Multiple Model Multiple Hypothesis Filter With Sojourn-Time-Dependent Semi-Markov Switching

This letter suggests a maneuvering target tracking algorithm using sojourn-time-dependent semi-Markov (STDM) model switching system on the basis of multiple model multiple hypothesis (M³H) filter. In the M³H filter, the target model sequences are constructed by a normal Markov switching system. A set of fixed model transition probabilities is used throughout the whole Markov process. In this letter, we propose the STDM-based M³H filter, which adapts the transition probability to the system sojourn time in the current model. This adaptation makes the target model sequence closer to the target natural behavior, and leads to the better tracking performance. Simulation results are presented to demonstrate the performance improvement after the STDM being introduced in the M³H filter.