Research on Collaborative Navigation Algorithm of Factor Graph Based on BP

Huaijian Li, Jin Jiang*, Tao Wang

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

The standard particle filter (PF) algorithm has the problem of particle diversity loss caused by particle impoverishment and resampling, which makes the particle sample unable to accurately represent the true distribution of the state probability density function. In this paper, a particle sampling method based on Sigma points and a method of classifying particles and recalculating weights based on weights are proposed. Based on the improvement of these two parts, an improved BP cooperative navigation algorithm is proposed. The simulation results show that the navigation error estimated by the improved BP algorithm proposed in this chapter is smaller than that of the traditional NBP algorithm, and the effectiveness of the improved algorithm is verified.

源语言英语
主期刊名2024 6th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2024
出版商Institute of Electrical and Electronics Engineers Inc.
229-234
页数6
ISBN(电子版)9798350377842
DOI
出版状态已出版 - 2024
活动6th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2024 - Hangzhou, 中国
期限: 16 8月 202418 8月 2024

出版系列

姓名2024 6th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2024

会议

会议6th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2024
国家/地区中国
Hangzhou
时期16/08/2418/08/24

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引用此

Li, H., Jiang, J., & Wang, T. (2024). Research on Collaborative Navigation Algorithm of Factor Graph Based on BP. 在 2024 6th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2024 (页码 229-234). (2024 6th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2024). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DOCS63458.2024.10704362