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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2023, Vol. 44 ›› Issue (6): 326817-326817.doi: 10.7527/S1000-6893.2022.26817

• Electronics and Electrical Engineering and Control • Previous Articles    

Predictive fifth-degree cubature Kalman filter method

Xiangdan ZHAO, Biao WANG, Zhisheng WANG(), Zhong YANG   

  1. College of Automation,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China
  • Received:2021-12-14 Revised:2021-12-31 Accepted:2022-03-21 Online:2022-05-09 Published:2022-04-12
  • Contact: Zhisheng WANG E-mail:wangzhisheng@nuaa.edu.cn
  • Supported by:
    Aeronautical Science Foundation of China(201928052006);Guizhou Provincial Science and Technology Projects([2020]2Y044)

Abstract:

A Predictive fifth-degree Cubature Kalman Filter (P5thCKF) method, which combines the Predictive Filter (PF) and the High-degree Cubature Kalman Filter (HCKF) is proposed for strongly nonlinear and non-Gaussian process noise systems. The PF is used to adjust the process noise and variance matrix in the system model in real time, and then the new model is put into the fifth-degree cubature Kalman filter framework to perform real-time recursive state estimation. The fifth-degree spherical simplex-radial rule is derived and is used to deal with spherical integration, and the generalized Gauss-Laguerre integral rule is used to deal with radial integration. The predictive filtering method is described, and the error adjustment amount of the model derived. The feasibility of the proposed method in strongly nonlinear and non-Gaussian process noise systems and its possible application to engineering practice are verified by two simulation experiments.

Key words: predictive filter, high-degree cubature Kalman filter, predictive fifth-degree cubature Kalman filter, fifth-degree spherical simplex rule, generalized Gauss-Laguerre integral rule

CLC Number: