Journal
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
Volume 46, Issue 9, Pages 1314-1325Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMC.2015.2487882
Keywords
Covariance intersection (CI); estimation fusion; minimax; robust fusion; semi-definite programming (SDP)
Funding
- State Key Program for Basic Research of China (973) [2013CB329405]
- National Natural Science Foundation (NNSF) of China [61403299]
- National Aeronautics and Space Administration/LEQSF-Phase3-06 [NNX13AD29A]
- Fundamental Research Funds for the Central Universities of China
- China Postdoctoral Science Foundation
- NNSF of China [61473197]
- NASA [475825, NNX13AD29A] Funding Source: Federal RePORTER
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This paper deals with distributed estimation fusion under unknown cross-covariance between errors of local estimates. We propose a formulation to restrict the set of possible cross-covariance matrices. The constraint in the formulation, named allowance of cross-covariance, provides a flexible way to utilize some prior information on cross-correlation in fusion methods. Then based on the allowance, an optimal robust fusion method is proposed in the minimax sense via semi-definite programming, and suboptimal fusion methods are also discussed to reduce the computational load. We analyze the properties of the proposed fusion methods and describe the relationships between our proposed fusion and some existing fusion methods. Numerical examples are given to illustrate their performance.
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