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The symmetric measurement equation approach to multiple target tracking is revisited using unscented Kalman and particle filters. The characteristics and performance of these filters are compared to the original symmetric measurement equation implementation relying upon an extended Kalman filter. Counterintuitive results are presented and explained for two(More)
Ronald Mahler's Probability Hypothesis Density (PHD) provides a promising framework for the passive coherent location of targets observed via multiple bistatic radar measurements. We consider tracking targets using only range measurements from a simple non-directional receiver that exploits non-cooperative FM radio transmitters as its " illuminators of(More)
The past decade has witnessed rapid development in accurate modeling of 3D targets and multiple sensor fusion in automatic target recognition (ATR), however, the scientiic study for quantifying non-target objects in a cluttered scene has made very limited progress, due to its enormous diiculties. In this paper, we study two important themes in ATR: I)(More)
We study noise artifacts in phase retrieval based on minimization of an information-theoretic discrepancy measure called Csiszár's I-divergence. We specifically focus on adding Poisson noise to either the autocorrelation of the true image (as in astronomical imaging through turbulence) or the squared Fourier magnitudes of the true image (as in x-ray(More)
Our pattern theoretic approach to the automated understanding of complex scenes brings the traditionally separate endeavors of detection, tracking, and recognition together into a uniied jump-diiusion process. Concentrating on an air-to-ground scenario, we postulate data likelihood models for a low-resolution, wide eld-of-view millimeter wave radar (for(More)
This paper examines metrics for measuring clutter eeectiveness on model-based automatic target recognition systems with FLIR sensors. The measure for clutter eeectiveness proposed is the diierence of two Kullback-Leibler distances between the idealized approximate probabilistic models without clutter and the real model containing clutter. We establish that(More)
Investigators interested in model order estimation have tended to divide themselves into widely separated camps; this survey of the contributions of Schwarz, Wallace, Rissanen, and their coworkers attempts to build bridges between the various viewpoints, illuminating connections which may have previously gone unnoticed and clarifying misconceptions which(More)
Ronald Mahler's Probability Hypothesis Density (PHD) provides a promising framework for the passive coherent location of targets observed via multiple bistatic radar measurements. We apply a particle filter implementation of the Bayesian PHD filter to target tracking using both range and Doppler measurements from a simple non-directional receiver that(More)
— The symmetric measurement equation approach to multiple target tracking is revisited using un-scented Kalman and particle filters. The characteristics and performance of these filters are compared to the original symmetric measurement equation implementation relying upon an extended Kalman filter. Counter-intuitive results are presented and explained for(More)