SIMPLIFIED PARTICLE PHD FILTER FOR MULTIPLE-TARGET TRACKING: ALGORITHM AND ARCHITECTURE

In this paper, we propose a simplified particle probability hypothesis density (PHD) filter and its hardware implementation for multiple-target tracking (MTT). In the proposed algorithm, the update step of particle PHD filter is simplified and the time-varying number of measurements is arranged in combination series/parallel mode. This may result in fixed hardware architecture and therefore present a convenient hardware implementation of particle PHD filter. Simulation results indicate that for the MTT problems, this proposed simplified algorithm shows similar performance with the standard particle PHD filter but has faster processing rate. Experiment study shows that the proposed simplified algorithm can be efficiently implemented in hardware and can effectively solve the MTT problems.