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

Li Liu, Aolei Yang, Xiaowei Tu, Minrui Fei, Wasif Naeem

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)
179 Downloads (Pure)

Abstract

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.
Original languageEnglish
Pages (from-to)54
Number of pages12
JournalNeurocomputing
Volume270
Issue numberDec 2017
Early online date16 Jun 2017
DOIs
Publication statusEarly online date - 16 Jun 2017

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