In a centralized multi-sensor target tracking system, different time delays occur when measurements are sent from different sensors to the processing center. This causes the measurements from the same target to arrive at the center out of order, which leads to the problem of out-of-order measurement processing. Inspired by the idea of \"centralized estimation reconstruction\" in distributed/track fusion theory, this paper proposes a new method for processing out-of-order measurements by combining forward prediction and equivalent measurement methods, which involves the decorrelation problem of state estimation. Finally, theoretical analysis and simulation experiments show that the algorithm is optimal for one-step delay, and when the process noise is small and the update rate of the system track is quite high, the performance degradation of the algorithm is very small.
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