aptamer proteomics assay Somascan (SomaLogic Inc, Boulder, CO), which targeted 1129 proteins, including 330 involved in inflammation, 180 in stress response, 80 in aging, etc. Three popular clustering methods (hierarchical, k-means, and k-medoids) were compared. K-means clustering performed much better for the simulated data than the other two methods and enabled classification with misclassification error below 5% in the simulated cohort of 100 patients based on the molecular signatures of 40 differentially abundant proteins (effect size 1.5) from among the 1129-protein panel. PMID:27524871

  11. The Application of Linear Prediction to Sequential Classification of Radar Target Signatures

    DTIC Science & Technology

    1976-03-25

    the covariance matrix for the observation vector A k of.th k k fkO the i class. Qk is the squared Mahalanobis distance between the observation vector...the sequential decision rule is IKk1 1 f<-2 lnTA- W1 hk =Qk1 -Qk1 + ’nInK k > -2 InT W (17) k 2B where Qk and Q are the squared Mahalanobis distances ...each stage. The dimension of vectors and matrices in the incremental classifier is equal to nAp. The change in the squared Mahalanobis distances Q at

  12. Evaluation of System Identification Algorithms for Aspect-Independent Radar Target Classification

    DTIC Science & Technology

    1989-12-01

    WRITE(1,110) NPTS WRITE (1, 110) NRT WRITE (1, 110) Kd WRITE(1, 110) M WRITE(1,110) DELTAY WRITE (1, 110) NSTRTPT WRITE(1, 110) CAUS CLOE (1) IF (DSE...Rabiner Madan Code 1114SE Office of Naval Research 800 N. Quincy St. Arlington, Virginia 22209 13. Professor K. M. Chen Department of Electrical

  13. Time-reversal imaging with multiple signal classification considering multiple scattering between the targets

    NASA Astrophysics Data System (ADS)

    Gruber, Fred K.; Marengo, Edwin A.; Devaney, Anthony J.

    2004-06-01

    The time-reversal imaging with multiple signal classification method for the location of point targets developed within the framework of the Born approximation in Lehman and Devaney [``Transmission mode time-reversal super-resolution imaging,'' J. Acoust. Soc. Am. 113, 2742-2753 (2003)] is generalized to incorporate multiple scattering between the targets. It is shown how the same method can be used in the location of point targets even if there is multiple scattering between them. On the other hand, both the conventional images and the calculated values of the target scattering amplitudes are scattering model-dependent.

  14. Absolute Radiometric Calibration of ALS Intensity Data: Effects on Accuracy and Target Classification

    PubMed Central

    Kaasalainen, Sanna; Pyysalo, Ulla; Krooks, Anssi; Vain, Ants; Kukko, Antero; Hyyppä, Juha; Kaasalainen, Mikko

    2011-01-01

    Radiometric calibration of airborne laser scanning (ALS) intensity data aims at retrieving a value related to the target scattering properties, which is independent on the instrument or flight parameters. The aim of a calibration procedure is also to be able to compare results from different flights and instruments, but practical applications are sparsely available, and the performance of calibration methods for this purpose needs to be further assessed. We have studied the radiometric calibration with data from three separate flights and two different instruments using external calibration targets. We find that the intensity data from different flights and instruments can be compared to each other only after a radiometric calibration process using separate calibration targets carefully selected for each flight. The calibration is also necessary for target classification purposes, such as separating vegetation from sand using intensity data from different flights. The classification results are meaningful only for calibrated intensity data. PMID:22346660

  15. Studies on Radar Sensor Networks

    DTIC Science & Technology

    2007-08-08

    through-foliage target detection using UWB radar sensor network based on real-world data; 2. Foliage clutter modeling using UWB radars; 3. Outdoor UWB...channel modeling based on field data; 4. Multi-target detection using radar sensor networks (theoretical studies); 5. SVD-QR and graph theory for MIMO...Foliage clutter modeling using UWB radars; 3. Outdoor UWB channel modeling based on field data; 4. Multi-target detection using radar sensor networks

  16. Seismic Target Classification Using a Wavelet Packet Manifold in Unattended Ground Sensors Systems

    PubMed Central

    Huang, Jingchang; Zhou, Qianwei; Zhang, Xin; Song, Enliang; Li, Baoqing; Yuan, Xiaobing

    2013-01-01

    One of the most challenging problems in target classification is the extraction of a robust feature, which can effectively represent a specific type of targets. The use of seismic signals in unattended ground sensor (UGS) systems makes this problem more complicated, because the seismic target signal is non-stationary, geology-dependent and with high-dimensional feature space. This paper proposes a new feature extraction algorithm, called wavelet packet manifold (WPM), by addressing the neighborhood preserving embedding (NPE) algorithm of manifold learning on the wavelet packet node energy (WPNE) of seismic signals. By combining non-stationary information and low-dimensional manifold information, WPM provides a more robust representation for seismic target classification. By using a K nearest neighbors classifier on the WPM signature, the algorithm of wavelet packet manifold classification (WPMC) is proposed. Experimental results show that the proposed WPMC can not only reduce feature dimensionality, but also improve the classification accuracy up to 95.03%. Moreover, compared with state-of-the-art methods, WPMC is more suitable for UGS in terms of recognition ratio and computational complexity. PMID:23881125

  17. Seismic target classification using a wavelet packet manifold in unattended ground sensors systems.

    PubMed

    Huang, Jingchang; Zhou, Qianwei; Zhang, Xin; Song, Enliang; Li, Baoqing; Yuan, Xiaobing

    2013-07-04

    One of the most challenging problems in target classification is the extraction of a robust feature, which can effectively represent a specific type of targets. The use of seismic signals in unattended ground sensor (UGS) systems makes this problem more complicated, because the seismic target signal is non-stationary, geology-dependent and with high-dimensional feature space. This paper proposes a new feature extraction algorithm, called wavelet packet manifold (WPM), by addressing the neighborhood preserving embedding (NPE) algorithm of manifold learning on the wavelet packet node energy (WPNE) of seismic signals. By combining non-stationary information and low-dimensional manifold information, WPM provides a more robust representation for seismic target classification. By using a K nearest neighbors classifier on the WPM signature, the algorithm of wavelet packet manifold classification (WPMC) is proposed. Experimental results show that the proposed WPMC can not only reduce feature dimensionality, but also improve the classification accuracy up to 95.03%. Moreover, compared with state-of-the-art methods, WPMC is more suitable for UGS in terms of recognition ratio and computational complexity.

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

    PubMed Central

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

    2015-01-01

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

  19. Non-cooperative target recognition by means of singular value decomposition applied to radar high resolution range profiles.

    PubMed

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

    2014-12-29

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

  20. Application of SEASAT-1 Synthetic Aperture Radar (SAR) data to enhance and detect geological lineaments and to assist LANDSAT landcover classification mapping. [Appalachian Region, West Virginia

    NASA Technical Reports Server (NTRS)

    Sekhon, R.

    1981-01-01

    Digital SEASAT-1 synthetic aperture radar (SAR) data were used to enhance linear features to extract geologically significant lineaments in the Appalachian region. Comparison of Lineaments thus mapped with an existing lineament map based on LANDSAT MSS images shows that appropriately processed SEASAT-1 SAR data can significantly improve the detection of lineaments. Merge MSS and SAR data sets were more useful fo lineament detection and landcover classification than LANDSAT or SEASAT data alone. About 20 percent of the lineaments plotted from the SEASAT SAR image did not appear on the LANDSAT image. About 6 percent of minor lineaments or parts of lineaments present in the LANDSAT map were missing from the SEASAT map. Improvement in the landcover classification (acreage and spatial estimation accuracy) was attained by using MSS-SAR merged data. The aerial estimation of residential/built-up and forest categories was improved. Accuracy in estimating the agricultural and water categories was slightly reduced.

  1. Measuring elimination of podoconiosis, endemicity classifications, case definition and targets: an international Delphi exercise

    PubMed Central

    Deribe, Kebede; Wanji, Samuel; Shafi, Oumer; Muheki Tukahebwa, Edridah; Umulisa, Irenee; Davey, Gail

    2015-01-01

    Background Podoconiosis is one of the major causes of lymphoedema in the tropics. Nonetheless, currently there are no endemicity classifications or elimination targets to monitor the effects of interventions. This study aimed at establishing case definitions and indicators that can be used to assess endemicity, elimination and clinical outcomes of podoconiosis. Methods This paper describes the result of a Delphi technique used among 28 experts. A questionnaire outlining possible case definitions, endemicity classifications, elimination targets and clinical outcomes was developed. The questionnaire was distributed to experts working on podoconiosis and other neglected tropical diseases in two rounds. The experts rated the importance of case definitions, endemic classifications, elimination targets and the clinical outcome measures. Median and mode were used to describe the central tendency of expert responses. The coefficient of variation was used to describe the dispersals of expert responses. Results Consensus on definitions and indicators for assessing endemicity, elimination and clinical outcomes of podoconiosis directed at policy makers and health workers was achieved following the two rounds of Delphi approach among the experts. Conclusions Based on the two Delphi rounds we discuss potential indicators and endemicity classification of this disabling disease, and the ongoing challenges to its elimination in countries with the highest prevalence. Consensus will help to increase effectiveness of podoconiosis elimination efforts and ensure comparability of outcome data. PMID:26185194

  2. Measuring elimination of podoconiosis, endemicity classifications, case definition and targets: an international Delphi exercise.

    PubMed

    Deribe, Kebede; Wanji, Samuel; Shafi, Oumer; Muheki Tukahebwa, Edridah; Umulisa, Irenee; Davey, Gail

    2015-09-01

    Podoconiosis is one of the major causes of lymphoedema in the tropics. Nonetheless, currently there are no endemicity classifications or elimination targets to monitor the effects of interventions. This study aimed at establishing case definitions and indicators that can be used to assess endemicity, elimination and clinical outcomes of podoconiosis. This paper describes the result of a Delphi technique used among 28 experts. A questionnaire outlining possible case definitions, endemicity classifications, elimination targets and clinical outcomes was developed. The questionnaire was distributed to experts working on podoconiosis and other neglected tropical diseases in two rounds. The experts rated the importance of case definitions, endemic classifications, elimination targets and the clinical outcome measures. Median and mode were used to describe the central tendency of expert responses. The coefficient of variation was used to describe the dispersals of expert responses. Consensus on definitions and indicators for assessing endemicity, elimination and clinical outcomes of podoconiosis directed at policy makers and health workers was achieved following the two rounds of Delphi approach among the experts. Based on the two Delphi rounds we discuss potential indicators and endemicity classification of this disabling disease, and the ongoing challenges to its elimination in countries with the highest prevalence. Consensus will help to increase effectiveness of podoconiosis elimination efforts and ensure comparability of outcome data. © The Author 2015. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene.

  3. Ionospheric Scintillation Effects on a Space-Based, Foliage Penetration, Ground Moving Target Indication Radar

    DTIC Science & Technology

    2001-08-01

    3.4 WBMOD Model and SCINTMOD Program........................................................ 3-3 4. RADAR PERFORMANCE SIMULATION... WBMOD , for predicting S4 values as a function of all of the inputs above. However, it is proprietary software, and the developer charges for its use...scintillation conditions are of interest, not location and time-specific predictions as would be provided by WBMOD . 2.4.1 Temporal and Spatial Distributions of

  4. Over-the-Horizon Radar Detection of Targets via Specular Scatter from Meteor Trails

    DTIC Science & Technology

    1988-09-27

    assumpten is roughly valid cor all polari- zations at the longer ranges and for horizontally polarized energy incident on the meteor trail for short...ranges. However, due Dn Faraday rotation in the ionosphere. the polarization of the radar energy incident of the meteor trail is unknown, Thus. these are...maximum values with respect to polarization considerations. The abscissa of each plot spans the -round range in kilometers to the nadir of all meteor

  5. Analysis of Matched Filter Mismatch for Focusing Moving Targets in Multi-channel Synthetic Aperture Radar

    DTIC Science & Technology

    2014-09-01

    Synthetic Aperture Radar ( SAR ) systems after clutter cancellation has been performed. The Displaced Phase Centre Antenna (DPCA) is utilized to achieve...the clutter cancellation in a two channel SAR system. After deriving the matched filter, the tolerance of the filter is then analyzed for mismatches...against errors in the moving target’s position and velocity components. The tolerances are quantified for two exemplar SAR systems; an X-band airborne

  6. Application of Cloude's target decomposition theorem to polarimetric imaging radar data

    NASA Technical Reports Server (NTRS)

    Vanzyl, Jakob J.

    1993-01-01

    We apply Cloude's decomposition to imaging radar polarimetry. We derive the general expressions for the eigenvalues and eigenvectors for the case of terrain with reflection symmetry, and show in detail how the decomposition results can guide the interpretation of scattering from vegetated areas. For multi-frequency polarimetric radar measurements of a clear-cut area, the decomposition leads us to conclude that the vegetation is probably thin compared to even the C-band radar wavelength of 6 cm. For a forested area, we notice an increased amount of even number of reflection scattering at P-band and L-band, probably the result of penetration through the coniferous canopy resulting in trunk-ground double reflection scattering. The scattering for the forested area is still dominated by scattering from randomly oriented cylinders, however. It is found that these cylinders are thicker than in the case of clear-cut areas, leading us to conclude that scattering from the branches probably dominate in this case.

  7. Advanced EMI models for survey data processing: targets detection and classification

    NASA Astrophysics Data System (ADS)

    Shubitidze, F.; Sigman, J. B.; Wang, Yinlin; Miller, J.; Keranen, J.; Shamatava, I.; Barrowes, B. E.; O'Neill, K.

    2014-06-01

    One of the most challenging aspects of survey data processing is target selection. The fundamental input for the classification is dynamic data collected along survey lines. These data are different from the static data obtained in cued mode and used for target classification. Survey data are typically collected using just one transmitter loop (the Z-axis loop) and feature short data point collection times and short decay transience. The collection intervals for each data point are typically 0.1 s, and the signal repetition rates are typically 90 or 270 Hz (in other words, the transient decay times are 2.7 ms or 0.9 ms). Reliable classification requires multiple side/angle illumination; i.e., to conduct reliable classification it is necessary to combine and jointly invert multiple data points. However, picking data points that provide optimal information for classifying targets is a difficult task. The traditional method plots signal amplitudes on a 2D map and picks peaks of signal level without properly accounting for the underlying physics. In this paper, the joint diagonalization is applied to survey data sets to improve data pre-processing and target picking. The JD technique is an EMI data analysis and target classification technique and is applicable for all next-generation multi-static array EMI sensors. The method extracts multi-static response data matrix eigenvalues. The eigenvalues are main characteristics of the data. Recent studies have demonstrated that the method has great potential to quickly estimate the number of potential targets and moreover classify these targets at the data pre-processing stage, in real time and without the need for a forward model. Another advantage of JD is that it provides the ability to separate signal from noise making it possible to de-noise data without distorting the signal due to the targets. In this paper the JD technique is used to process dynamic data collected at South West Proving Ground and Aberdeen Proving

  8. Detection and Classification of Finer-Grained Human Activities Based on Stepped-Frequency Continuous-Wave Through-Wall Radar

    PubMed Central

    Qi, Fugui; Liang, Fulai; Lv, Hao; Li, Chuantao; Chen, Fuming; Wang, Jianqi

    2016-01-01

    The through-wall detection and classification of human activities are critical for anti-terrorism, security, and disaster rescue operations. An effective through-wall detection and classification technology is proposed for finer-grained human activities such as piaffe, picking up an object, waving, jumping, standing with random micro-shakes, and breathing while sitting. A stepped-frequency continuous wave (SFCW) bio-radar sensor is first used to conduct through-wall detection of finer-grained human activities; Then, a comprehensive range accumulation time-frequency transform (CRATFR) based on inverse weight coefficients is proposed, which aims to strengthen the micro-Doppler features of finer activity signals. Finally, in combination with the effective eigenvalues extracted from the CRATFR spectrum, an optimal self-adaption support vector machine (OS-SVM) based on prior human position information is introduced to classify different finer-grained activities. At a fixed position (3 m) behind a wall, the classification accuracies of six activities performed by eight individuals were 98.78% and 93.23%, respectively, for the two scenarios defined in this paper. In the position-changing experiment, an average classification accuracy of 86.67% was obtained for five finer-grained activities (excluding breathing) of eight individuals within 6 m behind the wall for the most practical scenario, a significant improvement over the 79% accuracy of the current method. PMID:27314362

  9. Detection and Classification of Finer-Grained Human Activities Based on Stepped-Frequency Continuous-Wave Through-Wall Radar.

    PubMed

    Qi, Fugui; Liang, Fulai; Lv, Hao; Li, Chuantao; Chen, Fuming; Wang, Jianqi

    2016-06-15

    The through-wall detection and classification of human activities are critical for anti-terrorism, security, and disaster rescue operations. An effective through-wall detection and classification technology is proposed for finer-grained human activities such as piaffe, picking up an object, waving, jumping, standing with random micro-shakes, and breathing while sitting. A stepped-frequency continuous wave (SFCW) bio-radar sensor is first used to conduct through-wall detection of finer-grained human activities; Then, a comprehensive range accumulation time-frequency transform (CRATFR) based on inverse weight coefficients is proposed, which aims to strengthen the micro-Doppler features of finer activity signals. Finally, in combination with the effective eigenvalues extracted from the CRATFR spectrum, an optimal self-adaption support vector machine (OS-SVM) based on prior human position information is introduced to classify different finer-grained activities. At a fixed position (3 m) behind a wall, the classification accuracies of six activities performed by eight individuals were 98.78% and 93.23%, respectively, for the two scenarios defined in this paper. In the position-changing experiment, an average classification accuracy of 86.67% was obtained for five finer-grained activities (excluding breathing) of eight individuals within 6 m behind the wall for the most practical scenario, a significant improvement over the 79% accuracy of the current method.

