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检索条件"任意字段=Conference on Signal and Data Processing of Small Targets 2000"

共 865 条记录，以下是391-400 订阅

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ROBUST RADAR DETECTION OF MOVING GROUND targets WITH STAP

ROBUST RADAR DETECTION OF MOVING GROUND TARGETS WITH STAP

引用

IET International conference on Radar Systems (Radar 2007)

作者： Paul G. Kealey David M. Carrington QinetiQ Limited UK

Airborne radar sensors are able to detect small and slow moving ground targets using short dwell times by distinguishing the weak target signature from the dominant ground clutter signal. The capability of a Ground Moving Target Indication (GMTI) sensor is principally governed by the Probability of Detection (PD). Other capabilities such as geolocation, tracking and recognition are derived from these detection data. One method used to enhance the PD for platforms with multiple phase centres is Space Time Adaptive processing (STAP). In this paper we report an experimental assessment of a robust STAP algorithm [1, 5, 6] using the QinetiQ Enhanced Surveillance Radar (ESR) data. From our results it is apparent that robustness may be introduced if a selective training methodology is employed to estimate the data covariance. Results are given for both Pre- and Post-Doppler STAP.

关键词： STAP Detection Robust GMTI

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An Effective SAR-GMTI Technique Based on Eigen-Decomposition of the Covariance Matrix

An Effective SAR-GMTI Technique Based on Eigen-Decomposition...

引用

Asian and Pacific conference on Synthetic Aperture Radar (APSAR)

作者： Jing Yu Guisheng Liao National Lab of Radar Signal Processing Xidian University Xi'an China

An effective multi-channel SAR-GMTI technique based on eigen-decomposition of the covariance matrix is proposed. The variation of the sum of small eigenvalues of the covariance matrix is used to detect moving targets which can avoid clutter suppression. The radial velocity of the moving target is estimated by two steps. Firstly, using the interferometric phase of two SAR images to get the coarse radial velocity estimation, then the more precise radial velocity is obtained by searching the space-domain steering vector of the moving target. It overcomes the sensitivity of the interferometric phase to clutter and noise. The performance of the approach is analyzed in detail. The merit of the presented technique is demonstrated by simulated and measured SAR data.

关键词： Covariance matrix Clutter Eigenvalues and eigenfunctions Synthetic aperture radar Radar detection Phase estimation Phase noise Radar imaging Azimuth Radar signal processing

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An Effective SAR-GMTI Technique Based on Eigen-Decomposition of the Covariance Matrix

An Effective SAR-GMTI Technique Based on Eigen-Decomposition...

引用

2007 Asian and Pacific conference on Synthetic Aperture Radar(APSAR 2007)

作者： YU Jing LIAO Guisheng National Lab of Radar signal processing,Xidian University,Xi’an,710071,China

An effective multi-channel SAR-GMTI technique based on eigen-decomposition of the covariance matrix is proposed. The variation of the sum of small eigenvalues of the covariance matrix is used to detect moving targets which can avoid clutter suppression. The radial velocity of the moving target is estimated by two steps. Firstly,using the interferometric phase of two SAR images to get the coarse radial velocity estimation,then the more precise radial velocity is obtained by searching the space-domain steering vector of the moving target. It overcomes the sensitivity of the interferometric phase to clutter and noise. The performance of the approach is analyzed in detail. The merit of the presented technique is demonstrated by simulated and measured SAR data.

