Distributed weighted fusion estimation for uncertain networked systems with transmission time-delay and cross-correlated noises

[摘要] This paper investigates the state estimation issue for uncertain networked systems considering data transmission time-delay and cross-correlated noises. A distributed robust Kalman filtering-based perception and centralized fusion method is proposed to improve the estimation accuracy from perturbed measurement; consequently, reduce the amount of redundant information and alleviate the estimation burden. To describe the transmission time-delay and give rise to cross-correlated and state-dependent noises in the exchange measurement among neighbors, a weighted fusion reorganized innovation strategy is proposed to reduce the computational burden and suppress noise effect. Moreover, to obtain the optimal linear estimate, a fusion estimation approach is used for information collaboration by weighting the error cross-covariance matrices. Finally, an illustrative example is presented to demonstrate the effectiveness and robustness of the proposed method. (C) 2017 Elsevier B.V. All rights reserved.

[发布日期] 2017-12-27

[关键词] Distributed fusion estimation;Robust Kalman filtering;Uncertain networked systems;Transmission time-delay;Cross-correlated noises