A Novel Particle Filter Based on One-Step Smoothing for Nonlinear System with Missing Measurements

被引：0
作者：
Yang, Zhenrong [1 ]
Zhang, Xing [1 ]
Xiao, Yushan [1 ]
机构：
[1] Guangxi Univ, Sch Math & Informat Sci, Nanning 530003, Peoples R China
来源：
2024 3RD CONFERENCE ON FULLY ACTUATED SYSTEM THEORY AND APPLICATIONS, FASTA 2024 | 2024年
关键词：
Particle Filter; Nonlinear Filter; One-Step Particle Smoother; Sequential Importance Sampling; Missing Measurement; STATE ESTIMATION; CONTROL DESIGN; DELAY; SUBJECT;
D O I：
10.1109/FASTA61401.2024.10595162
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 proposes a novel particle filter based on one-step smoothing for nonlinear systems with missing measurements. This filter iteratively employs a one-step smoother to improve the efficiency of importance sampling in bootstrap particle filtering through incorporating current measurement information into the apriori distribution. A simulation example of a target tracking model is given to illustrate that the proposed algorithm improves the sampling efficiency and estimation accuracy, which effectively limits the particle degradation phenomenon.
引用
收藏
页码：792 / 797
页数：6
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