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conference on signal and data processing of small targets

作者： Williams, PR Litton Data Syst Agoura Hills CA 91376 USA

ISBN: (纸本)0819428221

The use of Track-Before-Detect (TBD) has been shown to be effective for enhanced target detection in certain cases but performance has been elusive in others. The TBD concept enhances detection by integrating multiple frames of data collected over a period of several seconds. Since the integration period is so long, the target's potential motion must be compensated for. TBD hypothesizes different target trajectories to account for target motion. The problem in analyzing or quantifying TBD behavior is the statistical correlation or dependence among the hypotheses. In this paper we present a theoretical framework for analyzing the TBD concept by utilizing the theory of Simultaneous Statistical Inference. We address the problem by adapting the method of simultaneous confidence intervals developed by Henry Scheffe. This method uses the fact that the confidence ellipsoid of a Gaussian random vector may be constructed as an infinite intersection of linear hyperplanes. In this paper we show that a single TBD hypothesis can be represented as a hyperplane in the detection space. We declare a detection whenever the observation falls on one side of the hyperplane (an ay from the origin). Then,using the Scheffe construction we can approximate the distribution for the TBD detection statistic. Finally, we establish performance bounds and quantify the relationship between the number of hypotheses and detection performance.

关键词： target detection track-before-detect multiple scan integration performance bounds

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Comparison of various schema of filter adaptivity for the tracking of maneuvering targets

Comparison of various schema of filter adaptivity for the tr...

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conference on signal and data processing of small targets

作者： Jouan, A Bosse, E Simard, MA Shahbazian, E Lockheed Martin Canada R&D Dept Montreal PQ Canada

ISBN: (纸本)0819428221

Tracking maneuvering targets is a complex problem which has generated a great deal of effort over the past several years. It has now been well established that in terms of tracking accuracy, the Interacting Multiple Model (IMM) algorithm, where state estimates are mixed, performs significantly better for maneuvering targets than other types of filters (Adaptive Single Model, Input Estimation, Variable Dimension, etc.). However, the complexity of the IMM algorithm can prohibit its use in those applications for which simpler algorithms can not provide the necessary accuracy and which can not afford the computational load of IMM algorithm. This paper presents the evaluation of the tracking accuracy of a multiple model track filter using three different constant-velocity models running in parallel (3CV-PAR) and a maneuver detector. The output estimate is defined by selecting the model whose likelihood function is lower than a Target Maneuver Threshold (TMTh). The tracking performance of the 3CV-PAR track filter is compared to : an adaptive single motion model Kalman filter (ASMMKF);an IMM algorithm using the same three CV models as the 3CV-PAR filter;an IMM filter using a CV model and a constant-acceleration (CA) model producing a CVCA filter;an IMM filter using a CV and two CA models (CA1, CA2) differing only by the level of process noise producing a CV2CA filter. Calculations of the average RMS error on 100 Monte-Carlo runs permit to evaluate the tracking accuracy of the 3CV-PAR track filter compared to the above algorithms on a challenging multiple sensors scenario.

关键词： tracking IMM algorithm

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m-best SD assignment algorithm with application to multitarget tracking

m-best SD assignment algorithm with application to multitarg...

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conference on signal and data processing of small targets

作者： Popp, RL Pattipati, KR Bar-Shalom, Y ALPHATECH Inc Informat Technol Burlington MA 01803 USA

ISBN: (纸本)0819428221

In this paper we describe a novel data association algorithm, termed m-best SD, that determines in O(mSkn(3)) time (m assignments, S lists of size n, k relaxations) the m-best solutions to an SD assignment problem. This algorithm is applied to the following problem. Given line of sight (i.e., incomplete position) measurements from S sensors, sets of complete position measurements are extracted, namely, the 1-st, 2-nd,... m-th best (in terms of likelihood) sets of composite measurements are determined solving a static SD assignment problem. Utilizing the joint likelihood functions used to determine the m-best SD assignment solutions, the composite measurements are then quantified with a probability of being correct using a JPDA-like technique. Lists of composite measurements from successive scans, along with their corresponding probabilities, are then used in turn with a state estimator in a dynamic 2D assignment algorithm to estimate the states of the moving targets over time. The dynamic assignment cost coefficients are based on a likelihood function that incorporates the "true" composite measurement probabilities obtained from the (static) m-best SD assignment solutions. We demonstrate this algorithm on a multitarget passive sensor track formation and maintenance problem, consisting of multiple time samples of line of sight (LOS) measurements originating from multiple (S = 7) synchronized high frequency direction finding sensors. Another significance of this work is that the m-best SD assignment algorithm (in a sliding window mode) provides for an efficient implementation of a Multiple Hypothesis Tracking (MHT) algorithm by obviating the need for a brute force enumeration of an exponential number of joint hypotheses.

