Efficient particle filters for tracking manoeuvring targets in clutter

In this paper, we propose an on-line Monte Carlo (MC) filtering algorithm to perform optimal state estimation for Jump Markov Linear Systems (JMLS). The approach taken is loosely based on the bootstrap filter which, whilst being a powerful general algorithm in its original form, does not make the most of the structure of JMLS. The proposed algorithm exploits this structure and is demonstrated to provide a performance improvement over the IMM-PDA for tracking manoeuvring targets in clutter.