Performance of the optimal nonlinear detector/tracker in clutter
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We propose an optimal nonlinear Bayesian algorithm for joint detection and tracking of targets that move randomly in cluttered environments. We review the derivation of the optimal Bayesian detector/tracker and present Monte Carlo simulations that benchmark the detection and tracking performances in both spatially correlated and non-Gaussian clutter.
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