Fuzzy multisensor tracking system
Keith C. C. Chan, Vika Lee, Henry Leung · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1999
Many multi-sensor target tracking systems are developed under the assumptions that data association is too complex and computational requirement is too excessive for centralized fusion approaches to be practical. In addition, it is also assumed that the noise component is relatively small, that there are no missed detection and that the scanning interval is relatively short, etc. Many multi- sensor tracking systems have been shown to be able to perform effectively when tested with simulated data generated under these assumptions. However, careful investigation into the characteristics of several sets of real data reveals that these assumptions cannot always be made validly. In this paper we first describe the characteristics of a real multisensor tracking environment and explain why existing system may not be able to perform their task effectively in such environment. We then present a data fusion technique that can overcome some of the weakness of these systems. This technique consists of three steps: (1) estimation of synchronization error using an adaptive leaning approach; (2) adjustment of measured positions of a target in case of missed detection; and (3) prediction of the next target position using a fuzzy logic based algorithm. For performance evaluation, we tested the technique using different sets of real and simulated data. The results obtained are very satisfactory.