Target tracking in an environment of nearly stationary and biased clutter

Abstract

The probabilistic data association (PDA) filter is considered for the tracking of a single target in an environment of randomly distributed clutters. Significant performance degradation occurs when the measurements originate from biased and nearly stationary clutters rather than a non-stationary nor non-biased one. We propose a modified PDA filter to achieve a successful tracking in such an environment. Simulation results demonstrate the feasibility of the proposed approach.