Research on Collaborative Navigation Algorithm of Factor Graph Based on BP

Huaijian Li, Jin Jiang*, Tao Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publication2024 6th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages229-234
Number of pages6
ISBN (Electronic)9798350377842
DOIs
Publication statusPublished - 2024
Event6th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2024 - Hangzhou, China
Duration: 16 Aug 202418 Aug 2024

Publication series

Name2024 6th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2024

Conference

Conference6th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2024
Country/TerritoryChina
CityHangzhou
Period16/08/2418/08/24

Keywords

  • belief propagation algorithm
  • cooperative navigation
  • factor graph

Fingerprint

Dive into the research topics of 'Research on Collaborative Navigation Algorithm of Factor Graph Based on BP'. Together they form a unique fingerprint.

Cite this