关键词： multisensor-multitarget tracking data association m-best assignment SD assignment

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Application of adaptive joint time-frequency processing to ISAR image enhancement and Doppler feature extraction for targets with rotating parts

Application of adaptive joint time-frequency processing to I...

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conference on Radar processing, Technology, and Applications III

作者： Wang, Y Ling, H Chen, VC Univ Texas Dept Elect & Comp Engn Austin TX 78712 USA

ISBN: (纸本)0819429171

A new methodology based on adaptive joint time-frequency processing is proposed to separate the interference due to fast rotating parts from the original ISAR image of the target. The technique entails adaptively searching for the linear chirp bases which best represent the time-frequency behavior of the signal and fully parameterizing the signal with these basis functions. The signal components due to the fast rotating part are considered to be associated with those chirp bases having large displacement and slope parameters, while the signal components due to the target body motion are represented by those chirp bases having relatively small displacement and slope parameters. By sorting these chirp bases according to their slopes and displacements, the scattering due to the fast rotating part can be separated from that due to the target body. Consequently, the image artifacts overlapping with the original image of the target can be removed and a clean ISAR image can be produced. Furthermore, useful rotation rate information contained in the Doppler signal can be extracted. Successful applications of the algorithm to numerically simulated and measurement data show the robustness of the algorithm.

关键词： ISAR imaging Doppler smearing fast rotating parts adaptive joint time-frequency processing

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ISAR imaging of targets with fast rotating parts using adaptive joint time-frequency processing 5

ISAR imaging of targets with fast rotating parts using adapt...

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SPIE conference on Wavelet Applications V

作者： Wang, Y Ling, H Chen, VC Univ Texas Dept Elect & Comp Engn Austin TX 78712 USA

ISBN: (纸本)081942840X

Based on the adaptive joint time-frequency processing techniques, a new methodology is proposed in this paper to separate the interference due to fast rotating parts from the original ISAR image of the target. The technique entails adaptively searching for the linear chirp bases which best represent the time-frequency behavior of the signal and fully parameterizing the signal with these basis functions. The signal components due to the fast rotating part are considered to be associated with those chirp bases having large displacement and slope parameters, while the signal components due to the target body motion are represented by those chirp bases which have relatively small displacement and slope parameters. By sorting these chirp bases according to their slopes and displacements, the scattering due to the fast rotating part can be separated from that due to the target body. Consequently, the image artifacts overlapping with the original image of the target can be well removed and a clean ISAR image can be produced. Successful applications of the algorithm to numerically simulated and measurement data show the robustness of the algorithm.

关键词： ISAR imaging Doppler smearing fast rotating parts adaptive joint time-frequency processing

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Quasi best weighted order statistics CFAR detector

International Conference on Signal Processing Proceedings, I...

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International conference on signal processing Proceedings, ICSP 1998年 1卷 145-147页

作者： Meng, Xiangwei He, You Naval Aeronautical Engineering Acad Yantai City China

In order to make the detector perform robustly, an intuitive solution can be obtained by censoring the clutter observations from large and small deriations. In recent studies, censoring techniques have been implemented using order statistics (OS) and trimmed mean (TM) methods. In order to utilizing censored data, we present a quasi best weighted (QBW) order statistics method resulting in an improved detection performance while censoring outliers. Under the assumption of Swerling II target and Rayleigh distributed clutter, the analytic expressions of Pfa, Pd and ADT are derived. The analytic results show that an improved performance over TM is obtained both in homogeneous background and in clutter edges situation, and QBW exhibits robustness in multiple interfering targets environment. In specific cases, QBW reduces to CMLD.

关键词： signal detection

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Range and azimuth estimation using raw data in DSP-based radar system

Range and azimuth estimation using raw data in DSP-based rad...