  10. Micro-Doppler processing for ultra-wideband radar data

    NASA Astrophysics Data System (ADS)

    Smith, Graeme E.; Ahmad, Fauzia; Amin, Moeness G.

    2012-06-01

    In this paper, we describe an operational pulse Doppler radar imaging system for indoor target localization and classification, and show how a target's micro-Doppler signature (μDS) can be processed when ultra-wideband (UWB) waveforms are employed. Unlike narrowband radars where time-frequency signal representations can be applied to reveal the target time-Doppler frequency signatures, the UWB system permits joint range-time-frequency representation (JRTFR). JRTFR outputs the data in a 3D domain representing range, frequency, and time, allowing both the μDS and high range resolution (HRR) signatures to be observed. We delineate the relationship between the μDS and the HRR signature, showing how they would form a complimentary joint feature for classification. We use real-data to demonstrate the effectiveness of the UWB pulse-Doppler radar, combined with nonstationary signal analyses, in gaining valuable insights into human positioning and motions.

  11. Focusing vibrating targets in frequency-modulation continuous-wave-synthetic aperture radar with Doppler keystone transform

    NASA Astrophysics Data System (ADS)

    Hu, Yuxin; Zhang, Yuan; Sun, Jinping; Lei, Peng

    2016-04-01

    Vibrating targets generally induce sinusoidal micro-Doppler modulation in high resolution synthetic aperture radar (SAR). They could cause defocused and ghost results by conventional imaging algorithms. This paper proposes a method on vibrating target imaging in frequency-modulation continuous-wave (FMCW) SAR systems. The continuous motion of sensor platform during pulse time is considered in the signal model. Based on Bessel series expansion of the signal in the azimuth direction, the influence of platform motion on the azimuth frequency is eliminated after dechirp and deskew. In addition, the range walk is compensated in the two-dimensional frequency domain by Doppler keystone transform. Next, using range cell migration correction, the azimuth quadratic phase compensation and the range curvature correction are made in range-Doppler domain for the focus of paired echoes. The residual video phase of paired echoes is eliminated, and vibration parameters are estimated to compensate in the sinusoidal modulation phase. Then the deghosted image of vibrating targets can be obtained. The proposed method is applicable to multiple targets with various vibrating states due to no need of a priori knowledge of targets. Finally, simulations are carried out to validate the effectiveness of the method in FMCW-SAR imaging of vibrating targets.

  12. Parametric bicubic spline and CAD tools for complex targets shape modelling in physical optics radar cross section prediction

    NASA Astrophysics Data System (ADS)

    Delogu, A.; Furini, F.

    1991-09-01

    Increasing interest in radar cross section (RCS) reduction is placing new demands on theoretical, computation, and graphic techniques for calculating scattering properties of complex targets. In particular, computer codes capable of predicting the RCS of an entire aircraft at high frequency and of achieving RCS control with modest structural changes, are becoming of paramount importance in stealth design. A computer code, evaluating the RCS of arbitrary shaped metallic objects that are computer aided design (CAD) generated, and its validation with measurements carried out using ALENIA RCS test facilities are presented. The code, based on the physical optics method, is characterized by an efficient integration algorithm with error control, in order to contain the computer time within acceptable limits, and by an accurate parametric representation of the target surface in terms of bicubic splines.

  13. Object-oriented fusion of RADARSAT-2 polarimetric synthetic aperture radar and HJ-1A multispectral data for land-cover classification

    NASA Astrophysics Data System (ADS)

    Xiao, Yan; Jiang, Qigang; Wang, Bin; Li, Yuanhua; Liu, Shu; Cui, Can

    2016-04-01

    The contribution of the integration of optical and polarimetric synthetic aperture radar (PolSAR) data to accurate land-cover classification was investigated. For this purpose, an object-oriented classification methodology that consisted of polarimetric decomposition, hybrid feature selection, and a support vector machine (SVM) was proposed. A RADARSAT-2 Fine Quad-Pol image and an HJ-1A CCD2 multispectral image were used as data sources. First, polarimetric decomposition was implemented for the RADARSAT-2 image. Sixty-one polarimetric parameters were extracted using different polarimetric decomposition methods and then merged with the main diagonal elements (T11, T22, T33) of the coherency matrix to form a multichannel image with 64 layers. Second, the HJ-1A and the multichannel images were divided into numerous image objects by implementing multiresolution segmentation. Third, 1104 features were extracted from the HJ-1A and the multichannel images for each image object. Fourth, the hybrid feature selection method that combined the ReliefF filter approach and the genetic algorithm (GA) wrapper approach (ReliefF-GA) was used. Finally, land-cover classification was performed by an SVM classifier on the basis of the selected features. Five other classification methodologies were conducted for comparison to verify the contribution of optical and PolSAR data integration and to test the superiority of the proposed object-oriented classification methodology. Comparison results show that HJ-1A data, RADARSAT-2 data, polarimetric decomposition, ReliefF-GA, and SVM have a significant contribution by improving land-cover classification accuracy.

  14. Classification of video sequences into chosen generalized use classes of target size and lighting level.

    PubMed

    Leszczuk, Mikołaj; Dudek, Łukasz; Witkowski, Marcin

    The VQiPS (Video Quality in Public Safety) Working Group, supported by the U.S. Department of Homeland Security, has been developing a user guide for public safety video applications. According to VQiPS, five parameters have particular importance influencing the ability to achieve a recognition task. They are: usage time-frame, discrimination level, target size, lighting level, and level of motion. These parameters form what are referred to as Generalized Use Classes (GUCs). The aim of our research was to develop algorithms that would automatically assist classification of input sequences into one of the GUCs. Target size and lighting level parameters were approached. The experiment described reveals the experts' ambiguity and hesitation during the manual target size determination process. However, the automatic methods developed for target size classification make it possible to determine GUC parameters with 70 % compliance to the end-users' opinion. Lighting levels of the entire sequence can be classified with an efficiency reaching 93 %. To make the algorithms available for use, a test application has been developed. It is able to process video files and display classification results, the user interface being very simple and requiring only minimal user interaction.

  15. Polarization Radar Processing Technology

    DTIC Science & Technology

    1989-10-01

    Oi"C FILE ( J qII RADC-TR-89-144 In-House Report October 1989 AD-A215 242 POLARIZATION RADAR PROCESSING TECHNOLOGY Kenneth C. Stiefvater, Russell D...NO. NO. NO. ACCESSION NO. 62702F 4506 11 58 11. TITLE (Include Security Classification) POLARIZATION RADAR PROCESSING TECHNOLOGY 12. PERSONAL AUTHOR(S

  16. Joint DOD/DOA Estimation in MIMO Radar Exploiting Time-Frequency Signal Representations

    DTIC Science & Technology

    2012-05-08

    direction-of-departure (DOD) and direction-of- arrival (DOA) information of maneuvering targets in a bistatic multiple-input multiple-output (MIMO) radar...CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Same as Report ( SAR ) 18. NUMBER OF PAGES 21 19a. NAME OF RESPONSIBLE PERSON a. REPORT unclassified b...departure (DOD) and direction-of- arrival (DOA) information of maneuvering targets in a bistatic multiple-input multiple-output (MIMO) radar system

  17. Contribution of Small-Scale Correlated Fluctuations of Microstructural Properties of a Spatially Extended Geophysical Target Under the Assessment of Radar Backscatter

    NASA Technical Reports Server (NTRS)

    Yurchak, Boris S.

    2010-01-01

    The study of the collective effects of radar scattering from an aggregation of discrete scatterers randomly distributed in a space is important for better understanding the origin of the backscatter from spatially extended geophysical targets (SEGT). We consider the microstructure irregularities of a SEGT as the essential factor that affect radar backscatter. To evaluate their contribution this study uses the "slice" approach: particles close to the front of incident radar wave are considered to reflect incident electromagnetic wave coherently. The radar equation for a SEGT is derived. The equation includes contributions to the total backscatter from correlated small-scale fluctuations of the slice's reflectivity. The correlation contribution changes in accordance with an earlier proposed idea by Smith (1964) based on physical consideration. The slice approach applied allows parameterizing the features of the SEGT's inhomogeneities.

  18. Infrared small target tracking by discriminative classification based on Gaussian mixture model in compressive sensing domain

    NASA Astrophysics Data System (ADS)

    Wang, Chuanyun; Song, Fei; Qin, Shiyin

    2017-02-01

    Addressing the problems of infrared small target tracking in forward looking infrared (FLIR) system, a new infrared small target tracking method is presented, in which features binding of both target gray intensity and spatial relationship is implemented by compressive sensing so as to construct the Gaussian mixture model of compressive appearance distribution. Subsequently, naive Bayesian classification is carried out over testing samples acquired with non-uniform sampling probability to identify the most credible location of targets from background scene. A series of experiments are carried out over four infrared small target image sequences with more than 200 images for each sequence, the results demonstrate the effectiveness and advantages of the proposed method in both success rate and precision rate.

  19. Classification

    ERIC Educational Resources Information Center

    Clary, Renee; Wandersee, James

    2013-01-01

    In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

  20. Classification

    ERIC Educational Resources Information Center

    Clary, Renee; Wandersee, James

    2013-01-01

    In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

  1. Sequence-Based Classification Scheme for the Genus Legionella Targeting the mip Gene

    PubMed Central

    Ratcliff, Rodney M.; Lanser, Janice A.; Manning, Paul A.; Heuzenroeder, Michael W.

    1998-01-01

    The identification and speciation of strains of Legionella is often difficult, and even the more successful chromatographic classification techniques have struggled to discriminate newly described species. A sequence-based genotypic classification scheme is reported, targeting approximately 700 nucleotide bases of the mip gene and utilizing gene amplification and direct amplicon sequencing. With the exception of Legionella geestiana, for which an amplicon was not produced, the scheme clearly and unambiguously discriminated among the remaining 39 Legionella species and correctly grouped 26 additional serogroup and reference strains within those species. Additionally, the genotypic classification of approximately 150 wild strains from several continents was consistent with their phenotypic classification, with the exception of a few strains where serological cross-reactivity was complex, potentially confusing the latter classification. Strains thought to represent currently uncharacterized species were also found to be genotypically unique. The scheme is technically simple for a laboratory with even basic molecular capabilities and equipment, if access to a sequencing laboratory is available. PMID:9620377

  2. Spatiotemporal representations of rapid visual target detection: a single-trial EEG classification algorithm.

    PubMed

    Fuhrmann Alpert, Galit; Manor, Ran; Spanier, Assaf B; Deouell, Leon Y; Geva, Amir B

    2014-08-01

    Brain computer interface applications, developed for both healthy and clinical populations, critically depend on decoding brain activity in single trials. The goal of the present study was to detect distinctive spatiotemporal brain patterns within a set of event related responses. We introduce a novel classification algorithm, the spatially weighted FLD-PCA (SWFP), which is based on a two-step linear classification of event-related responses, using fisher linear discriminant (FLD) classifier and principal component analysis (PCA) for dimensionality reduction. As a benchmark algorithm, we consider the hierarchical discriminant component Analysis (HDCA), introduced by Parra, et al. 2007. We also consider a modified version of the HDCA, namely the hierarchical discriminant principal component analysis algorithm (HDPCA). We compare single-trial classification accuracies of all the three algorithms, each applied to detect target images within a rapid serial visual presentation (RSVP, 10 Hz) of images from five different object categories, based on single-trial brain responses. We find a systematic superiority of our classification algorithm in the tested paradigm. Additionally, HDPCA significantly increases classification accuracies compared to the HDCA. Finally, we show that presenting several repetitions of the same image exemplars improve accuracy, and thus may be important in cases where high accuracy is crucial.

  3. Multi-agent Negotiation Mechanisms for Statistical Target Classification in Wireless Multimedia Sensor Networks

    PubMed Central

    Wang, Xue; Bi, Dao-wei; Ding, Liang; Wang, Sheng

    2007-01-01

    The recent availability of low cost and miniaturized hardware has allowed wireless sensor networks (WSNs) to retrieve audio and video data in real world applications, which has fostered the development of wireless multimedia sensor networks (WMSNs). Resource constraints and challenging multimedia data volume make development of efficient algorithms to perform in-network processing of multimedia contents imperative. This paper proposes solving problems in the domain of WMSNs from the perspective of multi-agent systems. The multi-agent framework enables flexible network configuration and efficient collaborative in-network processing. The focus is placed on target classification in WMSNs where audio information is retrieved by microphones. To deal with the uncertainties related to audio information retrieval, the statistical approaches of power spectral density estimates, principal component analysis and Gaussian process classification are employed. A multi-agent negotiation mechanism is specially developed to efficiently utilize limited resources and simultaneously enhance classification accuracy and reliability. The negotiation is composed of two phases, where an auction based approach is first exploited to allocate the classification task among the agents and then individual agent decisions are combined by the committee decision mechanism. Simulation experiments with real world data are conducted and the results show that the proposed statistical approaches and negotiation mechanism not only reduce memory and computation requirements in WMSNs but also significantly enhance classification accuracy and reliability. PMID:28903223

  4. Underwater target classification in changing environments using an adaptive feature mapping.

    PubMed

    Azimi-Sadjadi, M R; Yao, D; Jamshidi, A A; Dobeck, G J

    2002-01-01

    A new adaptive underwater target classification system to cope with environmental changes in acoustic backscattered data from targets and nontargets is introduced. The core of the system is the adaptive feature mapping that minimizes the classification error rate of the classifier. The goal is to map the feature vector in such a way that the mapped version remains invariant to the environmental changes. A K-nearest neighbor (K-NN) system is used as a memory to provide the closest matches of an unknown pattern in the feature space. The classification decision is done by a backpropagation neural network (BPNN). Two different cost functions for adaptation are defined. These two cost functions are then combined together to improve the classification performance. The test results on a 40-kHz linear FM acoustic backscattered data set collected from six different objects are presented. These results demonstrate the effectiveness of the adaptive system versus nonadaptive system when the signal-to-reverberation ratio (SRR) in the environment is varying.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-10-27

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

  7. Sparse and low-rank feature extraction for the classification of target's tracking capability

    NASA Astrophysics Data System (ADS)

    Rasti, Behnood; Gudmundsson, Karl S.

    2016-09-01

    A feature extraction-based classification method is proposed in this paper for verifying the capability of human's neck in target tracking. Here, the target moves in predefined trajectory patterns in three difficulty levels. Dataset used for each pattern is obtained from two groups of people, one with whiplash associated disorder (WAD) and asymptomatic group, who behave in both sincere and feign manner. The aim is to verify the WAD group from asymptomatic one and also to discriminate the sincere behavior from the feigned one. Sparse and low-rank feature extraction is proposed to extract the most informative feature from training samples and then each sample is classified into the group which has the highest correlation coefficient with. The classification results are improved by fusing the results of the three patterns.

  8. A novel neural network based image reconstruction model with scale and rotation invariance for target identification and classification for Active millimetre wave imaging

    NASA Astrophysics Data System (ADS)

    Agarwal, Smriti; Bisht, Amit Singh; Singh, Dharmendra; Pathak, Nagendra Prasad

    2014-12-01

    Millimetre wave imaging (MMW) is gaining tremendous interest among researchers, which has potential applications for security check, standoff personal screening, automotive collision-avoidance, and lot more. Current state-of-art imaging techniques viz. microwave and X-ray imaging suffers from lower resolution and harmful ionizing radiation, respectively. In contrast, MMW imaging operates at lower power and is non-ionizing, hence, medically safe. Despite these favourable attributes, MMW imaging encounters various challenges as; still it is very less explored area and lacks suitable imaging methodology for extracting complete target information. Keeping in view of these challenges, a MMW active imaging radar system at 60 GHz was designed for standoff imaging application. A C-scan (horizontal and vertical scanning) methodology was developed that provides cross-range resolution of 8.59 mm. The paper further details a suitable target identification and classification methodology. For identification of regular shape targets: mean-standard deviation based segmentation technique was formulated and further validated using a different target shape. For classification: probability density function based target material discrimination methodology was proposed and further validated on different dataset. Lastly, a novel artificial neural network based scale and rotation invariant, image reconstruction methodology has been proposed to counter the distortions in the image caused due to noise, rotation or scale variations. The designed neural network once trained with sample images, automatically takes care of these deformations and successfully reconstructs the corrected image for the test targets. Techniques developed in this paper are tested and validated using four different regular shapes viz. rectangle, square, triangle and circle.

  9. Performance Comparison of Feature Extraction Algorithms for Target Detection and Classification

    DTIC Science & Technology

    2013-01-01

    Succi, D. Clapp, R. Gampert, and G. Prado, “ Footstep detection and tracking,” Unattended Ground Sensor Technologies and Applications III, vol. 4393... Detection and Classification⋆ Soheil Bahrampour1 Asok Ray2 Soumalya Sarkar2 Thyagaraju Damarla3 Nasser M. Nasrabadi3 Keywords: Feature Extraction...rithm, symbolic dynamic filtering (SDF), is investigated for target detection and classification by using unmanned ground sensors (UGS). In SDF, sensor

  10. On the range resolution of point targets with FMCW radar systems

    NASA Astrophysics Data System (ADS)

    Hammel, Reinhard

    1989-08-01

    The range information with Frequency Modulated Continuous Wave (FMCW) radar systems is discrete within multiples of the modulation frequency. There is a correspondance between the spectral lines and discrete distance values. Even though the classical spectral theory defines the resolution to be 1.2 it is shown that with a FMCW-radar a resolution of only 2.1 is attainable because of harmonic interferences. The prerequisite of the equipment in order to achieve this resolution is a limitation of the relative fluctuation of the slope of the transmitting frequency variation. Without any control circuit for the transmitting frequency slope, this condition can be satisfied with a programmable wave-form device if a dynamic correction of the transmitting frequency slope was determined before. It is shown that by a variation of the modulation frequency and the modulation-bandwidth simultaneously, the envelope of the pseudo-Doppler spectrum can be sampled at much more discrete, but not any longer equidistant points, resulting in an improved resolution of 1.5.