关键词： SAR An Effective SAR-GMTI Technique Based on Eigen-Decomposition of the Covariance Matrix

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PHD filters of second order in target number

PHD filters of second order in target number

引用

18th conference on signal and data processing of small targets

作者： Mahler, Ronald Lockheed Martin MS2 Tact Syst Eagan MN USA

ISBN: (纸本)0819462926

The multitarget recursive Bayes nonlinear filter is the theoretically optimal approach to multisensor-multitarget detection, tracking, and identification. For applications in which this filter is appropriate, it is likely to be tractable for only a small number of targets. In earlier papers we derived closed-form equations for an approximation of this filter based on propagation of a first-order multitarget moment called the probability hypothesis density (PHD). In a recent paper, Erdinc, Willett, and Bar-Shalom argued for the need for a PHD-type filter which remains first-order in the states of individual targets, but which is higher-order in target number. In an earlier paper at this conference we derived a closed-form cardinalized PHD (CPHD) filter, which propagates not only the PHD but also the entire probability distribution on target number. Since the CPHD filter has computational complexity O(m(3)) in the number m of measurements, additional approximation is desirable. In this paper we discuss a second-order approximation called the "binomial filter."

关键词： Digital filtering Nonlinear filtering Sensors Target detection Electroactive polymers Filtering (signal processing) Motion models Picosecond phenomena Electronic filtering Linear filtering

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Peak inspecting and signal recovery methods based on triple correlation - art. no. 623608

Peak inspecting and signal recovery methods based on triple ...

引用

18th conference on signal and data processing of small targets

作者： Cao Hanqiang Li Xutao Chen Rujun Wei Jiaxin Cao Chao Huazhong Univ Sci & Technol Dept Elec & Info Eng Wuhan 430074 Peoples R China

ISBN: (纸本)0819462926

Weak target inspecting and recovering are very important in IR detecting systems. In this paper, triple correlation peak inspecting techniques(TCPIT) are adopted for the signal processing of IR systems in detecting sub-pixel or point targets. Investigations show that the signal-to-noise ratio (SNR) improvement of approximate 23dB can be obtained with the input peak SNR of 0.84 and the input power SNR of -0.93dB. The triple correlation overlapping sampling technique(TCOST) is advanced for restoring signal waveforms of IR detection systems. Investigations show that signal waveforms can effectively be restored in the low signal-to-noise ratio circumstances using this approach.

关键词： triple correlation weak signal inspecting detection of point target IR detecting system

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Comparison of tracklet methods with deterministic dynamics and false signals - art. no. 62360Z

Comparison of tracklet methods with deterministic dynamics a...

引用

18th conference on signal and data processing of small targets

作者： Drummond, Oliver E. Dana-Bashian, David CyberRnD Inc Culver City CA 90230 USA

ISBN: (纸本)0819462926

Track fusion processing is complicated because the estimation errors of a local track and a fusion track for the same target are usually cross-correlated. If these errors are cross-correlated, that should be taken into account when designing the data association processing and the filter used to combine the track data. An approach to dealing with this cross-correlation is to use tracklets. One of the important issues in tracklet fusion performance is whether the dynamics are deterministic, e.g., no filter process noise and no target maneuver. A number of different tracklet methods have been designed. This paper presents a comparison a tracklets-from-tracks approach to a tracklets-from-measurements approach. Tracklet fusion performance is also compared to centralized measurement fusion performance. The emphasis is on performance with targets that exhibit deterministic dynamics and the possibility of measurements caused by false signals.

关键词： target tracking multiple sensor tracking track fusion multiple target tracking sensor data fusion Bayesian methods tracklet distributed tracking estimation and filtering

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Joint detection and tracking of unresolved targets with a joint-bin processing monopulse radar - art. no. 62360T

Joint detection and tracking of unresolved targets with a jo...

引用

18th conference on signal and data processing of small targets

作者： Nandakumaran, N. Sinha, A. Kirubarajan, T. McMaster Univ ETFLab Dept Elect & Comp Engn Hamilton ON Canada

ISBN: (纸本)0819462926

Detection and estimation of multiple unresolved targets with a monopulse radar is limited by the availability of information in monopulse signals. The maximum possible number of targets that can be extracted from the monopulse signals of a single bin is two. Recently two approaches have been proposed in the literature to overcome this limitation. The first is joint-bin processing that exploits target spill-over among adjacent cells by modeling the target returns in the adjacent cells. In addition to making use of the additional information available in target spill-over, it handles a more practical problem where the usual assumption of ideal sampling is relaxed. The second approach is to make use of tracking information in detection through joint detection and tracking with the help of Monte Carlo integration of a particle filter. It was shown that the extraction of even more targets is possible with tracking information. In this paper, a new approach is proposed to combine make the best of these two approaches - a new joint detection and tracking algorithm with multibin processing. The proposed method increases the detection ability as well as tracking accuracy. Simulation studies are carried out. with amplitude comparison monopulse radar for an unresolved target scenario. The relative performances of various methods are also provided.

