Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/97810
Title: A mini-max robust estimation fusion in distributed multi-sensor target tracking systems
Authors: Qu, Xiaomei
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2012
Source: Qu, X. (2012). A mini-max robust estimation fusion in distributed multi-sensor target tracking systems. 2012 International Conference on Computational Problem-Solving (ICCP).
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.
URI: https://hdl.handle.net/10356/97810
http://hdl.handle.net/10220/12136
DOI: 10.1109/ICCPS.2012.6384212
Rights: © 2012 IEEE.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Conference Papers

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