首页|Multi-sensor multi-rate fusion estimation for networked systems: Advances and perspectives

Multi-sensor multi-rate fusion estimation for networked systems: Advances and perspectives

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  • NSTL
  • Elsevier
In industrial systems, the multi-rate sampling strategy has been widely used due to the advantage in balancing cost and performance as well as the psychical characteristics of the hardware. Accordingly, the analysis and synthesis problems of the multi-rate systems (MRSs) have received considerable research attentions owing to the significant engineering background. Among others, the state estimation problem, aims to estimate the system state based on the contaminated measurement signals, is one of the most important topics in the area of signal processing. In the past decades, plenty of research results have been obtained on the state estimation problems for MRSs. The intent of this survey is to provide a timely and systematic review with respect to the available state estimation algorithms for networked MRSs and the corresponding fusion methods. First, a general state-space model of the MRSs is given and the methods that transform the MRSs into single-rate ones are introduced. Then, the recent advances on the state estimation as well as fusion estimation problems for MRSs are discussed based on the performance indices used. Finally, some future research topics are given in the MRS state estimation problems.

Multi-rate systemsNetworked systemsH-infinity state estimationKalman filteringMulti-sensor information fusionINFINITY STATE ESTIMATIONRANDOM PARAMETER MATRICESUNSCENTED KALMAN FILTERMARKOV JUMP SYSTEMSSENSOR NETWORKSNEURAL-NETWORKSINFORMATION FUSIONCOMPLEX NETWORKSFAULT-DIAGNOSISDYNAMIC-SYSTEMS

Liu, Hongjian、Shen, Yuxuan、Wang, Zidong、Dong, Hongli

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Anhui Polytech Univ

Northeast Petr Univ

Brunel Univ London

2022

10.1016/j.inffus.2021.12.005

Information Fusion

Information Fusion

EISCI
ISSN：1566-2535
年,卷(期)：2022.82
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