基于GPS/偏振/地磁信息的SINS AUKF-ASVSF空中对准方法

AUKF-ASVSF in-flight alignment method of SINS based on the GPS/polarization/geomagnetic information

针对SINS/GPS/偏振/地磁组合导航系统对准期间滤波精度与鲁棒性不足的问题,提出了一种基于自适应无迹卡尔曼滤波-平滑变结构滤波器(AUKF-ASVSF)的空中对准方法。首先,建立SINS/GPS/偏振/地磁组合导航系统的误差模型,利用GPS、偏振光、地磁场信息提高SINS对准精度。其次,基于新息序列自适应地调整SVSF算法中平滑边界层的宽度和UKF算法中的量测噪声协方差矩阵。最后,根据平滑边界层的宽度大小计算自适应AUKF-ASVSF滤波器的增益。仿真结果表明,当系统受到外界干扰时,AUKF-ASVSF比UKF和自适应UKF的抗干扰能力和鲁棒性更强;在系统量测噪声未知的情况下,AUKF-ASVSF比UKF-SVSF的滤波性能更好,其失准角的对准时间减少了25.9%,对准精度提高了11.2%。

For the low filtering accuracy and robustness of SINS/GPS/polarization/geomagnetic integrated navigation system,an in-flight alignment method based on adaptive unscented Kalman filter-adaptive smooth variable structure filter(AUKF-ASVSF)integrated filter is addressed.Firstly,the error model of SINS/GPS/polarization/geomagnetic integrated navigation system is established to improve the accuracy of the navigation system by using the information of GPS,polarized light and geomagnetic field.Secondly,according to the innovation sequence,the width of the smooth boundary layer in SVSF algorithm and the measurement noise covariance matrix in UKF algorithm are adaptively adjusted.Finally,the gain of AUKF-ASVSF is calculated based on the width of the smooth boundary layer.Simulation results show that AUKF-ASVSF has stronger anti-interference ability and robustness than UKF and adaptive UKF when the system is subjected to external interference.In addition,the AUKF-ASVSF algorithm has a higher estimation accuracy and faster convergence rate than the traditional UKF-SVSF algorithm when the system measurement noise is unknown.The alignment time of the misalignment angles is reduced by 25.9%,and the alignment accuracy is increased by 11.2%.