A robust fusion estimation with unknown cross-covariance in distributed systems

Abstract An efficient robust fusion estimation (RFE) for distributed fusion system without knowledge of the cross-covariances of sensor estimation errors is suggested. With the hypothesis that the object lying in the intersection of some ellipsoids related to sensor estimations, the robust fusion es...

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Bibliographic Details
Main Authors: Duzhi Wu, Aiping Hu
Format: Article
Language:English
Published: SpringerOpen 2019-09-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Online Access:http://link.springer.com/article/10.1186/s13634-019-0640-6
Description
Summary:Abstract An efficient robust fusion estimation (RFE) for distributed fusion system without knowledge of the cross-covariances of sensor estimation errors is suggested. With the hypothesis that the object lying in the intersection of some ellipsoids related to sensor estimations, the robust fusion estimation is designed to be a minimax problem, which is solved by proposing a novel relaxation strategy. Some properties of the RFE are discussed, and numerical simulations are also present to compare the tracking performance of RFE with that of the centralized fusion and CI method. The numerical examples show that the average tracking performance of RFE is slightly better than that of the CI method, and the performance degradation of RFE is acceptable compared with the centralized fusion.
ISSN:1687-6180