Distributed optimal one-step-lag estimation for out-of-sequence track fusion based on pseudo-measurement for multi-sensor system
基于伪测量的分布式最优单步延迟航迹融合估计

The local processing of out-of-sequence data is crucial to the operation quality of the distributed multisensor system. We treat the estimation in local nodes as the pseudo-measurement, and convert the distributed estimation to a two-level centralized fusion estimation. By combining the pseudo-measurement-distributed fusion estimation algorithm obtained above with the optimal one-step-lag out-of-sequence measurement(OOSM) filter, we develop the optimal onestep-lag out-of-sequence track(OOST) estimation algorithm. This algorithm can be applied to the fusion estimation of out-of-sequence data of tracks with optimal estimation performances.