Systems Engineering and Electronics ›› 2022, Vol. 44 ›› Issue (6): 1994-2000.doi: 10.12305/j.issn.1001-506X.2022.06.27

• Guidance, Navigation and Control • Previous Articles     Next Articles

MEMS-INS/GNSS/VO integrated navigation method based on robust EKF

Wenhua LI, Lixin WANG*, Qiang SHEN, Can LI, Zongshou WU   

  1. College of Missile Engineering, Rocket Force Engineering University, Xi'an 710025, China
  • Received:2021-05-21 Online:2022-05-30 Published:2022-05-30
  • Contact: Lixin WANG

Abstract:

Aiming at the problem that traditional inertial navigation system/global navigation satellite system (INS/GNSS) integrated navigation is easy to be disturbed in complex environment and the observation is abnormal, which affects the navigation performance, an micro-electro-mechanical system (MEMS)-INS/GNSS/visual odometry (VO) integrated navigation method based on robust extended Kalman filter (EKF) is proposed. The fusion framework based on inertial navigation system (INS), global navigation satellite system (GNSS), and visual odometry (VO) is designed, and the navigation filtering model in the case of GNSS signal failure is given. The EKF and Huber method are combined to overcome the influence of noise interference on the navigation performance, so as to improve the robustness of the system. The simulation and the KITTI dataset verify that the integrated navigation method can still output high-precision navigation results when the GNSS signal fails, and can better overcome the influence of abnormal observations on the system, and has high reliability and robustness.

Key words: integrated navigation, extended Kalman filter (EKF), Huber method, visual odometry (VO), KITTI dataset

CLC Number: 

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