  11. Entropy-Based Classification of Subsurface Scatterers: A Valuable Tool for the Analysis of Data Obtained by the Fully Polarimetric WISDOM Radar

    NASA Astrophysics Data System (ADS)

    Plettemeier, D.; Statz, C.; Hahnel, R.; Benedix, W. S.; Hamran, S. E.; Ciarletti, V.

    2016-12-01

    The "Water Ice Subsurface Deposition on Mars" Experiment (WISDOM) is a Ground Penetrating Radar (GPR) and part of the 2020 ExoMars Rover payload. It will be the first GPR operating on a planetary rover and the first fully polarimetric radar tasked at probing the subsurface of Mars. WISDOM operates at frequencies between 500 MHz and 3 GHz yielding a centimetric resolution and a penetration depth of about 3 meters in Martian soil. Its prime scientific objective is the detailed characterization of the material distribution within the first few meters of the Martian subsurface as a contribution to the search for evidence of past life. For the first time, WISDOM will give access to the geological structure, electromagnetic nature, and hydrological state of the shallow subsurface by retrieving the layering and properties of the buried reflectors at an unprecedented resolution and, due to the fully polarimetric measurements, amount of information. Furthermore, a "real time" subsurface analysis will support the drill operations by identifying locations of high scientific interest and low risk. Key element in the WISDOM data analysis is the fast and reliable classification and correct localization of subsurface scatterers and layers. The fully polarimetric nature of the WISDOM measurements allows the use of the entropy-alpha decomposition (H-alpha). This method enables the classification of reconstructed images of the subsurface (obtained by inverse imaging algorithms, e.g. f-k migration) with regard to the main scattering mechanisms of geological features present in the image of the subsurface. It is, for example, possible to differentiate smooth surfaces, rough surfaces, isolated spherical scatterers, double- and bounce scattering, anisotropic scatterers, clouds of small scatterers of similar shape as well as layers of oblate spheroids. Preliminary tests under laboratory conditions suggest the feasibility and value of the approach for the classification of geological

  12. Three-Dimensional ISAR Imaging Method for High-Speed Targets in Short-Range Using Impulse Radar Based on SIMO Array

    PubMed Central

    Zhou, Xinpeng; Wei, Guohua; Wu, Siliang; Wang, Dawei

    2016-01-01

    This paper proposes a three-dimensional inverse synthetic aperture radar (ISAR) imaging method for high-speed targets in short-range using an impulse radar. According to the requirements for high-speed target measurement in short-range, this paper establishes the single-input multiple-output (SIMO) antenna array, and further proposes a missile motion parameter estimation method based on impulse radar. By analyzing the motion geometry relationship of the warhead scattering center after translational compensation, this paper derives the receiving antenna position and the time delay after translational compensation, and thus overcomes the shortcomings of conventional translational compensation methods. By analyzing the motion characteristics of the missile, this paper estimates the missile’s rotation angle and the rotation matrix by establishing a new coordinate system. Simulation results validate the performance of the proposed algorithm. PMID:26978372

  13. Three-Dimensional ISAR Imaging Method for High-Speed Targets in Short-Range Using Impulse Radar Based on SIMO Array.

    PubMed

    Zhou, Xinpeng; Wei, Guohua; Wu, Siliang; Wang, Dawei

    2016-03-11

    This paper proposes a three-dimensional inverse synthetic aperture radar (ISAR) imaging method for high-speed targets in short-range using an impulse radar. According to the requirements for high-speed target measurement in short-range, this paper establishes the single-input multiple-output (SIMO) antenna array, and further proposes a missile motion parameter estimation method based on impulse radar. By analyzing the motion geometry relationship of the warhead scattering center after translational compensation, this paper derives the receiving antenna position and the time delay after translational compensation, and thus overcomes the shortcomings of conventional translational compensation methods. By analyzing the motion characteristics of the missile, this paper estimates the missile's rotation angle and the rotation matrix by establishing a new coordinate system. Simulation results validate the performance of the proposed algorithm.

  14. Doppler laser radar for range and speed measurement of road targets

    NASA Astrophysics Data System (ADS)

    Lin, Yanfang; Mao, Xuesong; Fang, Jianchao; Zhang, Tao

    2016-11-01

    A pulsed coherent vehicle laser radar system basing on the measurement of light flight time and Doppler frequency shift is demonstrated for the first time, which features a simple design that uses one photodiode (PD) as its optical detector. Pseudo random noise (PN) code is used for modulating the amplitude of transmitting light. Correlation function of the received echoes and the local modulating codes is calculated for measuring the light flight time. Due to PN code modulation, beat signal output from PD is piecewise continuous, which causes equidistant sampling of Doppler sine wave not feasible. In order that Doppler frequency be correctly measured by using fast Fourier transform (FFT), a simple signal amplitude modification method is derived from the definition of Fourier transform.

  15. Inverse synthetic aperture radar imaging of targets with complex motion based on the local polynomial ambiguity function

    NASA Astrophysics Data System (ADS)

    Lv, Qian; Su, Tao; Zheng, Jibin

    2016-01-01

    In inverse synthetic aperture radar (ISAR) imaging of targets with complex motion, the azimuth echoes have to be modeled as multicomponent cubic phase signals (CPSs) after motion compensation. For the CPS model, the chirp rate and the quadratic chirp rate deteriorate the ISAR image quality due to the Doppler frequency shift; thus, an effective parameter estimation algorithm is required. This paper focuses on a parameter estimation algorithm for multicomponent CPSs based on the local polynomial ambiguity function (LPAF), which is simple and can be easily implemented via the complex multiplication and fast Fourier transform. Compared with the existing parameter estimation algorithm for CPS, the proposed algorithm can achieve a better compromise between performance and computational complexity. Then, the high-quality ISAR image can be obtained by the proposed LPAF-based ISAR imaging algorithm. The results of the simulated data demonstrate the effectiveness of the proposed algorithm.

  16. Underwater target classification using the wing BOSS and multi-channel decision fusion

    NASA Astrophysics Data System (ADS)

    Wachowski, Neil; Azimi-Sadjadi, Mahmood R.; Cartmill, Jered

    2007-04-01

    In this paper, two different multi-aspect underwater target classification systems are evaluated based on their ability to correctly detect and classify mine-like objects. These methods are tested on a recently collected database that consists of sonar returns from various buried mine-like and non-mine-like objects in different operating and environmental conditions. In one approach, coherent features are extracted from the data using canonical correlation analysis (CCA) between two sonar pings. Classification is performed using a collaborative multi-aspect classifier (CMAC), which utilizes a group of collaborative decision-making agents capable of producing a high-confidence final decision based on these features. The second approach uses features generated by a multi-channel coherence analysis (MCA), which is an extension of CCA utilizing multiple sonar pings. The MCA features are then applied to a simple classifier. Results are presented in terms of correct classification rate and general detection and classification performance of each system in relation to the various operating and environmental conditions.

  17. Unsupervised polarimetric synthetic aperture radar classification of large-scale landslides caused by Wenchuan earthquake in hue-saturation-intensity color space

    NASA Astrophysics Data System (ADS)

    Li, Ning; Wang, Robert; Deng, Yunkai; Liu, Yabo; Li, Bochen; Wang, Chunle; Balz, Timo

    2014-01-01

    A simple and effective approach for unsupervised classification of large-scale landslides caused by the Wenchuan earthquake is developed. The data sets used were obtained by a high-resolution fully polarimetric airborne synthetic aperture radar system working at X-band. In the proposed approach, Pauli decomposition false-color RGB imagery is first transformed to the hue-saturation-intensity (HSI) color space. Then, a good combination of k-means clustering and HSI imagery in different channels is used stage-by-stage for automatic landslides extraction. Two typical case studies are presented to evaluate the feasibility of the proposed scheme. Our approach is an important contribution to the rapid assessment of landslide hazards.

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

    NASA Astrophysics Data System (ADS)

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

    2013-06-01

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

  19. Sensor Reliability Evaluation Scheme for Target Classification Using Belief Function Theory

    PubMed Central

    Zhu, Jing; Luo, Yupin; Zhou, Jianjun

    2013-01-01

    In the target classification based on belief function theory, sensor reliability evaluation has two basic issues: reasonable dissimilarity measure among evidences, and adaptive combination of static and dynamic discounting. One solution to the two issues has been proposed here. Firstly, an improved dissimilarity measure based on dualistic exponential function has been designed. We assess the static reliability from a training set by the local decision of each sensor and the dissimilarity measure among evidences. The dynamic reliability factors are obtained from each test target using the dissimilarity measure between the output information of each sensor and the consensus. Secondly, an adaptive combination method of static and dynamic discounting has been introduced. We adopt Parzen-window to estimate the matching degree of current performance and static performance for the sensor. Through fuzzy theory, the fusion system can realize self-learning and self-adapting with the sensor performance changing. Experiments conducted on real databases demonstrate that our proposed scheme performs better in target classification under different target conditions compared with other methods. PMID:24351632

  20. A computational theory for the classification of natural biosonar targets based on a spike code.

    PubMed

    Müller, Rolf

    2003-08-01

    A computational theory for the classification of natural biosonar targets is developed based on the properties of an example stimulus ensemble. An extensive set of echoes (84 800) from four different foliages was transcribed into a spike code using a parsimonious model (linear filtering, half-wave rectification, thresholding). The spike code is assumed to consist of time differences (interspike intervals) between threshold crossings. Among the elementary interspike intervals flanked by exceedances of adjacent thresholds, a few intervals triggered by disjoint half-cycles of the carrier oscillation stand out in terms of resolvability, visibility across resolution scales and a simple stochastic structure (uncorrelatedness). They are therefore argued to be a stochastic analogue to edges in vision. A three-dimensional feature vector representing these interspike intervals sustained a reliable target classification performance (0.06% classification error) in a sequential probability ratio test, which models sequential processing of echo trains by biological sonar systems. The dimensions of the representation are the first moments of duration and amplitude location of these interspike intervals as well as their number. All three quantities are readily reconciled with known principles of neural signal representation, since they correspond to the centre of gravity of excitation on a neural map and the total amount of excitation.

  1. From molecular classification to targeted therapeutics: the changing face of systemic therapy in metastatic gastroesophageal cancer.

    PubMed

    Murphy, Adrian; Kelly, Ronan J

    2015-01-01

    Histological classification of adenocarcinoma or squamous cell carcinoma for esophageal cancer or using the Lauren classification for intestinal and diffuse type gastric cancer has limited clinical utility in the management of advanced disease. Germline mutations in E-cadherin (CDH1) or mismatch repair genes (Lynch syndrome) were identified many years ago but given their rarity, the identification of these molecular alterations does not substantially impact treatment in the advanced setting. Recent molecular profiling studies of upper GI tumors have added to our knowledge of the underlying biology but have not led to an alternative classification system which can guide clinician's therapeutic decisions. Recently the Cancer Genome Atlas Research Network has proposed four subtypes of gastric cancer dividing tumors into those positive for Epstein-Barr virus, microsatellite unstable tumors, genomically stable tumors, and tumors with chromosomal instability. Unfortunately to date, many phase III clinical trials involving molecularly targeted agents have failed to meet their survival endpoints due to their use in unselected populations. Future clinical trials should utilize molecular profiling of individual tumors in order to determine the optimal use of targeted therapies in preselected patients.

  2. Underwater target classification in changing environments using adaptive feature mapping schemes

    NASA Astrophysics Data System (ADS)

    Yao, De; Azimi-Sadjadi, Mahmood R.; Li, Donghui; Dobeck, Gerald J.

    2000-08-01

    A new adaptive feature mapping scheme is presented in this paper to cope with environmental and target signature changes in underwater target classification. A wavelet packet-based feature extraction scheme is used in conjunction with the linear prediction coding (LPC) scheme as the front-end processor. The core of the adaptive classification system is the adaptive feature mapping sub- system that minimizes the classification error of the classifier. The extracted feature vector is mapped by the resultant feature mapping matrix in such a way that the mapped version remains invariant to the environmental and sensory changes. The feedback to the adaptation mechanism is provided by a K-nearest neighbor (K-NN) classifier. In order to alleviate problems caused by poorly scaled features, a revised K-NN based on the scaled Euclidean distance was adopted. Two error criteria were used in the adaptive system, one is the least squares (LS) error criterion and the other is 2D sigmoid cost function. Those two criteria were combined together to offer a better performance. The test results on 40KHz sigmoid cost function. Those two criteria were combined together to offer a better performance. The test result on 40KHz linear FM acoustic backscattered data collected for six different objects are presented. The effectiveness of the adaptive system vs. non- adaptive system is demonstrated when the signal-to- reverberation ratio in the environment is varying.

  3. Radar Imaging with a Network of Digital Noise Radar Systems

    DTIC Science & Technology

    2009-03-01

    III. Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 3.1 Radar Range Equation and Radar Cross Section . . . . . 29 3.2 UWB...noise radar system. This particular ap- plication tracked a corner reflector that moved from a range of 40 ft to 185 ft from the radar while using an...target scenario and the resulting SAR image. In this test, a radar was placed outside a room with a trihedral reflector placed on the other side of the

  4. Classification and modeling of human activities using empirical mode decomposition with S-band and millimeter-wave micro-Doppler radars

    NASA Astrophysics Data System (ADS)

    Fairchild, Dustin P.; Narayanan, Ram M.

    2012-06-01

    The ability to identify human movements can be an important tool in many different applications such as surveillance, military combat situations, search and rescue operations, and patient monitoring in hospitals. This information can provide soldiers, security personnel, and search and rescue workers with critical knowledge that can be used to potentially save lives and/or avoid a dangerous situation. Most research involving human activity recognition is focused on using the Short-Time Fourier Transform (STFT) as a method of analyzing the micro-Doppler signatures. Because of the time-frequency resolution limitations of the STFT and because Fourier transform-based methods are not well-suited for use with non-stationary and nonlinear signals, we have chosen a different approach. Empirical Mode Decomposition (EMD) has been shown to be a valuable time-frequency method for processing non-stationary and nonlinear data such as micro-Doppler signatures and EMD readily provides a feature vector that can be utilized for classification. For classification, the method of a Support Vector Machine (SVMs) was chosen. SVMs have been widely used as a method of pattern recognition due to their ability to generalize well and also because of their moderately simple implementation. In this paper, we discuss the ability of these methods to accurately identify human movements based on their micro-Doppler signatures obtained from S-band and millimeter-wave radar systems. Comparisons will also be made based on experimental results from each of these radar systems. Furthermore, we will present simulations of micro-Doppler movements for stationary subjects that will enable us to compare our experimental Doppler data to what we would expect from an "ideal" movement.

  5. Arecibo and Goldstone Radar Observations of Binary Near-Earth Asteroid and Marco Polo-R Mission Target (175706) 1996 FG3

    NASA Astrophysics Data System (ADS)

    Benner, L. A. M.; Brozovic, M.; Giorgini, J. D.; Lawrence, K. J.; Taylor, P. A.; Nolan, M. C.; Howell, E. S.; Busch, M. W.; Margot, J. L.; Naidu, S. P.; Magri, C.; Shepard, M. K.

    2012-05-01

    We report Arecibo (2380 MHz), 13-cm) and Goldstone (8560 MHz, 3.5-cm) delay-Doppler radar observations of binary near-Earth asteroid and Marco Polo-R mission target (175706) 1996 FG3 that were obtained on nine dates November-December, 2011.

  6. Target Super-Resolution Compensation for Coherent Airborne Radar Utilizing Spread Spectrum Waveforms.

    DTIC Science & Technology

    1983-12-01

    47 Sampled Signal Theory..............................54 IV. Computer Simulation Development........................58 Approach...Solving Approach In order to determine the feasibility of the narrowband target filter, a computer simulation will be implemented. Signal parameters are...function has a Gaussian frequency spectrum. Various computer runs will be made, testing the waveforms developed in Chapter II and the coherent target

  7. Fusion of forward-looking infrared camera and down-looking ground penetrating radar for buried target detection

    NASA Astrophysics Data System (ADS)

    Yuksel, Seniha E.; Akar, Gozde Bozdagi; Ozturk, Serhat

    2015-05-01

    In this paper, we propose a system to detect buried disk-shaped landmines from ground penetrating radar (GPR) and forward-looking long wave infrared (FL-LWIR) data. The data is collected from a test area of 500m2, which was prepared at the IPA Defence, Ankara, Turkey. This test area was divided into four lanes, each of size 25m length by 4m width and 1m depth. Each lane was first carefully cleaned of stones and clutter and then filled with different soil types, namely fine-medium sand, course sand, sandy silt loam and loam mix. In all lanes, various clutter objects and landmines were buried at different depths and at 1meter intervals. In the proposed approach, IR data is used as a pre-screener. Then possible target regions are further analyzed using the GPR data. IR data processing is done in three steps such as preprocessing, target detection, and postprocessing. In the pre-processing stage, bilateral noise reduction filtering is performed. The target detection stage finds circular targets by a radial transformation algorithm. The proposed approach is compared with the RX algorithm used widely for anomaly detection. The suspicious regions are further analyzed using Histogram of Oriented Gradient (HOG) features that are extracted from GPR images and classified by SVM. The same approach can also be applied in a parallel way where the results are combined using decision level fusion. The results of the proposed approach are given on different scenarios including different weather temperature and depth of buried targets.

