Multisensor probabilistic multihypothesis tracking using dissimilar sensors
M.L. Krieg, Douglas Andrew Gray · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1997
A difficult problem in multisensor and multi-tracking is that of data association. A multitarget tracking algorithm, probabilistic multi-hypothesis tracking (PMHT), overcomes this problem by estimating the measurement-to-target assignments and the target states simultaneously. We have previously developed two multi-sensor variations of this algorithm, the multi-sensor PMHT and the general multi- sensor PMHT. In this paper, we apply the multi-sensor PMHT algorithm to non-simultaneous radar and optical real data, recorded from a testbed consisting of a radar and optical sensor. Its performance in a multi-target environment is compared to that of a multi-sensor variable update rate Kalman filter.