Sensors' optimal dimensionality compression matrix in estimation fusion

被引:45
|
作者
Song, EB [1 ]
Zhu, YM [1 ]
Zhou, E [1 ]
机构
[1] Sichuan Univ, Dept Math, Chengdu 610064, Peoples R China
基金
高等学校博士学科点专项科研基金; 中国国家自然科学基金;
关键词
multisensor estimation fusion; linear compression; minimum variance estimation;
D O I
10.1016/j.automatica.2005.07.011
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
When there exists the limitation of communication bandwidth between sensors and a fusion center, one needs to optimally pre-compress sensor outputs-sensor observations or estimates before sensors' transmission to obtain a constrained optimal estimation at the fusion center in terms of the linear minimum error variance criterion. This paper will give an analytic solution of the optimal linear dimensionality compression matrix for the single sensor case and analyze the existence of the optimal linear dimensionality compression matrix for the multisensor case, as well as how to implement a Gauss-Seidel algorithm to search for an optimal solution to linear dimensionality compression matrix. (c) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码:2131 / 2139
页数:9
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