@inproceedings{f44d3662c7714af2b0220f446e4a060a,
title = "Distributed estimation fusion under unknown cross-correlation: An analytic center approach",
abstract = "We develop an analytic center approach to distributed estimation fusion when the cross-correlation of errors between local estimates is unknown. Based on a set-theoretic formulation of the problem, we seek an estimate that maximizes the complementary squared Mahalanobis {"}distance{"} between the local and the desired estimates in a logarithmic average form, and the optimal value turns out to be the analytic center. For our problem, we then prove that the analytic center is a convex combination of the local estimates. As such, our proposed analytic center covariance intersection (AC-CI) algorithm could be regarded as the covariance intersection (CI) algorithm with respect to a set-theoretic optimization criteria.",
keywords = "Analytic center, Convex combination, Covariance intersection, Decentralized network, Distributed fusion, Settheoretic estimation",
author = "Yimin Wang and Li, \{X. Rong\}",
year = "2010",
language = "英语",
isbn = "9780982443811",
series = "13th Conference on Information Fusion, Fusion 2010",
booktitle = "13th Conference on Information Fusion, Fusion 2010",
note = "13th Conference on Information Fusion, Fusion 2010 ; Conference date: 26-07-2010 Through 29-07-2010",
}