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International conference on Microwaves, Radar and Wireless Communications

作者： M. Nalecz K. Kulpa Warsaw University of Technology Warsaw Poland

In the paper a problem of estimation of target position in a modern DSP-based radar system is considered. The processes of target detection and estimation are separated. Raw radar data supplied to the detection block are buffered in large RAM memory and then partially post-processed by the estimation block in areas nearby detected targets. Such an approach allows for more elaborate estimation algorithms than using joint detection and estimation. We have adopted curve-fitting procedures for both azimuth and range estimation. Simulation results prove good performance even for small signal to noise ratios.

关键词： Azimuth Read-write memory Random access memory signal processing algorithms Digital signal processing Radar detection Object detection Curve fitting Scalability Digital signal processing chips

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Quasi Best Weighted Order Statistics CFAR Detector

Quasi Best Weighted Order Statistics CFAR Detector

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1998 Fourth International conference signal processing

作者： MENG Xiangwei HE You Department of Electronic Engineering Naval Aeronautical Engineering Academy

In order to make the detector perform robustly,an intuitive solution can be obtained by censoring the clutter observations from large and small *** recent studies,censoring techniques have been implemented using order statistics（OS） and trimmed mean（TM） *** order to ultilizing censored data,we present a quasi best weighted（QBW） order statistics method resulting in an improved detection performance while censoring *** the assumption of Swerling II target and Rayleigh distributed clutter,the analytic expressions of P,P and ADT are derived. The analytic results show that an improved performance over TM is obtained both in homogeneous background and in clutter edges situation,and QBW exhibits robustness in multiple interfering targets *** specific cases,QBW reduces to CMLD.

关键词： Radar Detection CFAR Order Statistics

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A small target tracking technique with data fusion of distributed sensor net

A small target tracking technique with data fusion of distri...

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conference on signal and data processing of small targets 1997

作者： Cheng, HW Sun, ZK Liu, Q Chen, YG Institute of Electronic Engineering National Univ. of Defense Technology Changsha Hunan 410073 China

ISBN: (纸本)0819425850

small targets defined in the paper are low-RCS targets or weak infrared emitting targets which are very difficult to track by a single sensor (a radar or an IRST) because the measurements gained by the sensor are usually unsuccessive. Although a single sensor can only observe the target in unsuccessive way, the sensor mt may sometimes track the target continuously by data fusion of the fractional trajectories or hits of the target from all sensors of the netted system. Typically, data fusion method of a distributed sensor net is track-to-track fusion that requires continuous track-level data(space vector estimates and their covariance matrices) from sensors in the net. For the case of small targets this condition can not be satisfied. In the paper, we derive a method to fuse the data of the small target from the system. The method includes data association and tracking. Special attention is pay to track initiation with Hough Transform for the association algorithm. Test and results are also given in the paper.

关键词： small target tracking data fusion distributed sensor net

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Monopulse tracking of two unresolved Rayleigh targets

Monopulse tracking of two unresolved Rayleigh targets

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conference on signal and data processing of small targets 1997

作者： Blair, WD Watson, GA BrandtPearce, M Naval Surface Warfare Ctr. (United States) Univ. of Virginia (United States)

ISBN: (纸本)0819425850

When two targets are closely-spaced with respect to the resolution of a radar, the measurements of the two targets will be merged when the target echoes are not resolved in angle, range, or radial velocity (i.e., Doppler processing). Monopulse processing is considered for Direction-Of-Arrival (DOA) estimation of two unresolved Rayleigh targets with known relative Radar Cross Section (RCS). The probability distribution of the complex monopulse ratio is developed for two unresolved Rayleigh targets. The Fisher information matrix and Cramer Rao bounds are developed for the DOA estimation of two unresolved Rayleigh targets using a standard monopulse radar. When the two Rayleigh targets are separated by more than one-half of the radar beamwidth, DOA estimation is accomplished for each target by treating the other target as interference. When the two targets are separated by less than one-half of a beamwidth, the antenna boresight is pointed between the two targets, and the mean of the in-phase (i.e.,the real part) monopulse ratio and the variance of the in-phase and quadrature monopulse ratios are utilized to estimate the DOAs of the two targets. Simulation results that illustrate performance of the DOA estimators are given along with a simple tracking example.

关键词： radar signal processing target tracking sensor resolution

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