Nonlinear multiple model particle filters algorithm for tracking multiple targets

The paper addresses multiple targets tracking problem encountered in number of situations in signal and image processing. In this paper, we present an efficient filtering algorithm to perform accurate estimation in jump Markov nonlinear systems, which we aim to contribute in solving the problem of multiple targets tracking using bearings-only measurements. The idea of this algorithm consists of the combination between the multiple model approach and particle filtering methods, which give a nonlinear multiple model particle filters algorithm. This algorithm is used to estimate the trajectories of multiple targets assumed to be nonlinear, from their noisy bearings.