  8. Optimal Target Region for Subject Classification on the Basis of Amyloid PET Images.

    PubMed

    Carbonell, Felix; Zijdenbos, Alex P; Charil, Arnaud; Grand'Maison, Marilyn; Bedell, Barry J

    2015-09-01

    Classification of subjects on the basis of amyloid PET scans is increasingly being used in research studies and clinical practice. Although qualitative, visual assessment is currently the gold standard approach, automated classification techniques are inherently more reproducible and efficient. The objective of this work was to develop a statistical approach for the automated classification of subjects with different levels of cognitive impairment into a group with low amyloid levels (AβL) and a group with high amyloid levels (AβH) through the use of amyloid PET data from the Alzheimer Disease Neuroimaging Initiative study. In our framework, an iterative, voxelwise, regularized discriminant analysis is combined with a receiver operating characteristic approach that optimizes the selection of a region of interest (ROI) and a cutoff value for the automated classification of subjects into the AβL and AβH groups. The robustness, spatial stability, and generalization of the resulting target ROIs were evaluated by use of the standardized uptake value ratio for (18)F-florbetapir PET images from subjects who served as healthy controls, subjects who had mild cognitive impairment, and subjects who had Alzheimer disease and were participating in the Alzheimer Disease Neuroimaging Initiative study. We determined that several iterations of the discriminant analysis improved the classification of subjects into the AβL and AβH groups. We found that an ROI consisting of the posterior cingulate cortex/precuneus and the medial frontal cortex yielded optimal group separation and showed good stability across different reference regions and cognitive cohorts. A key step in this process was the automated determination of the cutoff value for group separation, which was dependent on the reference region used for the standardized uptake value ratio calculation and which was shown to have a relatively narrow range across subject groups. We developed a data-driven approach for the

  9. Micro-Doppler analysis of multiple frequency continuous wave radar signatures

    NASA Astrophysics Data System (ADS)

    Anderson, Michael G.; Rogers, Robert L.

    2007-04-01

    Micro-Doppler refers to Doppler scattering returns produced by non rigid-body motion. Micro-Doppler gives rise to many detailed radar image features in addition to those associated with bulk target motion. Targets of different classes (for example, humans, animals, and vehicles) produce micro-Doppler images that are often distinguishable even by nonexpert observers. Micro-Doppler features have great potential for use in automatic target classification algorithms. Although the potential benefit of using micro-Doppler in classification algorithms is high, relatively little experimental (non-synthetic) micro-Doppler data exists. Much of the existing experimental data comes from highly cooperative targets (human or vehicle targets directly approaching the radar). This research involved field data collection and analysis of micro-Doppler radar signatures from non-cooperative targets. The data was collected using a low cost Xband multiple frequency continuous wave (MFCW) radar with three transmit frequencies. The collected MFCW radar signatures contain data from humans, vehicles, and animals. The presented data includes micro-Doppler signatures previously unavailable in the literature such as crawling humans and various animal species. The animal micro-Doppler signatures include deer, dog, and goat datasets. This research focuses on the analysis of micro-Doppler from noncooperative targets approaching the radar at various angles, maneuvers, and postures.

  10. Super-resolution techniques for velocity estimation using UWB random noise radar signals

    NASA Astrophysics Data System (ADS)

    Dawood, Muhammad; Quraishi, Nafish; Alejos, Ana V.

    2011-06-01

    The Doppler spread pertaining to the ultrawideband (UWB) radar signals from moving target is directly proportional to the bandwidth of the transmitted signal and the target velocity. Using typical FFT-based methods, the estimation of true velocities pertaining to two targets moving with relatively close velocities within a radar range bin is problematic. In this paper, we extend the Multiple Signal Classification (MUSIC) algorithm to resolve targets moving velocities closer to each other within a given range bin for UWB random noise radar waveforms. Simulated and experimental results are compared for various target velocities using both narrowband (200MHz) and wideband (1GHz) noise radar signals, clearly establishing the unbiased and unambiguous velocity estimations using the MUSIC algorithm.

  11. An accelerated framework for the classification of biological targets from solid-state micropore data.

    PubMed

    Hanif, Madiha; Hafeez, Abdul; Suleman, Yusuf; Mustafa Rafique, M; Butt, Ali R; Iqbal, Samir M

    2016-10-01

    Micro- and nanoscale systems have provided means to detect biological targets, such as DNA, proteins, and human cells, at ultrahigh sensitivity. However, these devices suffer from noise in the raw data, which continues to be significant as newer and devices that are more sensitive produce an increasing amount of data that needs to be analyzed. An important dimension that is often discounted in these systems is the ability to quickly process the measured data for an instant feedback. Realizing and developing algorithms for the accurate detection and classification of biological targets in realtime is vital. Toward this end, we describe a supervised machine-learning approach that records single cell events (pulses), computes useful pulse features, and classifies the future patterns into their respective types, such as cancerous/non-cancerous cells based on the training data. The approach detects cells with an accuracy of 70% from the raw data followed by an accurate classification when larger training sets are employed. The parallel implementation of the algorithm on graphics processing unit (GPU) demonstrates a speedup of three to four folds as compared to a serial implementation on an Intel Core i7 processor. This incredibly efficient GPU system is an effort to streamline the analysis of pulse data in an academic setting. This paper presents for the first time ever, a non-commercial technique using a GPU system for realtime analysis, paired with biological cluster targeting analysis. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  12. Refocus of constant velocity moving targets in synthetic aperture radar imagery

    SciTech Connect

    Jakowatz, C.V. Jr.; Wahl, D.E.; Eichel, P.H.

    1998-04-01

    The detection and refocus of moving targets in SAR imagery is of interest in a number of applications. In this paper the authors address the problem of refocusing a blurred signature that has by some means been identified as a moving target. They assume that the target vehicle velocity is constant, i.e., the motion is in a straight line with constant speed. The refocus is accomplished by application of a two-dimensional phase function to the phase history data obtained via Fourier transformation of an image chip that contains the blurred moving target data. By considering separately the phase effects of the range and cross-range components of the target velocity vector, they show how the appropriate phase correction term can be derived as a two-parameter function. They then show a procedure for estimating the two parameters, so that the blurred signature can be automatically refocused. The algorithm utilizes optimization of an image domain contrast metric. They present results of refocusing moving targets in real SAR imagery by this method.

  13. Radar illusion via metamaterials

    NASA Astrophysics Data System (ADS)

    Jiang, Wei Xiang; Cui, Tie Jun

    2011-02-01

    An optical illusion is an image of a real target perceived by the eye that is deceptive or misleading due to a physiological illusion or a specific visual trick. The recently developed metamaterials provide efficient approaches to generate a perfect optical illusion. However, all existing research on metamaterial illusions has been limited to theory and numerical simulations. Here, we propose the concept of a radar illusion, which can make the electromagnetic (EM) image of a target gathered by radar look like a different target, and we realize a radar illusion device experimentally to change the radar image of a metallic target into a dielectric target with predesigned size and material parameters. It is well known that the radar signatures of metallic and dielectric objects are significantly different. However, when a metallic target is enclosed by the proposed illusion device, its EM scattering characteristics will be identical to that of a predesigned dielectric object under the illumination of radar waves. Such an illusion device will confuse the radar, and hence the real EM properties of the metallic target cannot be perceived. We designed and fabricated the radar illusion device using artificial metamaterials in the microwave frequency, and good illusion performances are observed in the experimental results.

  14. The application of the multifractal cross-correlation analysis methods in radar target detection within sea clutter

    NASA Astrophysics Data System (ADS)

    Xi, Caiping; Zhang, Shuning; Xiong, Gang; Zhao, Huichang; Yang, Yonghong

    2017-02-01

    Many complex systems generate multifractal time series which are long-range cross-correlated. This paper introduces three multifractal cross-correlation analysis methods, such as multifractal cross-correlation analysis based on the partition function approach (MFXPF), multifractal detrended cross-correlation analysis (MFDCCA) methods based on detrended fluctuation analysis (MFXDFA) and detrended moving average analysis (MFXDMA), which only consider one moment order. We do comparative analysis of the artificial time series (binomial multiplicative cascades and Cantor sets with different probabilities) by these methods. Then we do a feasibility test of the fixed threshold target detection within sea clutter by applying the multifractal cross-correlation analysis methods to the IPIX radar sea clutter data. The results show that it is feasible to use the method of the fixed threshold based on the multifractal feature parameter Δf(α) by the MFXPF and MFXDFA-1 methods. At last, we give the main conclusions and provide a valuable reference on how to choose the multifractal algorithms, the detection parameters and the target detection methods within sea clutter in practice.

  15. New method of cross-range scaling of low-resolution radar

    NASA Astrophysics Data System (ADS)

    Jiang, Zhenglin; Bao, Zheng

    2000-08-01

    Due to the ordinary low resolution radar can not distinguish the radar target in both range and azimuth. If we apply the technology of inverse synthetic aperture radar (ISAR) to resolve the difference among Doppler frequency of the scatters on the target, we can obtain a fine resolution cross-range image. The cross-range scale depends on both radar wavelength and rotating angle of target relative to radar-line-of-sight (RLOS) during the coherent accumulation. The former is known while the latter is difficult to determine especially in the case of ISAR. But we must investigate the method of cross- range scaling of low-resolution radar, as it is very important to radar target classification and recognition. In this paper, a new approach is proposed which is based on the principle of interferometric inverse synthetic aperture. We can calculate the phase difference of some scatters between two instant cross-range images by two antenna which are placed on one level, adding the range between the two radar and the range of the target, and then absolute cross ranges of some dominant scatters are obtained. We apply the proposed algorithm to the emulational data of two antennae. The processing results show that the proposed method is correct and effective.

  16. Detection and Classification of Low Probability of Intercept Radar Signals Using Parallel Filter Arrays and Higher Order Statistics

    NASA Astrophysics Data System (ADS)

    Taboada, Fernando L.

    2002-09-01

    Low probability of intercept (LPI) is that property of an emitter that because of its low power, wide bandwidth, frequency variability, or other design attributes, makes it difficult to be detected or identified by means of passive intercept devices such as radar warning, electronic support and electronic intelligence receivers. In order to detect LPI radar waveforms new signal processing techniques are required. This thesis first develops a MATLAB toolbox to generate important types of LPI waveforms based on frequency and phase modulation. The power spectral density and the periodic ambiguity function are examined for each waveforms. These signals are then used to test a novel signal processing technique that detects the waveforms parameters and classifies the intercepted signal in various degrees of noise. The technique is based on the use of parallel filter (sub-band) arrays and higher order statistics (third-order cumulant estimator). Each sub-band signal is treated individually and is followed by the third-order estimator in order to suppress any symmetrical noise that might be present. The significance of this technique is that it separates the LPI waveforms in small frequency bands, providing a detailed time-frequency description of the unknown signal. Finally, the resulting output matrix is processed by a feature extraction routine to detect the waveforms parameters. Identification of the signal is based on the modulation parameters detected.

  17. Obstacle avoidance and concealed target detection using the Army Research Lab ultra-wideband synchronous impulse reconstruction (UWB SIRE) forward imaging radar

    NASA Astrophysics Data System (ADS)

    Nguyen, Lam; Wong, David; Ressler, Marc; Koenig, Francois; Stanton, Brian; Smith, Gregory; Sichina, Jeffrey; Kappra, Karl

    2007-04-01

    The U.S. Army Research Laboratory (ARL), as part of a mission and customer funded exploratory program, has developed a new low-frequency, ultra-wideband (UWB) synthetic aperture radar (SAR) for forward imaging to support the Army's vision of an autonomous navigation system for robotic ground vehicles. These unmanned vehicles, equipped with an array of imaging sensors, will be tasked to help detect man-made obstacles such as concealed targets, enemy minefields, and booby traps, as well as other natural obstacles such as ditches, and bodies of water. The ability of UWB radar technology to help detect concealed objects has been documented in the past and could provide an important obstacle avoidance capability for autonomous navigation systems, which would improve the speed and maneuverability of these vehicles and consequently increase the survivability of the U. S. forces on the battlefield. One of the primary features of the radar is the ability to collect and process data at combat pace in an affordable, compact, and lightweight package. To achieve this, the radar is based on the synchronous impulse reconstruction (SIRE) technique where several relatively slow and inexpensive analog-to-digital (A/D) converters are used to sample the wide bandwidth of the radar signals. We conducted an experiment this winter at Aberdeen Proving Ground (APG) to support the phenomenological studies of the backscatter from positive and negative obstacles for autonomous robotic vehicle navigation, as well as the detection of concealed targets of interest to the Army. In this paper, we briefly describe the UWB SIRE radar and the test setup in the experiment. We will also describe the signal processing and the forward imaging techniques used in the experiment. Finally, we will present imagery of man-made obstacles such as barriers, concertina wires, and mines.

  18. Waveguide invariant active sonar target detection and depth classification in shallow water

    NASA Astrophysics Data System (ADS)

    Goldhahn, Ryan A.

    vital to maintaining low false alarm rates in active sonar. Moreover, because of the non-stationarity of the active sonar return, classification is most typically achieved using a single snapshot of test data. As an aid to classification, the waveguide invariant property is used to derive multiple snapshots by uniformly sub-sampling the short-time Fourier transform (STFT) coefficients of a single ping of wideband active sonar data. The sub-sampled target snapshots are used to define a waveguide-invariant spectral density matrix (WI-SDM) which allows the application of adaptive matched-filtering based approaches for target depth classification. Depth classification is performed by a waveguide-invariant minimum variance filter (WI-MVF) which matches the observed WI-SDM to depth-dependent signal replica vectors generated from a normal mode model. Robustness to environmental mismatch is achieved by adding environmental perturbation constraints (EPC) and averaging the signal replica vectors over the unknown channel parameters. Simulation and real data results from the SCARAB98, CLUTTER07, and CLUTTER09 experiments in the Mediterranean Sea are presented to illustrate the approach.

  19. Automatic Target Cueing and Operator Performance with Enhanced APG-70 Synthetic Aperture Radar Imagery.

    DTIC Science & Technology

    1997-11-01

    MAN truck carrying a high pressure air compressor ( HiPAC ) unit, and a Zil-131 communications van. The Scud-B, which was the primary target for...Laboratory d Perceptual sensitivity FA False Alarm FLIR Forward Looking Infrared H Hit HiPAC High Pressure Air Compressor HRM High Resolution Map

  20. An overview of current and advanced processing techniques for surveillance radar

    NASA Astrophysics Data System (ADS)

    Farina, A.; Galati, G.

    An evaluation is made of current and prospective signal processing techniques for air defense and surveillance radars, giving attention to surveillance performance-enhancement requirements, signal coding, and anticlutter and ECCM techniques for three-dimensional radars. Novel concepts and techniques anticipated for future application encompass low probability of intercept features, anti-ARM, and antistealth capabilities, digital beam forming, adaptivity, high resolution multidimensional processing, and target classification.

  1. A targeted change-detection procedure by combining change vector analysis and post-classification approach

    NASA Astrophysics Data System (ADS)

    Ye, Su; Chen, Dongmei; Yu, Jie

    2016-04-01

    In remote sensing, conventional supervised change-detection methods usually require effective training data for multiple change types. This paper introduces a more flexible and efficient procedure that seeks to identify only the changes that users are interested in, here after referred to as ;targeted change detection;. Based on a one-class classifier ;Support Vector Domain Description (SVDD);, a novel algorithm named ;Three-layer SVDD Fusion (TLSF); is developed specially for targeted change detection. The proposed algorithm combines one-class classification generated from change vector maps, as well as before- and after-change images in order to get a more reliable detecting result. In addition, this paper introduces a detailed workflow for implementing this algorithm. This workflow has been applied to two case studies with different practical monitoring objectives: urban expansion and forest fire assessment. The experiment results of these two case studies show that the overall accuracy of our proposed algorithm is superior (Kappa statistics are 86.3% and 87.8% for Case 1 and 2, respectively), compared to applying SVDD to change vector analysis and post-classification comparison.

  2. Active radar guides missile to its target: receptor-based targeted treatment of hepatocellular carcinoma by nanoparticulate systems.

    PubMed

    Yan, Jing-Jun; Liao, Jia-Zhi; Lin, Ju-Sheng; He, Xing-Xing

    2015-01-01

    Patients with hepatocellular carcinoma (HCC) usually present at advanced stages and do not benefit from surgical resection, so drug therapy should deserve a prominent place in unresectable HCC treatment. But chemotherapy agents, such as doxorubicin, cisplatin, and paclitaxel, frequently encounter important problems such as low specificity and non-selective biodistribution. Recently, the development of nanotechnology led to significant breakthroughs to overcome these problems. Decorating the surfaces of nanoparticulate-based drug carriers with homing devices has demonstrated its potential in concentrating chemotherapy agents specifically to HCC cells. In this paper, we reviewed the current status of active targeting strategies for nanoparticulate systems based on various receptors such as asialoglycoprotein receptor, transferrin receptor, epidermal growth factor receptor, folate receptor, integrin, and CD44, which are abundantly expressed on the surfaces of hepatocytes or liver cancer cells. Furthermore, we pointed out their merits and defects and provided theoretical references for further research.

  3. Characterizations of PAPR-Constrained Radar Waveforms for Optimal Target Detection

    SciTech Connect

    Sen, Satyabrata

    2014-01-01

    We propose to design a peak-to-average power ratio (PAPR) constrained transmit waveform that achieves the optimal performance (following the Neyman Pearson lemma) in detecting a target in the presence of signal-dependent interference. The direct time-domain approach allows straightforward characterizations of the correlation and PAPR properties of the designed signals, which are critically important to analyze the system performance in the presence of multiple targets and to assess the transmitter power-utilization, respectively. Therefore, instead of designing a transmit signal only for the optimal detection performance, we solve a biobjective Pareto-optimization problem, subjecting to the PAPR and total energy constraints, in order to simultaneously optimize the detection and cross-correlation performances. With extensive numerical examples, we demonstrate that PAPR-constrained signals produce nearly optimum detection performance even with a strict PAPR requirement, and also highlight the conflicting behavior of the detection and correlation performances.

