A Joint Probabilistic Data Association Smoothing Algorithm for Multitarget Tracking

Abstract

This paper is concerned with the development of a joint probabilistic data association based fixed-lag smoothing algorithm for the recursive tracking of multiple targets in cluttered environment. The improvement in accuracy of track estimation achieved by introducing a time lag of one or two sampling periods for a radar tracking problem are also demonstrated by using simulation experiment.