CI fusion filter for networked systems with uncertain observations, random delays and packets losses

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This paper is concerned with the covariance intersection (CI) fusion filtering problem for networked systems with multiple sensors subject to uncertain observations, random delays and losses of transmitted packets. Several groups of Bernoulli distributed random variables are used to depict the phenomena of uncertain observations, different random delays and losses of transmitted packets from different sensors to the fusion center. Using the innovation analysis approach, local optimal linear filter based on each sensor is presented in the linear minimum variance sense. Further, a distributed suboptimal fusion filter is obtained by using the CI fusion algorithm. It has the reduced computational burden since the computation of cross-covariance matrices is avoided. Moreover, it has better accuracy than any local filters. A simulation example verifies the effectiveness.