dc.contributor.authorQu, Xiaomei
dc.date.accessioned2013-07-25T01:30:00Z
dc.date.available2013-07-25T01:30:00Z
dc.date.copyright2012en_US
dc.date.issued2012
dc.identifier.citationQu, X. (2012). A mini-max robust estimation fusion in distributed multi-sensor target tracking systems. 2012 International Conference on Computational Problem-Solving (ICCP).en_US
dc.identifier.urihttp://hdl.handle.net/10220/12136
dc.description.abstractThis 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.en_US
dc.language.isoenen_US
dc.rights© 2012 IEEE.en_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering
dc.titleA mini-max robust estimation fusion in distributed multi-sensor target tracking systemsen_US
dc.typeConference Paper
dc.contributor.conferenceInternational Conference on Computational Problem-Solving (2012 : Leshan, China)en_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.identifier.doihttp://dx.doi.org/10.1109/ICCPS.2012.6384212


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