A Probability Hypothesis Density Filter and Data Association Based Algorithm for Multitarget Tracking with Pulse Doppler Radar

To solve the problem of multitarget tracking with the Pulse Doppler (PD) radar in clutters, a novel method based on Probability Hypothesis Density Filter (PHDF) and Data Association (DA) for joint range ambiguity resolving and multitarget tracking with range ambiguity is proposed. The method sets the radar work with a set of Pulse Repetition Frequencies (PRFs) alternately, and obtains the extended measurements set by making multiple hypotheses with the ambiguous measurement generated by the radar. Then, filters with extended measurement set with the PHDF by making full use of the advantages of which that it can eliminate clutters effectively and avoid the association between target and measurement. Finally it implements a track-estimate data association with the outputs of the PHDF and provides target tracks. Simulation results demonstrate that the proposed method can estimate the number of target as well as individual target state, and succeeds in multitarget tracking with range ambiguity in clutters.