Integrated Navigation Filtering Algorithm in Complex Environments

Yifu Xiao, Yuhang Guo, Xingcheng Li

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

Abstract

Abstract-Though the GNSS/SINS has been widely used to provide high-precision and high-integrity services for many aeronautical applications, GNSS is vulnerable to interference because of its low signal strength, leading to the accuracy degradation of the integrated navigation. To solve this problem, an adaptive Kalman algorithm introduces adaptive factor to adjust filter parameters in real time, so as to ensure the accuracy of integrated navigation in complex environments. Firstly, the state equation and observation equation of the integrated navigation system are determined based on the error equation of SINS. Secondly, the state transition matrix and white noise of the system are equivalently discretized, and then the data is filtered by the adaptive Kalman filter algorithm. Finally, the simulation results show that the adaptive Kalman filter algorithm can improve the integrated navigation accuracy, especially in complex environments.

Original languageEnglish
Title of host publicationICVIP 2022 - Proceeding of the 2022 6th International Conference on Video and Image Processing
PublisherAssociation for Computing Machinery
Pages110-113
Number of pages4
ISBN (Electronic)9781450397568
DOIs
Publication statusPublished - 23 Dec 2022
Event6th International Conference on Video and Image Processing, ICVIP 2022 - Virtual, Online, China
Duration: 23 Dec 202226 Dec 2022

Publication series

NameACM International Conference Proceeding Series

Conference

Conference6th International Conference on Video and Image Processing, ICVIP 2022
Country/TerritoryChina
CityVirtual, Online
Period23/12/2226/12/22

Keywords

  • GNSS
  • Keywords: SINS
  • adaptive Kalman filter
  • complex environments

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