Adaptive Kalman Filtering in Networked Systems With Random Sensor Delays, Multiple Packet Dropouts and Missing Measurements

被引：140
|
作者：
Moayedi, Maryam [1 ]
Foo, Yung K. [2 ]
Soh, Yeng C. [1 ]
机构：
[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore
[2] LW Elect & Mech Engn Private Ltd, Singapore 608608, Singapore
来源：
IEEE TRANSACTIONS ON SIGNAL PROCESSING | 2010年 / 58卷 / 03期
关键词：
Kalman filtering; minimum mean-square error estimation; missing measurements; networked control systems (NCSs); packet dropouts; sensor delays; sensor networks (SNs); TIME STOCHASTIC-SYSTEMS;
D O I：
10.1109/TSP.2009.2037853
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, adaptive filtering schemes are proposed for state estimation in sensor networks and/or networked control systems with mixed uncertainties of random measurement delays, packet dropouts and missing measurements. That is, all three uncertainties in the measurement have certain probability of occurrence in the network. The filter gains can be derived by solving a set of recursive discrete-time Riccati equations. Examples are presented to demonstrate the applicability and performances of the proposed schemes.
引用
收藏
页码：1577 / 1588
页数：12
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