Sequential hybrid consensus filtering with transmission delays and failures

This paper studies the distributed state estimation problem for nonlinear systems with random transmission delays and transmission failures, and proposes a novel sequential hybrid consensus filtering algorithm. The covariance intersection method is used to reach consensus over priors, and the consensus on measurements is used to fuse the innovation information, which makes the proposed algorithm robust to transmission failures. A compensation scheme is proposed when there are one-step transmission delays. The consensus weight of the delayed information is derived, and with the compensation term, the local estimation accuracy is improved. Rather than waiting for all information from neighboring nodes, the proposed algorithm is implemented sequentially once information from a neighboring node is received during the consensus step. The rigorous theoretical performance analysis is presented, and the proposed algorithm is tested numerically on a single target tracking problem and a distributed navigation of satellite cluster problem.