NDLI: A mini-max robust estimation fusion in distributed multi-sensor target tracking systems

Content Provider	IEEE Xplore Digital Library
Author	Xiaomei Qu
Copyright Year	2012
Description	Author affiliation: College of Computer Science and Technology, Southwest University for Nationalities, Chengdu, Sichuan, 610041, China (Xiaomei Qu)
Abstract	This paper proposed a mini-max fusion strategy in distributed multi-sensor system, which aims to minimize the worst-case squared estimation error when the cross-covariances between local sensors are unknown. The resulted estimation fusion is called as the Chebyshev fusion estimation (CFE) which is actually a non-linear combination of local estimations. We have also proofed that the CFE is better than any local estimator in the sense of minimize the worst-case squared estimation error. Moreover, a sensitive analysis about the choice of the support bound is carried out. The simulations illustrate that the proposed CFE is a robust fusion and more accurate than the previous covariance intersection (CI) estimation fusion method.
Starting Page	178
Ending Page	181
File Size	162255
Page Count	4
File Format	PDF
ISBN	9781467316965
e-ISBN	9781467316972
e-ISBN	9781467316958
DOI	10.1109/ICCPS.2012.6384212
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-19
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Estimation error Target tracking Sensitivity Distributed estimation fusion Chebyshev approximation Sensor fusion Robustness Robust fusion Mini-max strategy
Content Type	Text
Resource Type	Article

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