An Improved Adaptive Extended Kalman Filter Algorithm of SINS/GPS Loosely-Coupled Integrated Navigation System

  • Authors

    • Yuyan Wang
    • Xiuyun Meng
    • Jilu Liu
  • Strap-down inertial navigation system, Loosely-coupled integrated navigation, Extended Kalman filter, Adaptive extended Kalman filter.
  • The Kalman Filter algorithm usually cannot estimate noise statistics in real-time, in order to deal with this issue, a new kind of improved Adaptive Extended Kalman Filter algorithm is proposed. Based on residual sequence, this algorithm mainly improves the adaptive estimator of the filter algorithm, which can estimate measurement noise in real-time. Furthermore, this new filter algorithm is applied to a SINS/GPS loosely-coupled integrated navigation system, which can automatically adjust the covariance matrix of measurement noise as noise varies in the system. Finally, the original Extended Kalman Filter and the improved Adaptive Extended Kalman Filter are applied respectively to simulate for the SINS/GPS loosely-coupled model. Tests demonstrate that, the improved Adaptive Extended Kalman Filter reduces both position error and velocity error compared with the original Extended Kalman Filter.


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  • How to Cite

    Wang, Y., Meng, X., & Liu, J. (2018). An Improved Adaptive Extended Kalman Filter Algorithm of SINS/GPS Loosely-Coupled Integrated Navigation System. International Journal of Engineering & Technology, 7(4.27), 87-91.