An INS/Lidar Integrated Navigation Algorithm Based on Robust Kalman Filter

Xuhang Liu, Xiaoxiong Liu, Yue Yang, Weiguo Zhang

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

Abstract

Aiming at positioning requirement of UAV in GPS-denied Environment, an Inertial Navigation System (INS)/lidar algorithm based on Robust Kalman Filter (RKF) is proposed. The scan matching is selected to process the lidar information and obtain the position. After that, the INS/lidar model was constructed by using INS error model, in order to suppress the interference of measurement outliers on the navigation solution, RKF algorithm is introduced to reduce the influence of measurement outliers on filtering result. Experiment results indicate that the proposed algorithm can obtain precise position and attitude in GPS-denied environment, and suppress the influence of measurement outliers on filtering result.

Original languageEnglish
Title of host publicationAdvances in Guidance, Navigation and Control - Proceedings of 2020 International Conference on Guidance, Navigation and Control, ICGNC 2020
EditorsLiang Yan, Haibin Duan, Xiang Yu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages1027-1037
Number of pages11
ISBN (Print)9789811581540
DOIs
StatePublished - 2022
EventInternational Conference on Guidance, Navigation and Control, ICGNC 2020 - Tianjin, China
Duration: 23 Oct 202025 Oct 2020

Publication series

NameLecture Notes in Electrical Engineering
Volume644 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceInternational Conference on Guidance, Navigation and Control, ICGNC 2020
Country/TerritoryChina
CityTianjin
Period23/10/2025/10/20

Keywords

  • GPS-denied
  • Integrated navigation
  • Lidar
  • Robust Kalman filter
  • UAV

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