An efficient robust fusion estimation (RFE) for distributed fusion system without knowledge of the cross-covariances of sensor estimation errors is suggested. With the hypothesis that the object lying in the intersection of some ellipsoids related to sensor estimations, the robust fusion estimation is designed to be a minimax problem, which is solved by proposing a novel relaxation strategy. Some properties of the RFE are discussed, and numerical simulations are also present to compare the tracking performance of RFE with that of the centralized fusion and CI method. The numerical examples show that the average tracking performance of RFE is slightly better than that of the CI method, and the performance degradation of RFE is acceptable compared with the centralized fusion.

建议在不了解传感器估计误差的互协方差的情况下，为分布式融合系统提供一种有效的鲁棒融合估计（RFE）。假设对象位于与传感器估计有关的一些椭球的交点上，则将鲁棒融合估计设计为极小极大问题，这是通过提出一种新颖的松弛策略来解决的。讨论了RFE的一些属性，并提供了数值模拟，以比较RFE的跟踪性能与集中式融合和CI方法的跟踪性能。数值算例表明，RFE的平均跟踪性能比CI方法稍好，与集中式融合相比，RFE的性能下降是可以接受的。