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Nonlinear Filtering With Sample-Based Approximation Under Constrained Communication: Progress, Insights and Trends
Weihao Song; Zidong Wang; Zhongkui Li; Jianan Wang; Qing-Long Han
Source PublicationIEEE/CAA Journal of Automatica Sinica
ISSN2329-9266
2024
Volume11Issue:7Pages:1539-1556
AbstractThe nonlinear filtering problem has enduringly been an active research topic in both academia and industry due to its ever-growing theoretical importance and practical significance. The main objective of nonlinear filtering is to infer the states of a nonlinear dynamical system of interest based on the available noisy measurements. In recent years, the advance of network communication technology has not only popularized the networked systems with apparent advantages in terms of installation, cost and maintenance, but also brought about a series of challenges to the design of nonlinear filtering algorithms, among which the communication constraint has been recognized as a dominating concern. In this context, a great number of investigations have been launched towards the networked nonlinear filtering problem with communication constraints, and many sample-based nonlinear filters have been developed to deal with the highly nonlinear and/or non-Gaussian scenarios. The aim of this paper is to provide a timely survey about the recent advances on the sample-based networked nonlinear filtering problem from the perspective of communication constraints. More specifically, we first review three important families of sample-based filtering methods known as the unscented Kalman filter, particle filter, and maximum correntropy filter. Then, the latest developments are surveyed with stress on the topics regarding incomplete/imperfect information, limited resources and cyber security. Finally, several challenges and open problems are highlighted to shed some lights on the possible trends of future research in this realm.
KeywordCommunication constraints maximum correntropy filter networked nonlinear filtering particle filter sample-based approximation unscented Kalman filter
DOI10.1109/JAS.2023.123588
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/57300
Collection学术期刊_IEEE/CAA Journal of Automatica Sinica
Recommended Citation
GB/T 7714
Weihao Song,Zidong Wang,Zhongkui Li,et al. Nonlinear Filtering With Sample-Based Approximation Under Constrained Communication: Progress, Insights and Trends[J]. IEEE/CAA Journal of Automatica Sinica,2024,11(7):1539-1556.
APA Weihao Song,Zidong Wang,Zhongkui Li,Jianan Wang,&Qing-Long Han.(2024).Nonlinear Filtering With Sample-Based Approximation Under Constrained Communication: Progress, Insights and Trends.IEEE/CAA Journal of Automatica Sinica,11(7),1539-1556.
MLA Weihao Song,et al."Nonlinear Filtering With Sample-Based Approximation Under Constrained Communication: Progress, Insights and Trends".IEEE/CAA Journal of Automatica Sinica 11.7(2024):1539-1556.
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