Highest probability data association and particle filtering for target tracking in clutter

Abstract

There proposed a new method of data association called highest probability data association (HPDA) combined with particle filtering and applied to passive sonar tracking in clutter. The HPDA method evaluated the probabilities of one-to-one assignments of measurement-to-track. All of the bearing measurements at the present sampling instance were lined up in the order of signal strength. The measurement with the highest probability was selected to be target-originated and the measurement was used for probabilistic weight update of particle filtering. The proposed HPDA algorithm can be easily extended to multi-target tracking problems. It can be used to avoid track coalescence phenomenon that prevails when several tracks move very close together.