Computation-Efficient Centralized Fusion Estimation with Packet Dropouts

被引：0
|
作者：
Zhang, Jun Yang Wen-An [1 ]
Chen, Bo [1 ]
机构：
[1] Zhejiang Univ Technol, Coll Informat Engn, Hangzhou 310023, Zhejiang, Peoples R China
来源：
2018 37TH CHINESE CONTROL CONFERENCE (CCC) | 2018年
基金：
中国国家自然科学基金;
关键词：
computation-efficient centralized fusion Kalman filter; networked multi-sensor fusion systems; packet dropouts; Riccati equation; SYSTEMS; SENSORS; DELAYS;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper is concerned with the computation-efficient centralized fusion Kalman filter for networked multi-sensor fusion systems with packet dropouts. Packet dropouts of each sensor channel is modeled by a Bemouli stochastic variable which is mutually uncorrelated and independent of the process noise and the measurement noises. The sum of the matrix weighted innovation of all the sensor measurements are used to update the one-step predicted state. Then, the computation-efficient centralized fusion Kalman filter is designed by solving a set of discrete-time Riccati equations. An illustrative example is used to show the effectiveness of the proposed algorithm.
引用
收藏
页码：6196 / 6200
页数：5
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