Data fusion of association hypotheses in a distributed sensor network
Craig S. Agate, R.A. Iltis · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1994
A fusion algorithm is presented for a multisensor tracking system, in which the local trackers are N-scan data association filters. Previously, a fusion algorithm was given for the case where the local trackers are JPDA filters. Here, a fusion algorithm is presented for the more general case of local N-scan data association filters, of which the JPDA is a special case (N equals 0). The fusion equations consist of a simultaneous updating of the global hypothesis probabilities, and conditional global target state estimates. Two communication schemes between the local trackers and global processor are considered. A unidirectional communication scheme is examined in which the local trackers send the updated hypothesis probabilities and conditional target state estimates to the global processor; the local nodes then continue to track without knowledge of the global estimates. A bidirectional communication scheme is examined in which the local trackers send the updated hypothesis probabilities and conditional target state estimates to the global processor.