Integrated probabilistic data association-finite resolution

This paper considers the problem of forming and maintaining tracks when measurements have both uncertain origin and are limited by finite resolution. A new version of the probabilistic data association algorithm is derived which takes account of the effects of sensor resolution. The Integrated Probabilistic Data Association-Finite Resolution (IPDA-FR) algorithm is presented for two situations, first when an accurate stationary clutter map is available and second when no a priori clutter information is available. Both cases result in a set of recursive formulae for data association and probability of track existence, thus enabling automatic track initiation and track maintenance. Simulation results comparing the performance of IPDA-FR with the IPDA and standard PDA algorithm are presented.