Distributed estimation based on information-based covariance intersection algorithms

被引：13
|
作者：
Mahmoud, Magdi S. [1 ]
机构：
[1] KFUPM, Dept Syst Engn, Dhahran 31261, Saudi Arabia
来源：
INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING | 2016年 / 30卷 / 05期
关键词：
information matrix filter; covariance intersection; weighted covariance; Kalman-like particle filter; industrial utility boiler; KALMAN-FILTER; MEASUREMENT FUSION; TRACK FUSION; SYSTEMS;
D O I：
10.1002/acs.2638
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A distributed estimation approach is developed in this paper using information matrix filter on a distributed tracking system in which multiple sensors are tracking the same target. The information matrix filter version is derived from covariance intersection, weighted covariance and Kalman-like particle filter, respectively. The steady performance of these filters is evaluated with different feedback strategies. The developed filters are then validated on an industrial utility boiler. Copyright (c) 2015 John Wiley & Sons, Ltd.
引用
收藏
页码：750 / 778
页数：29
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