关键词: 数据融合, 无序量测, 协方差加权, 多步延迟, 等效量测

Abstract: For Out Of Sequence Measurement（OOSM） problem in centralized multi-sensor target tracking system, an algorithm based on optimal fusion has been proposed, which is based on the idea of weighted covariance fusion and in the sense of the trace of fusion estimation error covariance matrix smallest. The algorithm aligns the OOSM to the time of the latest state estimate, and then it is fused with the latest state estimate using the covariance weighted method. In order to calculate the noise correlation of OOSM and the other measurements, equivalent measurement is introduced. Theoretical analysis and simulation show that the algorithm can effectively deal with the problem of OOSM multi-step delay. Its performance is almost optimal and decreases small as delay steps increases, and it has the same filtering accuracy with data saving method with the optimal performance and a small amount of additional storage.

Key words: data fusion, out-of-sequence-measurement, covariance weighting, multiple-step delay, equivalent measurement