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 journalArticle

9 Citations (Scopus)
184 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
Number of pages12
JournalNeurocomputing
Early online date16 Jun 2017
DOIs
Publication statusEarly online date - 16 Jun 2017

Fingerprint Dive into the research topics of 'Distributed weighted fusion estimation for uncertain networked systems with transmission time-delay and cross-correlated noises'. Together they form a unique fingerprint.

  • Cite this