  4. Classification.

    PubMed

    Tuxhorn, Ingrid; Kotagal, Prakash

    2008-07-01

    In this article, we review the practical approach and diagnostic relevance of current seizure and epilepsy classification concepts and principles as a basic framework for good management of patients with epileptic seizures and epilepsy. Inaccurate generalizations about terminology, diagnosis, and treatment may be the single most important factor, next to an inadequately obtained history, that determines the misdiagnosis and mismanagement of patients with epilepsy. A stepwise signs and symptoms approach for diagnosis, evaluation, and management along the guidelines of the International League Against Epilepsy and definitions of epileptic seizures and epilepsy syndromes offers a state-of-the-art clinical approach to managing patients with epilepsy.

  5. Forest above ground biomass estimation and forest/non-forest classification for Odisha, India, using L-band Synthetic Aperture Radar (SAR) data

    NASA Astrophysics Data System (ADS)

    Suresh, M.; Kiran Chand, T. R.; Fararoda, R.; Jha, C. S.; Dadhwal, V. K.

    2014-11-01

    Tropical forests contribute to approximately 40 % of the total carbon found in terrestrial biomass. In this context, forest/non-forest classification and estimation of forest above ground biomass over tropical regions are very important and relevant in understanding the contribution of tropical forests in global biogeochemical cycles, especially in terms of carbon pools and fluxes. Information on the spatio-temporal biomass distribution acts as a key input to Reducing Emissions from Deforestation and forest Degradation Plus (REDD+) action plans. This necessitates precise and reliable methods to estimate forest biomass and to reduce uncertainties in existing biomass quantification scenarios. The use of backscatter information from a host of allweather capable Synthetic Aperture Radar (SAR) systems during the recent past has demonstrated the potential of SAR data in forest above ground biomass estimation and forest / nonforest classification. In the present study, Advanced Land Observing Satellite (ALOS) / Phased Array L-band Synthetic Aperture Radar (PALSAR) data along with field inventory data have been used in forest above ground biomass estimation and forest / non-forest classification over Odisha state, India. The ALOSPALSAR 50 m spatial resolution orthorectified and radiometrically corrected HH/HV dual polarization data (digital numbers) for the year 2010 were converted to backscattering coefficient images (Schimada et al., 2009). The tree level measurements collected during field inventory (2009-'10) on Girth at Breast Height (GBH at 1.3 m above ground) and height of all individual trees at plot (plot size 0.1 ha) level were converted to biomass density using species specific allometric equations and wood densities. The field inventory based biomass estimations were empirically integrated with ALOS-PALSAR backscatter coefficients to derive spatial forest above ground biomass estimates for the study area. Further, The Support Vector Machines (SVM) based Radial

  6. Classification

    NASA Technical Reports Server (NTRS)

    Oza, Nikunj C.

    2011-01-01

    A supervised learning task involves constructing a mapping from input data (normally described by several features) to the appropriate outputs. Within supervised learning, one type of task is a classification learning task, in which each output is one or more classes to which the input belongs. In supervised learning, a set of training examples---examples with known output values---is used by a learning algorithm to generate a model. This model is intended to approximate the mapping between the inputs and outputs. This model can be used to generate predicted outputs for inputs that have not been seen before. For example, we may have data consisting of observations of sunspots. In a classification learning task, our goal may be to learn to classify sunspots into one of several types. Each example may correspond to one candidate sunspot with various measurements or just an image. A learning algorithm would use the supplied examples to generate a model that approximates the mapping between each supplied set of measurements and the type of sunspot. This model can then be used to classify previously unseen sunspots based on the candidate's measurements. This chapter discusses methods to perform machine learning, with examples involving astronomy.

  7. Improved variability classification of CoRoT targets with Giraffe spectra

    NASA Astrophysics Data System (ADS)

    Sarro, L. M.; Debosscher, J.; Neiner, C.; Bello-García, A.; González-Marcos, A.; Prendes-Gero, B.; Ordieres, J.; León, G.; Aerts, C.; de Batz, B.

    2013-02-01

    Aims: We present an improved method for automated stellar variability classification, using fundamental parameters derived from high resolution spectra, with the goal to improve the variability classification obtained using information derived from CoRoT light curves only. Although we focus on Giraffe spectra and CoRoT light curves in this work, the methods are much more widely applicable. Methods: In order to improve the variability classification obtained from the photometric time series, only rough estimates of the stellar physical parameters (Teff and log (g)) are needed because most variability types that overlap in the space of time series parameters, are well separated in the space of physical parameters (e.g. γ Dor/SPB or δ Sct/β Cep). In this work, several state-of-the-art machine learning techniques are combined to estimate these fundamental parameters from high resolution Giraffe spectra. Next, these parameters are used in a multi-stage Gaussian-Mixture classifier to perform an improved supervised variability classification of CoRoT light curves. The variability classifier can be used independently of the regression module that estimates the physical parameters, so that non-spectroscopic estimates derived e.g. from photometric colour indices can be used instead. Results: Teff and log (g) are derived from Giraffe spectra, for 6832 CoRoT targets. The use of those parameters in addition to information extracted from the CoRoT light curves, significantly improves the results of our previous automated stellar variability classification. Several new pulsating stars are identified with high confidence levels, including hot pulsators such as SPB and β Cep, and several γ Dor-δ Sct hybrids. From our samples of new γ Dor and δ Sct stars, we find strong indications that the instability domains for both types of pulsators are larger than previously thought. The CoRoT space mission, launched on 27 December 2006, has been developed and is operated by CNES, with

  8. Classification of Soil Moisture on Vegetated Earthen Levees Using X and L Band Synthetic Aperture Radar (SAR)

    NASA Astrophysics Data System (ADS)

    Mahrooghy, M.; Aanstoos, J. V.; Hasan, K.; Nobrega, R. A.; Younan, N. H.

    2011-12-01

    Earthen levees protect large areas of land in the US from flooding. Timely inspection and repairs can reduce the potential for catastrophic failures. Changes in spatial and temporal patterns of soil moisture can reveal signs of instability and help identify zones of weakness. Since analytical and empirical models have shown a relationship between SAR backscatter and soil moisture, we are using SAR to classify soil moisture on levees. Estimation of soil moisture from SAR is challenging when the surface has any significant vegetation. For the levee application, the soil is typically covered with a uniform layer of grass. Our methodology is based on a supervised soil moisture classification using a back propagation neural network with four classes of low, medium, high, and very high soil moisture. Our methodology consists of the following steps: 1) segmentation of the levee area from background and exclusion of tree-covered areas; 2) extracting the backscattering and texture features such as GLCM (Grey-Level Co-occurrence Matrix) and wavelet features; 3) training the back propagation neural network classifier; and 4) testing the area of interest and validation of the results using ground truth data. Two sources of SAR imagery are tested with this method: (1) fully polarimetric L-band data from NASA's UAVSAR; and (2) dual-polarimetric X-band data from the German TerraSAR-X satellite. The study area is a 4 km stretch of levee along the lower Mississippi River in the United States. Field data collected simultaneously with image acquisition are utilized for training and validation. Preliminary results show classification accuracies of about 50% for the UAVSAR image and 30% for the TerraSAR-X image in vegetated areas. The figure below shows a soil moisture classification using UAVSAR on April 28, 2011.

  9. A comparison of information functions and search strategies for sensor planning in target classification.

    PubMed

    Zhang, Guoxian; Ferrari, Silvia; Cai, Chenghui

    2012-02-01

    This paper investigates the comparative performance of several information-driven search strategies and decision rules using a canonical target classification problem. Five sensor models are considered: one obtained from classical estimation theory and four obtained from Bernoulli, Poisson, binomial, and mixture-of-binomial distributions. A systematic approach is presented for deriving information functions that represent the expected utility of future sensor measurements from mutual information, Rènyi divergence, Kullback-Leibler divergence, information potential, quadratic entropy, and the Cauchy-Schwarz distance. The resulting information-driven strategies are compared to direct-search, alert-confirm, task-driven (TS), and log-likelihood-ratio (LLR) search strategies. Extensive numerical simulations show that quadratic entropy typically leads to the most effective search strategy with respect to correct-classification rates. In the presence of prior information, the quadratic-entropy-driven strategy also displays the lowest rate of false alarms. However, when prior information is absent or very noisy, TS and LLR strategies achieve the lowest false-alarm rates for the Bernoulli, mixture-of-binomial, and classical sensor models.

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

    NASA Astrophysics Data System (ADS)

    Tsui, Eddy K.; Thomas, Russell L.

    2004-09-01

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

  11. Dark-spot segmentation for oil spill detection based on multifeature fusion classification in single-pol synthetic aperture radar imagery

    NASA Astrophysics Data System (ADS)

    Lang, Haitao; Zhang, Xingyao; Xi, Yuyang; Zhang, Xi; Li, Wei

    2017-01-01

    In recent years, oil spill surveillance with space-borne synthetic aperture radar (SAR) has received unprecedented attention and has been gradually developed into a common technique for maritime environment protection. A typical SAR-based oil spill detection process consists of three steps: (1) dark-spot segmentation, (2) feature extraction, and (3) oil spill and look-alike discrimination. As a preliminary task in the oil spill detection process chain, dark-spot segmentation is a critical and fundamental step prior to feature extraction and classification, since its output has a direct impact on the two subsequent stages. The balance between the detection probability and false alarm probability has a vital impact on the performance of the entire detection system. Unfortunately, this problem has not drawn as much attention as the other two stages. A specific effort has been placed on dark-spot segmentation in single-pol SAR imagery. A combination of fine designed features, including gray features, geometric features, and textural features, is proposed to characterize the oil spill and seawater for improving the performance of dark-spot segmentation. In the proposed process chain, a histogram stretching transform is incorporated before the gray feature extraction to enhance the contrast between possible oil spills and water. A simple but effective multiple-level thresholding algorithm is developed to conduct a binary classification before the geometric feature extraction to obtain more accurate area features. A local binary pattern code is computed and assigned as the textural feature for a pixel to characterize the physical difference between oil spills and water. The experimental result confirms that the proposed fine designed feature combination outperforms existing approaches in both aspects of overall segmentation accuracy and the capability to balance detection probability and false alarm probability. It is a promising alternative that can be incorporated into

  12. RCS Predictions From a Method of Moments and a Finite-Element Code for Several Targets

    DTIC Science & Technology

    2010-07-01

    01803 14. ABSTRACT This report presents results of radar cross section (RCS) calculations for several interesting targets using a method-of-moments...TERMS radar cross section, method of moments, finite element, modeling 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18... radar cross section (RCS) simulation that require an exact code for solution. In this report, we compare RCS calculations with two very different

  13. Under the radar--how the tobacco industry targets youth in Australia.

    PubMed

    Harper, Todd A; Martin, Jane E

    2002-12-01

    Tobacco consumption has been declining in Australia since the 1970s when controls on advertising were first introduced. Since this time, legislation has been progressively introduced, severely restricting tobacco advertising and promotion in the mainstream media. This has resulted in limited opportunities for the tobacco industry to reach new smokers, particularly young people. This paper outlines marketing strategies used by tobacco companies and their advertising agencies to reach this group; it examines how the industry exploits loopholes in current legislation and identifies new promotional opportunities. Increasingly, the industry has targeted young people through film, dance parties, nightclubs, fashion shows, e-mail and the internet. The industry is also capitalizing on promoting pack design elements and enhancing them through event promotion. Unless restrictions on tobacco marketing and promotion are comprehensive they undermine the effectiveness of those already in place and will continue to be exploited by the tobacco industry. The recent announcement by the Federal government to reassess the current legislative restrictions in light of these new marketing trends is welcome. The removal of all incentives to promote tobacco products, including imagery associated with the pack and its design, is essential in removing one of the key factors influencing the uptake and prevalence of smoking in youth.

  14. Computationally efficient target classification in multispectral image data with Deep Neural Networks

    NASA Astrophysics Data System (ADS)

    Cavigelli, Lukas; Bernath, Dominic; Magno, Michele; Benini, Luca

    2016-10-01

    Detecting and classifying targets in video streams from surveillance cameras is a cumbersome, error-prone and expensive task. Often, the incurred costs are prohibitive for real-time monitoring. This leads to data being stored locally or transmitted to a central storage site for post-incident examination. The required communication links and archiving of the video data are still expensive and this setup excludes preemptive actions to respond to imminent threats. An effective way to overcome these limitations is to build a smart camera that analyzes the data on-site, close to the sensor, and transmits alerts when relevant video sequences are detected. Deep neural networks (DNNs) have come to outperform humans in visual classifications tasks and are also performing exceptionally well on other computer vision tasks. The concept of DNNs and Convolutional Networks (ConvNets) can easily be extended to make use of higher-dimensional input data such as multispectral data. We explore this opportunity in terms of achievable accuracy and required computational effort. To analyze the precision of DNNs for scene labeling in an urban surveillance scenario we have created a dataset with 8 classes obtained in a field experiment. We combine an RGB camera with a 25-channel VIS-NIR snapshot sensor to assess the potential of multispectral image data for target classification. We evaluate several new DNNs, showing that the spectral information fused together with the RGB frames can be used to improve the accuracy of the system or to achieve similar accuracy with a 3x smaller computation effort. We achieve a very high per-pixel accuracy of 99.1%. Even for scarcely occurring, but particularly interesting classes, such as cars, 75% of the pixels are labeled correctly with errors occurring only around the border of the objects. This high accuracy was obtained with a training set of only 30 labeled images, paving the way for fast adaptation to various application scenarios.

  15. Side looking radar calibration study

    NASA Technical Reports Server (NTRS)

    Edwards, W. D.

    1975-01-01

    Calibration of an airborne sidelooking radar is accomplished by the use of a model that relates the radar parameters to the physical mapping situation. Topics discussed include: characteristics of the transmitters; the antennas; target absorption and reradiation; the receiver and map making or radar data processing; and the calibration process.

  16. A simulation study of scene confusion factors in sensing soil moisture from orbital radar

    NASA Technical Reports Server (NTRS)

    Ulaby, F. T. (Principal Investigator); Dobson, M. C.; Moezzi, S.; Roth, F. T.

    1983-01-01

    Simulated C-band radar imagery for a 124-km by 108-km test site in eastern Kansas is used to classify soil moisture. Simulated radar resolutions are 100 m by 100 m, 1 km by 1km, and 3 km by 3 km. Distributions of actual near-surface soil moisture are established daily for a 23-day accounting period using a water budget model. Within the 23-day period, three orbital radar overpasses are simulated roughly corresponding to generally moist, wet, and dry soil moisture conditions. The radar simulations are performed by a target/sensor interaction model dependent upon a terrain model, land-use classification, and near-surface soil moisture distribution. The accuracy of soil-moisture classification is evaluated for each single-date radar observation and also for multi-date detection of relative soil moisture change. In general, the results for single-date moisture detection show that 70% to 90% of cropland can be correctly classified to within +/- 20% of the true percent of field capacity. For a given radar resolution, the expected classification accuracy is shown to be dependent upon both the general soil moisture condition and also the geographical distribution of land-use and topographic relief. An analysis of cropland, urban, pasture/rangeland, and woodland subregions within the test site indicates that multi-temporal detection of relative soil moisture change is least sensitive to classification error resulting from scene complexity and topographic effects.

  17. Convolutional neural network-based automatic classification of midsagittal tongue gestural targets using B-mode ultrasound images.

    PubMed

    Xu, Kele; Roussel, Pierre; Csapó, Tamás Gábor; Denby, Bruce

    2017-06-01

    Tongue gestural target classification is of great interest to researchers in the speech production field. Recently, deep convolutional neural networks (CNN) have shown superiority to standard feature extraction techniques in a variety of domains. In this letter, both CNN-based speaker-dependent and speaker-independent tongue gestural target classification experiments are conducted to classify tongue gestures during natural speech production. The CNN-based method achieves state-of-the-art performance, even though no pre-training of the CNN (with the exception of a data augmentation preprocessing) was carried out.

  18. Spatially-Varying Calibration of Along-Track Monopulse Synthetic Aperture Radar Imagery for Ground Moving Target Indication and Tracking

    DTIC Science & Technology

    2010-05-01

    discussions on the merit of this algorithm. REFERENCES [1] U. Majumder, M . Minardi, E. Blasch, L. Gorham, K. Naidu , T. Lewis and R. Williams, “Radar...Proc. IEEE Radar Conference, Pasadena, May 2009. [5] S. Scarborough, C . Casteel, Jr., L. Gorham, M . Minardi, U. Majumder, M . Judge, E. Zelnio, M ...Same as Report (SAR) 18. NUMBER OF PAGES 6 19a. NAME OF RESPONSIBLE PERSON a. REPORT unclassified b. ABSTRACT unclassified c . THIS PAGE

  19. Three-dimensional interferometric inverse synthetic aperture radar imaging of maneuvering target based on the joint cross modified Wigner-Ville distribution

    NASA Astrophysics Data System (ADS)

    Lv, Qian; Su, Tao; Zheng, Jibin; Zhang, Jiancheng

    2016-01-01

    Inverse synthetic aperture radar (ISAR) can achieve high-resolution two-dimensional images of maneuvering targets. However, due to the indeterminate relative motion between radar and target, ISAR imaging does not provide the three-dimensional (3-D) position information of a target and suffers from great difficulty in target recognition. To tackle this issue, a 3-D interferometric ISAR (InISAR) imaging algorithm based on the joint cross modified Wigner-Ville distribution (MWVD) is presented to form 3-D images of maneuvering targets. First, we form two orthogonal interferometric baselines with three receiving antennas to establish an InISAR imaging system. Second, after the uniform range alignment and phase adjustment, the joint cross MWVD is used for all range cell of each antenna pair to generate the separation of the scatterer as well as preserve the phase that contains position information of the scatterer. At last, the 3-D images of the target can be directly reconstructed from the distribution. Simulation results demonstrate the validity of the proposal.

