Optimal track fusion with feedback for multiple asynchronous measurements
Gregory A. Watson, Theodore R. Rice, Ali T. Alouani · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2000
An analytic solution for the fusion of track estimates produced from two asynchronous measurements has been recently developed. The fusion process can occur at any time in the interval between the arrival of the second measurement of a fusion interval and the first measurement of the next fusion interval. The solution was stipulated to be a weighted sum of the previous fused estimate and the two individual estimates. The matrix weights are the unknowns for which a solution was formulated. This fusion process has properties that are identical to the Kalman filter. Even though this technique is a breakthrough, it is restricted to the fusion of only two estimates. The objective of this paper is to provide a numeric solution to this track fusion problem with an arbitrary number of asynchronous measurements. Simulation results will be employed to compare the performance of the Kalman filter and the track fusion algorithm in a multisensor environment.