Performance of the optimal nonlinear detector/tracker in clutter

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.