  20. 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.

  1. 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.

  2. Using Support Vector Machine Ensembles for Target Audience Classification on Twitter

    PubMed Central

    Lo, Siaw Ling; Chiong, Raymond; Cornforth, David

    2015-01-01

    The vast amount and diversity of the content shared on social media can pose a challenge for any business wanting to use it to identify potential customers. In this paper, our aim is to investigate the use of both unsupervised and supervised learning methods for target audience classification on Twitter with minimal annotation efforts. Topic domains were automatically discovered from contents shared by followers of an account owner using Twitter Latent Dirichlet Allocation (LDA). A Support Vector Machine (SVM) ensemble was then trained using contents from different account owners of the various topic domains identified by Twitter LDA. Experimental results show that the methods presented are able to successfully identify a target audience with high accuracy. In addition, we show that using a statistical inference approach such as bootstrapping in over-sampling, instead of using random sampling, to construct training datasets can achieve a better classifier in an SVM ensemble. We conclude that such an ensemble system can take advantage of data diversity, which enables real-world applications for differentiating prospective customers from the general audience, leading to business advantage in the crowded social media space. PMID:25874768

  3. ARTMAP-FTR: a neural network for fusion target recognition with application to sonar classification

    NASA Astrophysics Data System (ADS)

    Carpenter, Gail A.; Streilein, William W.

    1998-09-01

    ART (Adaptive Resonance Theory) neural networks for fast, stable learning and prediction have been applied in a variety of areas. Applications include automatic mapping from satellite remote sensing data, machine tool monitoring, medical prediction, digital circuit design, chemical analysis, and robot vision. Supervised ART architectures, called ARTMAP systems, feature internal control mechanisms that create stable recognition categories of optimal size by maximizing code compression while minimizing predictive error in an on- line setting. Special-purpose requirements of various application domains have led to a number of ARTMAP variants, including fuzzy ARTMAP, ART-EMAP, ARTMAP-IC, Gaussian ARTMAP, and distributed ARTMAP. A new ARTMAP variant, called ARTMAP- FTR (fusion target recognition), has been developed for the problem of multi-ping sonar target classification. The development data set, which lists sonar returns from underwater objects, was provided by the Naval Surface Warfare Center (NSWC) Coastal Systems Station (CSS), Dahlgren Division. The ARTMAP-FTR network has proven to be an effective tool for classifying objects from sonar returns. The system also provides a procedure for solving more general sensor fusion problems.

  4. Using support vector machine ensembles for target audience classification on Twitter.

    PubMed

    Lo, Siaw Ling; Chiong, Raymond; Cornforth, David

    2015-01-01

    The vast amount and diversity of the content shared on social media can pose a challenge for any business wanting to use it to identify potential customers. In this paper, our aim is to investigate the use of both unsupervised and supervised learning methods for target audience classification on Twitter with minimal annotation efforts. Topic domains were automatically discovered from contents shared by followers of an account owner using Twitter Latent Dirichlet Allocation (LDA). A Support Vector Machine (SVM) ensemble was then trained using contents from different account owners of the various topic domains identified by Twitter LDA. Experimental results show that the methods presented are able to successfully identify a target audience with high accuracy. In addition, we show that using a statistical inference approach such as bootstrapping in over-sampling, instead of using random sampling, to construct training datasets can achieve a better classifier in an SVM ensemble. We conclude that such an ensemble system can take advantage of data diversity, which enables real-world applications for differentiating prospective customers from the general audience, leading to business advantage in the crowded social media space.

  5. Radar Cross Section Measurements

    DTIC Science & Technology

    1986-09-30

    Radar 54 17. Measured Range Sidelobe Performance of Chirp Radar 56 18. Range and Cross Range Image of Target Dror.’ŕ Vehicle 57 19. Incoherent rms...the measured range resolution, 4.9 in, closely agrees with the theoretical performance for this weighting. The measured range sidelobe performance...Interval 4.89in. 2% kHz 300 kHz 310 kHz (b) Expanded Scale + 5 ft from Target Figure 17. Measured Range Sidelobe Performance of

  6. Doppler Feature Based Classification of Wind Profiler Data

    NASA Astrophysics Data System (ADS)

    Sinha, Swati; Chandrasekhar Sarma, T. V.; Lourde. R, Mary

    2017-01-01

    Wind Profilers (WP) are coherent pulsed Doppler radars in UHF and VHF bands. They are used for vertical profiling of wind velocity and direction. This information is very useful for weather modeling, study of climatic patterns and weather prediction. Observations at different height and different wind velocities are possible by changing the operating parameters of WP. A set of Doppler power spectra is the standard form of WP data. Wind velocity, direction and wind velocity turbulence at different heights can be derived from it. Modern wind profilers operate for long duration and generate approximately 4 megabytes of data per hour. The radar data stream contains Doppler power spectra from different radar configurations with echoes from different atmospheric targets. In order to facilitate systematic study, this data needs to be segregated according the type of target. A reliable automated target classification technique is required to do this job. Classical techniques of radar target identification use pattern matching and minimization of mean squared error, Euclidean distance etc. These techniques are not effective for the classification of WP echoes, as these targets do not have well-defined signature in Doppler power spectra. This paper presents an effective target classification technique based on range-Doppler features.

  7. Demonstration of Advanced Geophysics and Classification Technologies on Munitions Response Sites, Pole Mountain Target and Maneuver Area, Wyoming

    DTIC Science & Technology

    2012-03-01

    FINAL REPORT Demonstration of Advanced Geophysics and Classification Technologies on Munitions Response Sites Pole Mountain Target and...RESPONSIBLE PERSON 19b. TELEPHONE NUMBER (Include area code) 27-03-2012 Final Report May 2011 - March 2012 Demonstration of Advanced Geophysics and...document serves as the Environmental Security Technology Certification Program (ESTCP) Demonstration Report for the Demonstration of Advanced Geophysics

  8. Quantum radar cross sections

    NASA Astrophysics Data System (ADS)

    Lanzagorta, Marco

    2010-06-01

    The radar cross section σC is an objective measure of the "radar visibility" of an object. As such, σC is an important concept for the correct characterization of the operational performance of radar systems. Furthermore, σC is equally essential for the design and development of stealth weapon systems and platforms. Recent years have seen the theoretical development of quantum radars, that is, radars that operate with a small number of photons. In this regime, the radar-target interaction is described through photon-atom scattering processes governed by the laws of quantum electrodynamics. As such, it is theoretically inconsistent to use the same σC to characterize the performance of a quantum radar. In this paper we define a quantum radar cross section σQ based on quantum electrodynamics and interferometric considerations. We discuss the theoretical challenges of defining σQ, as well as computer simulations of σC and σQ for simple targets.

  9. 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

  10. Radar high-speed maneuvering target detection based on joint second-order keystone transform and modified integrated cubic phase function

    NASA Astrophysics Data System (ADS)

    Zhang, Jiancheng; Su, Tao; Li, Yanyan; Zheng, Jibin

    2016-07-01

    Long-time coherent integration is an effective means to improve the radar detection ability of high-speed maneuvering targets with jerk motion. However, the range migration (RM) and Doppler frequency migration (DFM) have a great impact on the integration performance. To overcome these problems, a unique method, called the second-order keystone transform modified integrated cubic phase function (SKT-MICPF), is proposed. In this method, the velocity compensation and SKT are jointly employed to correct the RM. After the RM correction, the azimuth echoes of a range cell where a target is located can be modeled as a cubic phase signal (CPS), whose chirp rate (CR) and quadratic CR are related to the target's radial acceleration and jerk, respectively. Thereafter, an effective parameters' estimation algorithm for CPS, called MICPF, is proposed and applied to compensate the DFM. After that, coherent integration and target detection are accomplished via the fast Fourier transform and constant false alarm rate technique, successively. Compared with the improved axis rotation discrete chirp Fourier transform, the SKT-MICPF achieves close detection performance, but greatly reduces the computational complexity. The results of simulation and real radar data demonstrate the validity of the proposed algorithm.

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

    PubMed

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

    2016-09-01

    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.

  12. Radar cross-sectional study using noise radar

    NASA Astrophysics Data System (ADS)

    Freundorfer, A. P.; Siddiqui, J. Y.; Antar, Y. M. M.

    2015-05-01

    A noise radar system is proposed with capabilities to measure and acquire the radar cross-section (RCS) of targets. The proposed system can cover a noise bandwidth of near DC to 50 GHz. The noise radar RCS measurements were conducted for selective targets like spheres and carpenter squares with and without dielectric bodies for a noise band of 400MHz-5000MHz. The bandwidth of operation was limited by the multiplier and the antennae used.

  13. High-resolution instrumentation radar

    NASA Astrophysics Data System (ADS)

    Dydbal, Robert B.; Hurlbut, Keith H.; Mori, Tsutomu T.

    1987-03-01

    An instrumentation radar that uses a chirp waveform to achieve high-range resolution is described. High-range-resolution instrumentation radars evaluate the target response to operational waveforms used in high-performance radars and/or obtain a display of the individual target scattering mechanisms to better understand the scattering process. This particular radar was efficiently constructed from a combination of commercially available components and in-house fabricated circuitry. This instrumentation radar operates at X-band and achieves a 4.9-in-range resolution. A key feature of the radar is the combination of amplitude weighting with a high degree of waveform fidelity to achieve a very good range sidelobe performance. This range sidelobe performance is important to avoid masking lower level target returns in the range sidelobes of higher target returns.

  14. FMCW Radar Jamming Techniques and Analysis

    DTIC Science & Technology

    2013-09-01

    discussed. 14. SUBJECT TERMS FMCW Radar , LPI , Jamming, Electronic Warfare 15. NUMBER OF PAGES 103 16. PRICE CODE 17. SECURITY CLASSIFICATION...Among the many variations of LPI radar systems, Frequency-Modulated Continuous Wave ( FMCW ) radar has not only the ability to avoid detection, but... LPI radars and possible electronic protection (EP) mechanisms that may be implemented in the FMCW emitter. The research questions can be summarized

  15. An Acoustic Signal Enhancement Method Based on Independent Vector Analysis for Moving Target Classification in the Wild.

    PubMed

    Zhao, Qin; Guo, Feng; Zu, Xingshui; Chang, Yuchao; Li, Baoqing; Yuan, Xiaobing

    2017-09-28

    In this paper, we study how to improve the performance of moving target classification by using an acoustic signal enhancement method based on independent vector analysis (IVA) in the unattended ground sensor (UGS) system. Inspired by the IVA algorithm, we propose an improved IVA method based on a microphone array for acoustic signal enhancement in the wild, which adopts a particular multivariate generalized Gaussian distribution as the source prior, an adaptive variable step strategy for the learning algorithm and discrete cosine transform (DCT) to convert the time domain observed signals to the frequency domain. We term the proposed method as DCT-G-IVA. Moreover, we design a target classification system using the improved IVA method for signal enhancement in the UGS system. Different experiments are conducted to evaluate the proposed method for acoustic signal enhancement by comparing with the baseline methods in our classification system under different wild environments. The experimental results validate the superiority of the DCT-G-IVA enhancement method in the classification system for moving targets in the presence of dynamic wind noise.

  16. Combined target factor analysis and Bayesian soft-classification of interference-contaminated samples: forensic fire debris analysis.

    PubMed

    Williams, Mary R; Sigman, Michael E; Lewis, Jennifer; Pitan, Kelly McHugh

    2012-10-10

    A bayesian soft classification method combined with target factor analysis (TFA) is described and tested for the analysis of fire debris data. The method relies on analysis of the average mass spectrum across the chromatographic profile (i.e., the total ion spectrum, TIS) from multiple samples taken from a single fire scene. A library of TIS from reference ignitable liquids with assigned ASTM classification is used as the target factors in TFA. The class-conditional distributions of correlations between the target and predicted factors for each ASTM class are represented by kernel functions and analyzed by bayesian decision theory. The soft classification approach assists in assessing the probability that ignitable liquid residue from a specific ASTM E1618 class, is present in a set of samples from a single fire scene, even in the presence of unspecified background contributions from pyrolysis products. The method is demonstrated with sample data sets and then tested on laboratory-scale burn data and large-scale field test burns. The overall performance achieved in laboratory and field test of the method is approximately 80% correct classification of fire debris samples.

  17. Micropower impulse radar imaging

    SciTech Connect

    Hall, M.S.

    1995-11-01

    From designs developed at the Lawrence Livermore National Laboratory (LLNL) in radar and imaging technologies, there exists the potential for a variety of applications in both public and private sectors. Presently tests are being conducted for the detection of buried mines and the analysis of civil structures. These new systems use a patented ultra-wide band (impulse) radar technology known as Micropower Impulse Radar (GPR) imaging systems. LLNL has also developed signal processing software capable of producing 2-D and 3-D images of objects embedded in materials such as soil, wood and concrete. My assignment while at LLNL has focused on the testing of different radar configurations and applications, as well as assisting in the creation of computer algorithms which enable the radar to scan target areas of different geometeries.

  18. MARSnet: Mission-aware Autonomous Radar Sensor Network for Future Combat Systems 12/8/06 to 12/31/09

    DTIC Science & Technology

    2010-01-01

    CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF PAGES 816 19a. NAME OF RESPONSIBLE PERSON a. REPORT unclassified b. ABSTRACT...Cybernetics. [Pages 496- 524 in this Report] [28] Hong Sam Le, Qilian Liang, “Multi-target Identification and Classification in Cognitive Radar Sensor Networks...through-foliage detection, tracking and classification . The radio channels can be categorized in a number of dif- ferent ways, such as narrowband versus

  19. Detection of target distance in the presence of an interfering reflection using a frequency-stepped double side-band suppressed carrier microwave radar system

    NASA Technical Reports Server (NTRS)

    Ybarra, Gary A.; Ardalan, Sasan H.; Hearn, Chase P.; Neece, Robert T.; Marshall, Robert E.

    1991-01-01

    A technique for detecting the distance to a highly reflective target in the presence of an interesting reflection using a frequency-stepped double-sideband suppressed carrier (DSBSC) microwave-millimeter-wave radar system is analytically derived. The main result of the analysis shows that the measured group delays produced by the DSBSC system possess a periodicity inversely proportional to the difference between the time delays to the target and interferer, independent of the signal-to-interference ratio (SIR). Simulation results are presented in the context of electron plasma density range estimation using a block diagram communications CAD tool. A unique and accurate plasma model is introduced. A high-resolution spectral estimation technique based on an autoregressive time series analysis is applied to the measured group delays, and it is shown that accurate target distance estimates may be obtained, independent of SIR.

  20. New experiments in inverse synthetic aperture radar image exploitation for maritime surveillance

    NASA Astrophysics Data System (ADS)

    Sadjadi, Firooz A.

    2014-06-01

    This paper provides a summary of recent experimental study in using signatures obtained via polarimetric inverse synthetic aperture radar (ISAR) for classification of small boats in littoral environments. First step in discerning the intention of any small boat is to classify and fingerprint it so it can be observed over an extended period of time. Currently, ISAR techniques are used for large ship classification. Large ships tend to have a rich set of discernible features making classification straightforward. However, small boats rarely have a rich set of discernible features, and are more vulnerable to motion-based range migration that leads to severe signature blurring, thus making classification more challenging. The emphasis of this paper is on the development and use of several enhancement methods for polarimetric ISAR imagery of small boats followed by a target classification study whereby the enhanced signatures of two boats were used to extract several separability metrics to ascertain the effectiveness of these distance measure for target classification.

  1. Three-dimensional laser radar modeling

    NASA Astrophysics Data System (ADS)

    Steinvall, Ove K.; Carlsson, Tomas

    2001-09-01

    Laser radars have the unique capability to give intensity and full 3-D images of an object. Doppler lidars can give velocity and vibration characteristics of an objects. These systems have many civilian and military applications such as terrain modelling, depth sounding, object detection and classification as well as object positioning. In order to derive the signal waveform from the object one has to account for the laser pulse time characteristics, media effects such as the atmospheric attenuation and turbulence effects or scattering properties, the target shape and reflection (BRDF), speckle noise together with the receiver and background noise. Finally the type of waveform processing (peak detection, leading edge etc.) is needed to model the sensor output to be compared with observations. We have developed a computer model which models performance of a 3-D laser radar. We will give examples of signal waveforms generated from model different targets calculated by integrating the laser beam profile in space and time over the target including reflection characteristics during different speckle and turbulence conditions. The result will be of help when designing and using new laser radar systems. The importance of different type of signal processing of the waveform in order to fulfil performance goals will be shown.

