Integrated Bayesian Clutter Estimation with JIPDA/MHT Trackers

Based on Poisson point processes, multitarget multi-Bernoulli processes, and set calculus, a Bayesian method is presented to estimate the nonhomogeneous clutter background while simultaneously tracking multiple targets. A major feature of the proposed approach is the seamless integration of clutter estimation with standard multitarget tracking algorithms like the multiple hypothesis tracker (MHT) and the joint integrated probabilistic data association (JIPDA) tracker by exploiting the association events and their probabilities constructed and calculated in standard multitarget tracking algorithms.