Systems Engineering and Electronics ›› 2025, Vol. 47 ›› Issue (10): 3426-3432.doi: 10.12305/j.issn.1001-506X.2025.10.26

• Guidance, Navigation and Control • Previous Articles    

Fault diagnosis method of inertial sensor based on iterative double-model Kalman filter

Chenyuan ZHANG1,*, Haiying LIU1,2   

  1. 1. College of Astronautics,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China
    2. Nanjing Center for Applied Mathematics,Nanjing 211135,China
  • Received:2024-07-01 Online:2025-10-25 Published:2025-10-23
  • Contact: Chenyuan ZHANG

Abstract:

In response to the problem of inaccurate or even failed navigation information caused by inertial sensor faults, a fault diagnosis method based on improved Kalman filter is proposed. By introducing an iterative dual-model mechanism, the method enhances the performance of the extended Kalman filter (EKF) algorithm in handling nonlinear systems. Additionally, a kinematic model is adopted to reduce the sensitivity of the method to turbulence, thereby improving algorithm accuracy. Evaluation and comparison with traditional methods using simulation experiment data demonstrate that the proposed method has significant advantages in accuracy and robustness, effectively achieving the diagnosis of both abrupt and gradual faults in inertial sensors.

Key words: inertial navigation system (INS), sensor fault diagnosis, extended Kalman filter (EKF), fault detection and diagnosis

CLC Number: 

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