  2. Tumor initiation and progression in hepatocellular carcinoma: risk factors, classification, and therapeutic targets

    PubMed Central

    Severi, Tamara; van Malenstein, Hannah; Verslype, Chris; van Pelt, Jos F

    2010-01-01

    Hepatocellular carcinoma (HCC) is a major health problem worldwide responsible for 500 000 deaths annually. A number of risk factors are associated with either the induction of the disease or its progression; these include infection with hepatitis B or C virus, alcohol consumption, non-alcoholic steatohepatitis and certain congenital disorders. In around 80% of the cases, HCC is associated with cirrhosis or advanced fibrosis and with inflammation and oxidative stress. In this review we focus firstly on the different risk factors for HCC and summarize the mechanisms by which each is considered to contribute to HCC. In the second part we look at the molecular processes involved in cancer progression. HCC development is recognized as a multistep process that normally develops over many years. Over this period several mutations accumulate in the cell and that stimulate malign transformation, growth, and metastatic behavior. Over the recent years it has become evident that not only the tumor cell itself but also the tumor microenviroment plays a major role in the development of a tumor. There is a direct link between the role of inflammation and cirrhosis with this microenviroment. Both in vitro and in vivo it has been shown that tumor formation and metastatic properties are linked to epithelial-mesenchymal transition (EMT), a process by which facillitates the tumor cell's attempts to migrate to a more favourable microenviroment. Several groups have analyzed the gene expression in HCC and its surrounding tissue by microarray and this has resulted in the molecular classification into a distinct number of classes. Here we also found a role for hypoxia induced gene expression leading to a clinically more aggressive gene expression in HCC. Molecular analysis also helped to identify important cellular pathways and possible therapeutic targets. The first molecule that in this way has shown clinical application for liver cancer is the multikinase inhibitor sorafenib, others

  3. Radar investigation of asteroids

    NASA Technical Reports Server (NTRS)

    Ostro, S. J.

    1984-01-01

    The initial radar observations of the mainbelt asteroids 9 Metis, 27 Euterpe, and 60 Echo are examined. For each target, data are taken simultaneously in the same sense of circular polarization as transmitted as well as in the opposite (OC) sense. Estimates of the radar cross sections provide estimates of the circular polarization ratio, and the normalized OC radar cross section. The circular polarization ratio, is comparable to values measured for other large S type asteroids and for a few much smaller, Earth approaching objects, most of the echo is due to single reflection backscattering from smooth surface elements.

  4. Spectral dependence of texture features integrated with hyperspectral data for area target classification improvement

    NASA Astrophysics Data System (ADS)

    Bangs, Corey F.; Kruse, Fred A.; Olsen, Chris R.

    2013-05-01

    Hyperspectral data were assessed to determine the effect of integrating spectral data and extracted texture feature data on classification accuracy. Four separate spectral ranges (hundreds of spectral bands total) were used from the Visible and Near Infrared (VNIR) and Shortwave Infrared (SWIR) portions of the electromagnetic spectrum. Haralick texture features (contrast, entropy, and correlation) were extracted from the average gray-level image for each of the four spectral ranges studied. A maximum likelihood classifier was trained using a set of ground truth regions of interest (ROIs) and applied separately to the spectral data, texture data, and a fused dataset containing both. Classification accuracy was measured by comparison of results to a separate verification set of test ROIs. Analysis indicates that the spectral range (source of the gray-level image) used to extract the texture feature data has a significant effect on the classification accuracy. This result applies to texture-only classifications as well as the classification of integrated spectral data and texture feature data sets. Overall classification improvement for the integrated data sets was near 1%. Individual improvement for integrated spectral and texture classification of the "Urban" class showed approximately 9% accuracy increase over spectral-only classification. Texture-only classification accuracy was highest for the "Dirt Path" class at approximately 92% for the spectral range from 947 to 1343nm. This research demonstrates the effectiveness of texture feature data for more accurate analysis of hyperspectral data and the importance of selecting the correct spectral range to be used for the gray-level image source to extract these features.

  5. Inverse synthetic aperture radar imaging of targets with complex motions based on modified chirp rate-quadratic chirp rate distribution for cubic phase signal

    NASA Astrophysics Data System (ADS)

    Yanyan, Li; Tao, Su; Jibin, Zheng

    2015-01-01

    For targets with complex motions, the time-varying Doppler frequency deteriorates inverse synthetic aperture radar (ISAR) images. After range alignment and phase adjustment, azimuth echoes in a range cell can be modeled as multicomponent cubic phase signals (CPSs). The chirp rate and the quadratic chirp rate of the CPS are identified as the causes of the time-varying Doppler frequency; thus, it is necessary to estimate these two parameters correctly to obtain a well-focused ISAR image. The parameter-estimation algorithm based on the modified chirp rate-quadratic chirp rate distribution (M-CRQCRD) is proposed for the CPS and applied to the ISAR imaging of targets with complex motions. The computational cost of M-CRQCRD is low, because it can be implemented by the fast Fourier transform (FFT) and the nonuniform FFT easily. Compared to two representative parameter-estimation algorithms, the M-CRQCRD can acquire a higher antinoise performance due to the introduction of an optimal lag-time. Through simulations and analyses for the synthetic radar data, the effectiveness of the M-CRQCRD and the imaging algorithm based on the M-CRQCRD are verified.

  6. GPM Level 1 Requirements Validation with Groundbased Dual-polarization radars

    NASA Astrophysics Data System (ADS)

    Chandra, C. V.; Chen, H.; Le, M.; Biswas, S.; Ganesan, K.; Petersen, W. A.

    2016-12-01

    The two advanced instruments onboard the Global Precipitation Measurement (GPM) Core Observatory satellite, namely, Dual-frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI), can provide detailed precipitation observations over most of the globe. As an integral part of the GPM mission, ground validation helps to quantify precipitation measurement uncertainty and provide insight into the physical and statistical basis of GPM retrieval algorithms. Therein ground-based dual-polarization radar has shown great potential to estimate surface rainfall rate and amount. The combination of dual-polarization measurements and environmental temperature information is also capable of identifying different hydrometeor types over the radar illuminated scanning volumes. This paper presents the validation of GPM level1 requirements as part of the GPM ground validation effort. The requirements validations using the high resolution DFW CASA radar network as well as target of opportunity dual-polarization radars are presented. The ground radar based hydrometeor classification methodology implemented in the validation study will be described.. In addition, the high-resolution urban radar network deployed in Dallas-Fort Worth is used for detailed evaluation of instantaneous rainfall rate product of GPM. Quantitative evaluation of GPM rainfall products and statistical analysis between GPM and ground radar snowfall products will be provided based on a large number of GPM satellite overpass cases.

  7. Radar for tracer particles

    NASA Astrophysics Data System (ADS)

    Ott, Felix; Herminghaus, Stephan; Huang, Kai

    2017-05-01

    We introduce a radar system capable of tracking a 5 mm spherical target continuously in three dimensions. The 10 GHz (X-band) radar system has a transmission power of 1 W and operates in the near field of the horn antennae. By comparing the phase shift of the electromagnetic wave traveling through the free space with an IQ-mixer, we obtain the relative movement of the target with respect to the antennae. From the azimuth and inclination angles of the receiving antennae obtained in the calibration, we reconstruct the target trajectory in a three-dimensional Cartesian system. Finally, we test the tracking algorithm with target moving in circular as well as in pendulum motions and discuss the capability of the radar system.

  8. Radar Investigations of Asteroids

    NASA Technical Reports Server (NTRS)

    Ostro, S. J.

    1984-01-01

    Radar investigations of asteroids, including observations during 1984 to 1985 of at least 8 potential targets and continued analyses of radar data obtained during 1980 to 1984 for 30 other asteroids is proposed. The primary scientific objectives include estimation of echo strength, polarization, spectral shape, spectral bandwidth, and Doppler shift. These measurements yield estimates of target size, shape, and spin vector; place constraints on topography, morphology, density, and composition of the planetary surface; yield refined estimates of target orbital parameters; and reveals the presence of asteroidal satellites.

  9. Radar applications overview

    NASA Astrophysics Data System (ADS)

    Greenspan, Marshall

    1996-06-01

    During the fifty years since its initial development as a means of providing early warning of airborne attacks against allied countries during World War II, radar systems have developed to the point of being highly mobile and versatile systems capable of supporting a wide variety of remote sensing applications. Instead of being tied to stationary land-based sites, radar systems have found their way into highly mobile land vehicles as well as into aircraft, missiles, and ships of all sizes. Of all these applications, however, the most exciting revolution has occurred in the airborne platform arena where advanced technology radars can be found in all shapes and sizes...ranging from the large AWACS and Joint STARS long range surveillance and targeting systems to small millimeter wave multi-spectral sensors on smart weapons that can detect and identify their targets through the use of highly sophisticated digital signal processing hardware and software. This paper presents an overview of these radar applications with the emphasis on modern airborne sensors that span the RF spectrum. It will identify and describe the factors that influence the parameters of low frequency and ultra wide band radars designed to penetrate ground and dense foliage environments and locate within them buried mines, enemy armor, and other concealed or camouflaged weapons of war. It will similarly examine the factors that lead to the development of airborne radar systems that support long range extended endurance airborne surveillance platforms designed to detect and precision-located both small high speed airborne threats as well as highly mobile time critical moving and stationary surface vehicles. The mission needs and associated radar design impacts will be contrasted with those of radar systems designed for high maneuverability rapid acquisition tactical strike warfare platforms, and shorter range cued air-to-surface weapons with integral smart radar sensors.

  10. Radar Imaging of Non-Uniformly Rotating Targets via a Novel Approach for Multi-Component AM-FM Signal Parameter Estimation

    PubMed Central

    Wang, Yong

    2015-01-01

    A novel radar imaging approach for non-uniformly rotating targets is proposed in this study. It is assumed that the maneuverability of the non-cooperative target is severe, and the received signal in a range cell can be modeled as multi-component amplitude-modulated and frequency-modulated (AM-FM) signals after motion compensation. Then, the modified version of Chirplet decomposition (MCD) based on the integrated high order ambiguity function (IHAF) is presented for the parameter estimation of AM-FM signals, and the corresponding high quality instantaneous ISAR images can be obtained from the estimated parameters. Compared with the MCD algorithm based on the generalized cubic phase function (GCPF) in the authors’ previous paper, the novel algorithm presented in this paper is more accurate and efficient, and the results with simulated and real data demonstrate the superiority of the proposed method. PMID:25806870

  11. Shuttle orbiter radar cross-sectional analysis

    NASA Technical Reports Server (NTRS)

    Cooper, D. W.; James, R.

    1979-01-01

    Theoretical and model simulation studies on signal to noise levels and shuttle radar cross section are described. Pre-mission system calibrations, system configuration, and postmission system calibration of the tracking radars are described. Conversion of target range, azimuth, and elevation into radar centered east north vertical position coordinates are evaluated. The location of the impinging rf energy with respect to the target vehicles body axis triad is calculated. Cross section correlation between the two radars is presented.

  12. Venus Radar Mapper (VRM): Multimode radar system design

    NASA Technical Reports Server (NTRS)

    Johnson, William T. K.; Edgerton, Alvin T.

    1986-01-01

    The surface of Venus has remained a relative mystery because of the very dense atmosphere that is opaque to visible radiation and, thus, normal photographic techniques used to explore the other terrestrial objects in the solar system are useless. The atmosphere is, however, almost transparent to radar waves and images of the surface have been produced via Earth-based and orbital radars. The technique of obtaining radar images of a surface is variously called side looking radar, imaging radar, or synthetic aperture radar (SAR). The radar requires a moving platform in which the antenna is side looking. High resolution is obtained in the cross-track or range direction by conventional radar pulse encoding. In the along-track or azimuth direction, the resolution would normally be the antenna beam width, but for the SAR case, a much longer antenna (or much sharper beam) is obtained by moving past a surface target as shown, and then combining the echoes from many pulses, by using the Doppler data, to obtain the images. The radar design of the Venus Radar Mapper (VRM) is discussed. It will acquire global radar imagery and altimetry data of the surface of Venus.

  13. Classification of Archaeological Targets by the Use of Temporary Magnetic Variations Examination

    NASA Astrophysics Data System (ADS)

    Finkelstein, Michael; Eppelbaum, Lev

    2015-04-01

    Many buried magnetized archaeological and geological objects producing significant magnetic anomalies(for instance, ancient furnaces, weapon, agricultural targets and high-magnetized basalts) may be classified without high-expensive excavations. Such a classification may be conducted on the basis of comprehensive studying temporary magnetic variations over these objects. It is especially significant for archaeogeophysical investigations in the areas of world recognized religious and cultural artifacts where all excavations are forbidden (Eppelbaum, 2010). Yanovsky's (1978) investigations laid the foundation of the magnetic variations utilization for separation of disturbing objects with high magnetic susceptibility (not depending on intensity of the studied magnetic anomalies). However, these procedures are inapplicable for studying low-intensive and negative magnetic anomalies, where an influence of residual magnetization may be sufficient one. At the same time the approach presented below may be used for investigation of the nature of magnetic anomalies with arbitrary intensity and origin. In the common case (we consider for simplicity that anomalous object is a sphere) the value of magnetic variations η could be estimated using the following expression (Finkelstein and Eppelbaum, 1997): η =f( P ))+δ Ha +δ Ho /δ Ho, where induction parameter P=α √ {κ & &gamma & ω } (Wait, 1951), Ho is the initial field of magnetic variations, Ha is the anomalous component of magnetic variations, κ is the magnetic susceptibility, &gamma is the electric conductivity, ω is the frequency of geomagnetic variations, and α is the radius of the sphere. For the approximate estimation of possible values of anomalous geomagnetic variations (AGV) over sphere within some domain T, we will use an expression of the anomalous vertical magnetic component Z for any point M (x, y, z) in the external space (for the case of vertical magnetization) (Nepomnyaschikh, 1964): Za =( {κ 1 -κ

  14. Whither radar?

    NASA Astrophysics Data System (ADS)

    Radford, M. F.

    The evolution of radar technology in the future is examined with respect to both civilian and military applications. Consideration is given to four broad categories of radar technology where improvements in the state of the art are expected. The categories include: antenna design; transmitter design; receiver/signal processor design; and data handling/radar management technology. The influence of CAD/CAM techniques and very high performance ICs on radar system design is evaluated. A formula is presented for calculating the performance requirements of a radar system with respect to sensitivity, resolution, and optimum data rate.

  15. Prediction of the effects of soil and target properties on the antipersonnel landmine detection performance of ground-penetrating radar: A Colombian case study

    NASA Astrophysics Data System (ADS)

    Lopera, Olga; Milisavljevic, Nada

    2007-09-01

    The performance of ground-penetrating (GPR) radar is determined fundamentally by the soil electromagnetic (EM) properties and the target characteristics. In this paper, we predict the effects of such properties on the antipersonnel (AP) landmine detection performance of GPR in a Colombian scenario. Firstly, we use available soil geophysical information in existing pedotransfer models to calculate soil EM properties. The latter are included in a two-dimensional (2D), finite-difference time-domain (FDTD) modeling program in conjunction with the characteristics of AP landmines to calculate the buried target reflection. The approach is applied to two soils selected among Colombian mine-affected areas, and several local improvised explosive devices (IEDs) and AP landmines are modeled as targets. The signatures from such targets buried in the selected soils are predicted, considering different conditions. Finally, we show how the GPR can contribute in detecting low- and non-metallic targets in these Colombian soils. Such a system could be quite adequate for complementing humanitarian landmine detection by metal detectors.

  16. High-Resolution Radar Imaging

    DTIC Science & Technology

    1990-01-14

    vThe goal of this project is to formulate and investigate new approaches for forming images of radar targets from spotlight-mode, delay-doppler...the new methods we are studying. There are two modules in the program. The first module produces simulated radar back-scatter data. The simulation...gives the model and fundamental estimation equations for the method we are developing. The abstract is: "A new approach to high resolution radar

  17. Progress in coherent laser radar

    NASA Technical Reports Server (NTRS)

    Vaughan, J. M.

    1986-01-01

    Considerable progress with coherent laser radar has been made over the last few years, most notably perhaps in the available range of high performance devices and components and the confidence with which systems may now be taken into the field for prolonged periods of operation. Some of this increasing maturity was evident at the 3rd Topical Meeting on Coherent Laser Radar: Technology and Applications. Topics included in discussions were: mesoscale wind fields, nocturnal valley drainage and clear air down bursts; airborne Doppler lidar studies and comparison of ground and airborne wind measurement; wind measurement over the sea for comparison with satellite borne microwave sensors; transport of wake vortices at airfield; coherent DIAL methods; a newly assembled Nd-YAG coherent lidar system; backscatter profiles in the atmosphere and wavelength dependence over the 9 to 11 micrometer region; beam propagation; rock and soil classification with an airborne 4-laser system; technology of a global wind profiling system; target calibration; ranging and imaging with coherent pulsed and CW system; signal fluctuations and speckle. Some of these activities are briefly reviewed.

  18. [MicroRNA Target Prediction Based on Support Vector Machine Ensemble Classification Algorithm of Under-sampling Technique].

    PubMed

    Chen, Zhiru; Hong, Wenxue

    2016-02-01

    Considering the low accuracy of prediction in the positive samples and poor overall classification effects caused by unbalanced sample data of MicroRNA (miRNA) target, we proposes a support vector machine (SVM)-integration of under-sampling and weight (IUSM) algorithm in this paper, an under-sampling based on the ensemble learning algorithm. The algorithm adopts SVM as learning algorithm and AdaBoost as integration framework, and embeds clustering-based under-sampling into the iterative process, aiming at reducing the degree of unbalanced distribution of positive and negative samples. Meanwhile, in the process of adaptive weight adjustment of the samples, the SVM-IUSM algorithm eliminates the abnormal ones in negative samples with robust sample weights smoothing mechanism so as to avoid over-learning. Finally, the prediction of miRNA target integrated classifier is achieved with the combination of multiple weak classifiers through the voting mechanism. The experiment revealed that the SVM-IUSW, compared with other algorithms on unbalanced dataset collection, could not only improve the accuracy of positive targets and the overall effect of classification, but also enhance the generalization ability of miRNA target classifier.

