Topic
Moving target indication
About: Moving target indication is a research topic. Over the lifetime, 2653 publications have been published within this topic receiving 32435 citations.
Papers published on a yearly basis
Papers
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30 Dec 2003
TL;DR: Estimation accuracy, statistical consistency, and computational speed and storage are used to evaluate the performance of these estimators and the average mean square error (MSE) matrix, normalized estimation error squared (NEES), and normalized innovation squared (NIS) to analyze the accuracy and statistical consistency.
Abstract: Tracking using the ground moving target indicator (GMTI) sensor measurements plays an important role in situation awareness of the battlefield, surveillance, and precision tracking of ground moving targets. The GMTI sensor measurements range, azimuth, and range-rate are nonlinear functions of the target state. The extended Kalman filter (EKF) is widely used to solve the GMTI filtering problem. Since the GMTI measurement model is nonlinear, the use of an EKF is sub-optimal. The sub-optimality depends on the degree of nonlinearity of the measurement function and GMTI measurement error covariance. We can convert polar measurements range and azimuth to Cartesian measurements and approximately treat the range-rate as a linear function of the target velocity by considering the radar line-of-sight (RLOS) vector as a constant. This allows the use linear Kalman filter (KF) with linearized measurements in an approximate way. The unscented Kalman filter (UKF) and particle filter (PF) have been shown recently as robust alternate algorithms for a wide range of nonlinear estimation problems. This paper compares the performance of the KF with linearized measurements, EKF, iterated EKF (IEKF), UKF, and PF for the GMTI measurement filtering problem using a wide range of operating conditions. Estimation accuracy, statistical consistency, and computational speed and storage are used to evaluate the performance of these estimators. We use Monte-Carlo simulations and calculate the average mean square error (MSE) matrix, normalized estimation error squared (NEES), and normalized innovation squared (NIS) to analyze the accuracy and statistical consistency.© (2003) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
50 citations
TL;DR: This work addresses the nonstationary nature of the jammer multipath and its impact on clutter cancellation and target localization, and it is shown that the weight updating needed to track this interference will also modulate sidelobe signals.
Abstract: Airborne surveillance radars must detect and localize targets in diverse interference environments consisting of ground clutter, conventional jamming, and terrain scattered jammer multipath. Multidimensional adaptive filtering techniques have been proposed to adaptively cancel this interference. However, a detailed analysis that includes the effects of multipath nonstationarity has been elusive. This work addresses the nonstationary nature of the jammer multipath and its impact on clutter cancellation and target localization. It is shown that the weight updating needed to track this interference will also modulate sidelobe signals. At the very least, this complicates the localization of targets. At the worst, it also greatly complicates the rejection of clutter. Several techniques for improving cancellation of jammer multipath and clutter are proposed, including 1) weight vector interpolation, extrapolation, and updating; 2) filter architecture, constraint, and beamspace selection; 3) prefilters; 4) 3-D STAP architectures; and 5) multidimensional sidelobe target editing.
49 citations
TL;DR: The proposed clutter suppression and imaging approach is not only adapted for uniformly displaced phase center sampling but also for the nonuniform sampling cases.
Abstract: This paper describes a clutter suppression approach and the corresponding moving target imaging algorithm for a multichannel in azimuth high-resolution and wide-swath (MC-HRWS) synthetic aperture radar (SAR) system. Incorporated with digital beamforming processing, MC-HRWS SAR systems are able to suppress the Doppler ambiguities to allow for HRWS SAR imaging and null the clutter directions to suppress clutter for ground moving target indication. In this paper, the degrees of freedom in azimuth for the multichannel SAR systems are employed to implement clutter suppression. First, the clutter and moving target echoes are transformed into the range compression and azimuth chirp Fourier transform frequency domain, i.e., coarse-focused images formation, when the clutter echoes are with azimuth Doppler ambiguity. Considering that moving targets are sparse in the imaging scene and that there is a difference between clutter and a moving target in the spatial domain, a series of spatial domain filters are constructed to extract moving target echoes. Then, using an extracted moving target echo, two groups of signals are formed, and slant-range velocity of a moving target can be estimated based on baseband Doppler centroid estimation algorithm and multilook cross-correlation Doppler centroid ambiguity number resolving approach. After the linear range cell migration correction and azimuth focus processing, a well-focused moving target image can be obtained. In addition, the proposed clutter suppression and imaging approach is not only adapted for uniformly displaced phase center sampling but also for the nonuniform sampling cases. Some simulation experiments are taken to demonstrate our proposed algorithms. Finally, some real measured data results are presented to validate the theoretical investigations and the proposed approaches.
49 citations
TL;DR: Experimental results on measured SAR data are presented to demonstrate that this novel detector has wider range of detection velocity and lower false alarm probability.
Abstract: A novel approach to moving target detection is proposed for dual-channel SAR system. This approach is on the basis of eigen- decomposition of the sample covariance matrix and examines the statistic of the second eigenvalue and the Along-Track Interferometric (ATI) phase for ground moving target indication. Based on this statistic, a new Constant False Alarm Rate (CFAR) detector can be designed to solve the problem of GMTI. To detect slow moving targets more accurately, the second eigenvalue and the ATI phase pre- thresholds are implemented before a CFAR detector. Experimental results on measured SAR data are presented to demonstrate that this novel detector has wider range of detection velocity and lower false alarm probability.
48 citations
25 Jul 2005
TL;DR: This paper studies the tracking of a manoeuvring ground target on a road in a cluttered environment using map information to enhance the tracking quality and proposes an optimized projection technique of the estimated state in order to keep the target position and heading on the road.
Abstract: Tracking a ground target, based on GMTI radar measurements, is a challenging problem This is due particularly to the environment with a high density road traffic, terrain masks etc, and to the high manoeuverability of ground targets In this paper, the tracking of a manoeuvring ground target on a road in a cluttered environment is studied using map information to enhance the tracking quality Based on road segments positions, dynamic models under road constraints are built and an optimized projection technique of the estimated state is proposed in order to keep the target position and heading on the road Using this projection approach, a multiple model tracking algorithm is derived and its performances are studied The derived filter is an IMM (interacting multiple model) filter with a variable structure (VS-IMM) where the models set adapts sequentially according to the target position and to the road network configuration
48 citations