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Reliable fusion estimation over sensor networks with outliers and energy constraints
Author(s) -
Xie Meiling,
Ding Derui,
Dong Hongli,
Han QingLong,
Wei Guoliang
Publication year - 2019
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.4706
Subject(s) - outlier , estimator , computer science , reliability (semiconductor) , covariance matrix , covariance , energy (signal processing) , network packet , mathematical optimization , sensor fusion , state (computer science) , algorithm , mathematics , artificial intelligence , statistics , computer network , power (physics) , physics , quantum mechanics
Summary This paper provides a reliable fusion scheme over sensor networks subject to abnormal measurements and energy constraints. Two kinds of channels are employed to implement the information transmission in order to extend the lifetime. Specifically, the one has the merit of high reliability by sacrificing energy cost and the other reduces the energy cost but could result in packet loss. For the addressed problem, a χ 2 detection in local state estimator is first designed to remove abnormal measurements, which could come from outliers or a malicious modification by attackers. Then, a new strategy is developed to compensate the lost local estimation transmitted by low‐reliable channels. Furthermore, by view of matrix operation and probability theory, a set of recursive formulas are developed to calculate desired error covariance matrices of local state estimation, compensated state estimation as well as fusion estimation. The optimal fusion weights are obtained analytically and the advantage of fusion estimation is disclosed by resorting to these covariance matrices. Finally, a numerical example is used to illustrate the effectiveness of the proposed method.