  19. German Radar Observation Shuttle Experiment (ROSE)

    NASA Technical Reports Server (NTRS)

    Sleber, A. J.; Hartl, P.; Haydn, R.; Hildebrandt, G.; Konecny, G.; Muehlfeld, R.

    1984-01-01

    The success of radar sensors in several different application areas of interest depends on the knowledge of the backscatter of radar waves from the targets of interest, the variance of these interaction mechanisms with respect to changing measurement parameters, and the determination of the influence of he measuring systems on the results. The incidence-angle dependency of the radar cross section of different natural targets is derived. Problems involved by the combination of data gained with different sensors, e.g., MSS-, TM-, SPOTand SAR-images are analyzed. Radar cross-section values gained with ground-based radar spectrometers and spaceborne radar imaging, and non-imaging scatterometers and spaceborne radar images from the same areal target are correlated. The penetration of L-band radar waves into vegetated and nonvegetated surfaces is analyzed.

  20. Bistatic and Multistatic Radar: Surveillance, Countermeasures, and Radar Cross Sections. (Latest citations from the Aerospace Database)

    NASA Technical Reports Server (NTRS)

    1998-01-01

    The bibliography contains citations concerning the design, development, testing, and evaluation of bistatic and multistatic radar used in surveillance and countermeasure technology. Citations discuss radar cross sections, target recognition and characteristics, ghost recognition, motion image compensation, and wavelet analysis. Stealth aircraft design, stealth target tracking, synthetic aperture radar, and space applications are examined.

  1. Bistatic and Multistatic Radar: Surveillance, Countermeasures, and Radar Cross Sections. (Latest Citations from the Aerospace Database)

    NASA Technical Reports Server (NTRS)

    1997-01-01

    The bibliography contains citations concerning the design, development, testing, and evaluation of bistatic and multistatic radar used in surveillance and countermeasure technology. Citations discuss radar cross sections, target recognition and characteristics, ghost recognition, motion image compensation, and wavelet analysis. Stealth aircraft design, stealth target tracking, synthetic aperture radar, and space applications are examined.

  2. Bistatic and Multistatic Radar: Surveillance, Countermeasures, and Radar Cross Sections. (Latest citations from the Aerospace Database)

    NASA Technical Reports Server (NTRS)

    1998-01-01

    The bibliography contains citations concerning the design, development, testing, and evaluation of bistatic and multistatic radar used in surveillance and countermeasure technology. Citations discuss radar cross sections, target recognition and characteristics, ghost recognition, motion image compensation, and wavelet analysis. Stealth aircraft design, stealth target tracking, synthetic aperture radar, and space applications are examined.

  3. Bistatic and Multistatic Radar: Surveillance, Countermeasures, and Radar Cross Sections. (Latest Citations from the Aerospace Database)

    NASA Technical Reports Server (NTRS)

    1997-01-01

    The bibliography contains citations concerning the design, development, testing, and evaluation of bistatic and multistatic radar used in surveillance and countermeasure technology. Citations discuss radar cross sections, target recognition and characteristics, ghost recognition, motion image compensation, and wavelet analysis. Stealth aircraft design, stealth target tracking, synthetic aperture radar, and space applications are examined.

  4. Improving Maritime Domain Awareness Using Neural Networks for Target of Interest Classification

    DTIC Science & Technology

    2015-03-01

    longer training times for neural networks since the magnitudes are small at the tails of the sigmoid function. The RP uses an update valueα rather...other” are images of clouds, whales , aircraft, etc. Binary classification performance is determined by the number of correct ship image

  5. Global radar units on Venus derived from statistical analysis of Pioneer Venus Orbiter radar data

    NASA Technical Reports Server (NTRS)

    Davis, P. A.; Kozak, R. C.; Schaber, G. G.

    1986-01-01

    The classification of surface radar units on Venus using an unsupervised cluster analysis of Pioneer Venus radar reflectivity and root-mean-square (rms)-slope data is described. The advantages of the unsupervised analysis are discussed. F tests are utilized to evaluate the numerical significance of the clusters. The derived rms-slope data and reflectivity for 15 radar units are presented. The relations between radar data bases and elevation are studied. The lowlands, rolling plains, highlands, and mountainous surface of Venus are examined. The geology of Venus landing sites and radar properties, and the surface radar reflectivity images and earth-based images are compared. The spatial relations between classification units are calculated. It is concluded that the unsupervised analysis data correlate well with Head et al. (1985b) data and produce more detailed classification images.

  6. Spaceborne laser radar.

    NASA Technical Reports Server (NTRS)

    Flom, T.

    1972-01-01

    Development of laser systems to acquire and track targets in applications such as the rendezvous and docking of two spacecraft. A scan technique is described whereby a narrow laser beam is simultaneously scanned with an equally narrow receiver field-of-view without the aid of mechanical gimbals. Equations are developed in order to examine the maximum acquisition and tracking rates, and the maximum target range for a scanning laser radar system. A recently built prototype of a small, lightweight, low-power-consuming scanning laser radar is described.

  7. Tracing the spatio-temporal evolution of the Merapi 2010 erupted deposits based on object-oriented classification and object-based image analysis of multi-temporal VHR optical and ALOS radar imagery

    NASA Astrophysics Data System (ADS)

    Thouret, J. C.; Solikhin, A.; Pinel, V.; Kassouk, Z.; Gupta, A.; Liew, S. C.; Oehler, J. F.

    2015-12-01

    We compare the extent to which VHR optical and radar images delineate the eruption impacts and trace the evolution of erupted deposits on active volcanoes. We could identify about 75% of the 2010 Merapi erupted deposits recognized in traditional geological mapping using object-oriented classification and spectral indices on sub-metric GeoEye and Pléiades images. We recognized sixteen PDC depositional units including high-energy surge deposits on the upper south flank, valley-confined BAF deposits channeled in the Gendol River, and overbank BAF with ash-cloud surge deposits on valley margins. We used an innovative method to map PDC and tephra-fall deposits exploiting direct- and cross-polarized L-band SAR data from ALOS-PALSAR before and after the eruption and combining changes in amplitude of the radar signal with temporal decorrelation. Deposits were separated according to increase or decrease in ground backscattering in direct (HH) and cross (HV) polarizations. The maximum likelihood classification applied to ALOS images provided a result consistent with previous studies with 70% classification accuracy for deposits overall. Scatter diagrams of NDWI, NDVI and NDRSI from three VHR images and morphometric analysis of the initial drainage network enabled us to trace the spatio-temporal evolution (2010-2012) of impacted areas against re-vegetation and surficial erosion. In two years after the eruption, the drainage network was fully developed in the upper catchment devastated by high energy surges but far less developped on fans formed by overbank BAF deposits in the middle valley, suggesting the importance of slope gradient and the deposit grain size, permeability and thickness. We updated the Merapi hazard assessment using Pleiades images as the 2010 eruption changed the summit crater morphology and valley channels. Potential sites favorable to future lahar overbank were identified by computing three morphometric parameters of the river channels.

  8. SMAP's Radar OBP Algorithm Development

    NASA Technical Reports Server (NTRS)

    Le, Charles; Spencer, Michael W.; Veilleux, Louise; Chan, Samuel; He, Yutao; Zheng, Jason; Nguyen, Kayla

    2009-01-01

    An approach for algorithm specifications and development is described for SMAP's radar onboard processor with multi-stage demodulation and decimation bandpass digital filter. Point target simulation is used to verify and validate the filter design with the usual radar performance parameters. Preliminary FPGA implementation is also discussed.

  9. Radar Imaging and Feature Extraction

    DTIC Science & Technology

    2007-11-02

    aperture radar (ISAR) autofocus and imaging, synthetic aperture radar (SAR) autofocus and motion compensation, superresolution SAR image formation... superresolution image formation, and two parametric methods, MCRELAX (Motion Compensation RELAX) and MCCLEAN (Motion Compensation CLEAN), for simultaneous target...Direction Estimation) together with WRELAX) algorithm is proposed for the superresolution time delay estimation.

  10. Comparison of monostatic and bistatic bearing estimation performance for low RCS targets

    NASA Astrophysics Data System (ADS)

    Boyle, Robert J.; Wasylkiwskyj, Wasyl

    1994-07-01

    Bistatic radars, specifically forward-scatter radars, are proposed as an alternative to standard monostatic radars against targets whose radar cross sections (RCS) have been reduced by passive means. Forward-scatter radars operate by detecting echoes from a targets forward-scatter RCS, which is insensitive to effects of passive RCS reduction techniques. However, the performance of the forward-scatter radar is compromised when the angular separation between the interference, which propagates directly from the transmitter to the receiver, and the target return is less than the Rayleigh resolution limit of the receiving antenna. This research presents the results of a parametric study of the ability of a forward-scatter radar to detect and measure the bearing of a large target, whose RCS is reduced via passive means. Super-resolution array processing techniques, particularly root-MUSIC (multiple signal classification), are used to overcome the traditional limitations resulting from the Rayleigh resolution limit of the antenna. The study compares the received power and the bearing measurement accuracy of the forward-scatter radar to that of an 'equivalent' monostatic radar system. The results indicate that forward-scatter radars enjoy advantages in detection and bearing measurement when the backscatter RCS of the target has been reduced and when the target is close to the baseline. The results also indicate that, through the use of super-resolution array processing, the capability of the forward-scatter radar to accurately measure the bearing of the target is dependent upon the amount of interference from the direct wave (i.e., the wave which propagates from the transmitter directly to the receiver) and the correlation between the direct wave and the target echo. Good bearing estimates can be achieved if the correlation coefficient is less than 0.95. Bearing measurements may be improved by suppressing the direct wave by either sidelobe control or null steering

  11. A barrier radar concept

    NASA Astrophysics Data System (ADS)

    Marshall, J.; Ball, C.; Weissman, I.

    A description is given of a low power, light-weight radar that can be quickly set up and operated on batteries for extended periods of time to detect airborne intruders. With low equipment and operating costs, it becomes practical to employ a multiplicity of such radars to provide an unbroken intrusion fence over the desired perimeter. Each radar establishes a single transmitted fan beam extending vertically from horizon to horizon. The beam is generated by a two-face array antenna built in an A-frame configuration and is shaped, through phasing of the array elements, to concentrate the transmitter power in a manner consistent with the expected operating altitude ceiling of the targets of interest. The angular width of this beam in the dimension transverse to the fan depends on the radar transmission frequency and the antenna aperture dimension, but is typically wide enough so that a target at the maximum altitude or range will require tens of seconds to pass through the beam. A large number of independent samples of radar data will thus be available to provide many opportunities for target detection.

  12. Radar Polarimetry

    DTIC Science & Technology

    2004-12-01

    RADAR CROSS SECTION (RCS) σ.................................................. 15 D. THE RADAR SYSTEM...spherical surface, as [13]: rV V s iV rH H s iH E D E E D E ρ ρ = Γ = Γ (2.27) 15 C. RADAR CROSS SECTION (RCS) σ The radar cross section is...Interpretation ⎥ ⎦ ⎤ ⎢ ⎣ ⎡ 10 01 Odd- bounce Surface, sphere, corner reflectors ⎥ ⎦ ⎤ ⎢ ⎣ ⎡ −10 01 Even-bounce Dihedral ⎥

  13. Multi-target QPDR classification model for human breast and colon cancer-related proteins using star graph topological indices.

    PubMed

    Munteanu, Cristian Robert; Magalhães, Alexandre L; Uriarte, Eugenio; González-Díaz, Humberto

    2009-03-21

    The cancer diagnostic is a complex process and, sometimes, the specific markers can interfere or produce negative results. Thus, new simple and fast theoretical models are required. One option is the complex network graphs theory that permits us to describe any real system, from the small molecules to the complex genetic, neural or social networks by transforming real properties in topological indices. This work converts the protein primary structure data in specific Randic's star networks topological indices using the new sequence to star networks (S2SNet) application. A set of 1054 proteins were selected from previous works and contains proteins related or not with two types of cancer, human breast cancer (HBC) and human colon cancer (HCC). The general discriminant analysis method generates an input-coded multi-target classification model with the training/predicting set accuracies of 90.0% for the forward stepwise model type. In addition, a protein subset was modified by single amino acid mutations with higher log-odds PAM250 values and tested with the new classification if can be related with HBC or HCC. In conclusion, we shown that, using simple input data such is the primary protein sequence and the simples linear analysis, it is possible to obtain accurate classification models that can predict if a new protein related with two types of cancer. These results promote the use of the S2SNet in clinical proteomics.

  14. Use of Target Shape and Size in Classification of UXO in Survey Data

    DTIC Science & Technology

    2005-12-01

    be the m ost effective approach. 3.3 Task 3: Develop An Enhanced Target Picker and Target Ranker In Task 3 we developed a more sophisticated...23 21. Shown is a 100 X 200 m clip from the...the nu mber of non-UXO targets while m aintaining most of the sensitivity of traditional physics-based approaches for finding true UXO. As a result

  15. Detection and classification of underwater targets in background noise acoustic daylight

    NASA Astrophysics Data System (ADS)

    Goo, Gee-In

    2003-09-01

    It has been reported that underwater target models, spheres and cylinders can be detected and classified in background acoustic noise. In this paper, the author presents his recent finding that underwater target is detectable in acoustic background noise in open waters. Using a resonance detection technique, G-Transform, the noise background of a number of AUTEC sample data files with mammal clicks were analyzed. From the noise backgrounds in these data files, a number of possible target signatures were observed. It suggests that real underwater targets may be detected and classified passively in background noise.

  16. The Design and Performance Characteristics of a Cellular Logic 3-D Image Classification Processor.

    DTIC Science & Technology

    1981-04-01

    number) Pattern Recognition Cellular Automata " Cellular Logic Target Classificatio4 1Neighborhood Transformation Image Processing Laser Radar iASSTRACT...AND PERFORMANCE CHARACTERISTICS OF A CELLULAR LOGIC 3-D IMAGE CLASSIFICATION PROCESSOR 1 &/. , DISSERTATION AFIT/DS/EE/81-1 Lawrence A. Ankeney... CELLULAR LOGIC 3-D IMAGE - -- A&I PRCSRDTIC T B CLASSIFICATION PROCESSOR Unannounced 0 Justificatio b yD t i u i n Lawrence A. Ankeney, B.S., M.S

  17. Comparative analysis of different implementations of a parallel algorithm for automatic target detection and classification of hyperspectral images

    NASA Astrophysics Data System (ADS)

    Paz, Abel; Plaza, Antonio; Plaza, Javier

    2009-08-01

    Automatic target detection in hyperspectral images is a task that has attracted a lot of attention recently. In the last few years, several algoritms have been developed for this purpose, including the well-known RX algorithm for anomaly detection, or the automatic target detection and classification algorithm (ATDCA), which uses an orthogonal subspace projection (OSP) approach to extract a set of spectrally distinct targets automatically from the input hyperspectral data. Depending on the complexity and dimensionality of the analyzed image scene, the target/anomaly detection process may be computationally very expensive, a fact that limits the possibility of utilizing this process in time-critical applications. In this paper, we develop computationally efficient parallel versions of both the RX and ATDCA algorithms for near real-time exploitation of these algorithms. In the case of ATGP, we use several distance metrics in addition to the OSP approach. The parallel versions are quantitatively compared in terms of target detection accuracy, using hyperspectral data collected by NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) over the World Trade Center in New York, five days after the terrorist attack of September 11th, 2001, and also in terms of parallel performance, using a massively Beowulf cluster available at NASA's Goddard Space Flight Center in Maryland.

  18. Large phased-array radars

    SciTech Connect

    Brookner, D.E.

    1988-12-15

    Large phased-array radars can play a very important part in arms control. They can be used to determine the number of RVs being deployed, the type of targeting of the RVs (the same or different targets), the shape of the deployed objects, and possibly the weight and yields of the deployed RVs. They can provide this information at night as well as during the day and during rain and cloud covered conditions. The radar can be on the ground, on a ship, in an airplane, or space-borne. Airborne and space-borne radars can provide high resolution map images of the ground for reconnaissance, of anti-ballistic missile (ABM) ground radar installations, missile launch sites, and tactical targets such as trucks and tanks. The large ground based radars can have microwave carrier frequencies or be at HF (high frequency). For a ground-based HF radar the signal is reflected off the ionosphere so as to provide over-the-horizon (OTH) viewing of targets. OTH radars can potentially be used to monitor stealth targets and missile traffic.

  19. Large phased-array radars

    NASA Astrophysics Data System (ADS)

    Brookner, Eli, Dr.

    1988-12-01

    Large phased-array radars can play a very important part in arms control. They can be used to determine the number of RVs being deployed, the type of targeting of the RVs (the same or different targets), the shape of the deployed objects, and possibly the weight and yields of the deployed RVs. They can provide this information at night as well as during the day and during rain and cloud covered conditions. The radar can be on the ground, on a ship, in an airplane, or space-borne. Airborne and space-borne radars can provide high resolution map images of the ground for reconnaissance, of anti-ballistic missile (ABM) ground radar installations, missile launch sites, and tactical targets such as trucks and tanks. The large ground based radars can have microwave carrier frequencies or be at HF (high frequency). For a ground-based HF radar the signal is reflected off the ionosphere so as to provide over-the-horizon (OTH) viewing of targets. OTH radars can potentially be used to monitor stealth targets and missile traffic.

  20. Radar operation in a hostile electromagnetic environment

    SciTech Connect

    Doerry, Armin Walter

    2014-03-01

    Radar ISR does not always involve cooperative or even friendly targets. An adversary has numerous techniques available to him to counter the effectiveness of a radar ISR sensor. These generally fall under the banner of jamming, spoofing, or otherwise interfering with the EM signals required by the radar sensor. Consequently mitigation techniques are prudent to retain efficacy of the radar sensor. We discuss in general terms a number of mitigation techniques.