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Acta Aeronautica et Astronautica Sinica ›› 2024, Vol. 45 ›› Issue (S1): 730782.doi: 10.7527/S1000-6893.2024.30782

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Robust filtering method for GNSS denied multi-source autonomous navigation

Zihan NAN1(), Dayu LIU2, Ming DONG3,4, Wenning LIANG5, Xuewei ZHAO1, Yilin MA1, Yao GUAN1   

  1. 1.Beijing Institute of Aerospace Control Devices,Beijing  100039,China
    2.Beijing Institute of Electrical Engineering,Beijing  100854,China
    3.Beijing Institute of Tracking and Telecommunications Technology,Beijing  100094,China
    4.Key Laboratory of Smart Earth,Beijing  100094,China
    5.China Aerospace Science and Technology Corporation,Beijing  100048,China
  • Received:2024-06-04 Revised:2024-06-24 Accepted:2024-07-04 Online:2024-12-25 Published:2024-07-11
  • Contact: Zihan NAN E-mail:nan657584155@163.com
  • Supported by:
    Aerospace Science and Technology Group Ninth Academy Science and Technology Committee Youth Fund(KJWQN202402)

Abstract:

To meet the requirements for high precision and high completeness in navigation and positioning of spacecraft in the environment of satellite rejection, a robust filtering method for multi-source autonomous navigation is proposed, which combines strapdown inertial navigation, satellite navigation and barometric altimeter. In a short period of time after measurement interruption, this method can accurately quantify the state space model in the tightly integrated navigation model through the filter estimation of the measurement uncertainty and nonlinear error model. Based on an in-depth analysis of the mechanism of the measurement anomaly vector’s action on the filter state output, a robust volume Kalman filter is proposed. The suppression effect of error covariance matrix is effectively improved, and the stability of filter and the estimation accuracy of state equation are improved in the process of multi-source autonomous navigation interpretation. The simulation results show that compared with the traditional volume Kalman filter, the method proposed can improve the accuracy of zero bias estimation of the gyroscope and accelerometer by about 31% and the positioning accuracy of autonomous navigation system by about 23.77%, and suppress the attitude angle error. This study can provide a reference for the terminal application of multi-source autonomous navigation system of the new generation of national integrated PNT system.

Key words: multi-source autonomous navigation, GNSS denied, nonlinearity robust filtering, tight integration, inertial navigation

CLC Number: