论文信息 - Optimal update with out-of-sequence measurements for distributed filtering

Optimal update with out-of-sequence measurements for distributed filtering

This paper is concerned with optimal filtering in a distributed multiple sensor system with the so-called out-of-sequence measurements (OOSM). Based on BLUE (best linear unbiased estimation) fusion, we present two algorithms for updating with OOSM that are optimal for the information available at the time of update. Different minimum storage of information concerning the occurrence time of OOSMs are given for both algorithms. It is shown by analysis and simulation results that the two proposed algorithms are flexible and simple.

X. R. Li | Keshu Zhang

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