关键词： U nresolved targets closely-spaced targets monopulse radar multitarget tracking particle filters joint-bin processing

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Fixed-lag sequential Monte Carlo data association

Fixed-lag sequential Monte Carlo data association

引用

18th conference on signal and data processing of small targets

作者： Briers, Mark Doucet, Arnaud Maskell, Simon R. Horridge, Paul R. QinetiQ Ltd. (United Kingdom) Cambridge Univ. (United Kingdom) The Univ. of British Columbia (Canada)

ISBN: (纸本)0819462926

The use of multiple scans of data to improve ones ability to improve target tracking performance is widespread in the tracking literature. In this paper, we introduce a novel application of a recent innovation in the SMC literature that uses multiple scans of data to improve the stochastic approximation (and so the data association ability) of a multiple target Sequential Monte Carlo based tracking system. Such an improvement is achieved by resimulating sampled variates over a fixed-lag time window by artificially extending the space of the target distribution. In doing so, the stochastic approximation is improved and so the data association ambiguity is more readily resolved.

关键词： particle filter Sequential Monte Carlo Multi-target tracking fixed-lag data association out-of-sequence measurements

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Radar measurement noise variance estimation with several targets of opportunity - art. no. 62360M

Radar measurement noise variance estimation with several tar...

引用

18th conference on signal and data processing of small targets

作者： Osborne, Richard W., III Bar-Shalom, Yaakov Univ Connecticut Storrs CT USA

ISBN: (纸本)0819462926

A number of methods exist to track a target's uncertain motion through space using inherently inaccurate sensor measurements. A powerful method of adaptive estimation is the interacting multiple model (IMM) estimator. In order to carry out state estimation from the noisy measurements of a sensor, however, the filter should have knowledge of the statistical characteristics of the noise associated with that sensor. The statistical characteristics (accuracies) of real sensors, however, are not always available, in particular for legacy sensors. This paper presents a method of determining the measurement noise variances of a sensor by using multiple IMM estimators while tracking targets whose motion is not known - targets of opportunity. Combining techniques outlined in [1] and [3], the likelihood functions are obtained for a number of IMM estimators, each with different assumptions on the measurement noise variances. Then a search is carried out to bracket the variances of the sensor measurement noises. The end result consists of estimates of the measurement noise variances of the sensor in question.

关键词： tracking noise estimation

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Effects of multiple targets on the mean level STAP detector

Effects of multiple targets on the mean level STAP detector

引用

CIE International conference on Radar

作者： Van Cao, Tri-Tan Def Sci & Technol Org Edinburgh SA 5111 Australia

ISBN: (纸本)9780780395824

Robustness of the constant false alarm rate (CFAR) mean level adaptive detector for a phased array radar equipped with a space-time adaptive processing (STAP) algorithm :is analysed when the secondary data is contaminated by multiple interfering targets at different ranges. Closed-form analysis is first given based on the assumption of Gaussian interference and Swerling I target models. The deleterious effect on target detection is then experimentally examined using the multi channel airborne radar measurements (MCARM) database. It is found that both the probability of detection and the false alarm rate decrease in accordance with the sum of the signal power of the interfering targets. In addition, the false alarm rate is very sensitive to the presence of interfering targets, in the sense that a small sum (below the noise floor) of their signal power can lower the false alarm rate.

关键词： constant false alarm rate (CFAR) phased array radar space-time adaptive processing (STAP) Gaussian interference swerling I targets

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