Multi-sensor multi-target tracking with OOSM

Abstract

In multi-sensor multi-target tracking systems, the arrivals of "out-of-sequence" measurement (OOSM) can occur even in the absence of communication time delays. A optimal OOSM update algorithm are derived to solve one-lag as well as multi-lag OOSM update problems. In order to extend the OOSM update algorithms to multi-sensor multi-target tracking in clutter, the probabilistic data association (PDA) have been incorporated into the OOSM update algorithms with economic storage and efficient computation based on the nonsingularity assumption of some special matrices. The simulation results shows that PDA with the OOSM update algorithms have compatible RMS errors to the in-sequence PDA filter. © 2010 Springer-Verlag Berlin Heidelberg.