Optimal Asynchronous Recursive Track Fusion with Global Feedback
带有信息反馈的最优异步递推航迹融合算法

Asynchronous fusion is common in processing multisensor data fusion problems and the asynchronous track fusion which adopts distributed fusion architecture has an extensive application among asynchronous fusion. In current asynchronous track fusion algorithms, the global feedback is mostly not established from fusion center to local sensors, so the local estimate can not be improved by the global estimate. Another defect among these algorithms is the correlation between the local prediction track estimate errors is ignored; thereby the accuracy of global estimate is reduced. In order to improve the estimate precision of the fusion system, the correlation is considered and the global feedback is introduced in this paper, accordingly a novel optimal asynchronous track fusion algorithm with feedback is presented. Compared with the current algorithm without global feedback and correlation, the proposed method can improve the estimate performance of the fusion system. The algorithm analysis and simulations both show the advantages of the novel algorithm.