Clutter map information for data association and track initialization

This paper considers the problem of forming and maintaining tracks when measurements have both uncertain origin and are corrupted by additive sensor noise. The spatial clutter measurement density is assumed nonhomogenous and known. The IPDA-MAP algorithm provides a set of recursive formulae for data association and probability of target existence, thus enabling automatic track initiation, track maintenance, and track termination. New values for initial probability of target existence for IPDA-type algorithms are also derived. Simulation results compare the performance of IPDA-MAP with IPDA, IMM-PDA, IMM-PDA-MAP, EB-PDA and EB-PDA-MAP in a heavy and nonuniform clutter situation.