改进调节因子的GPS/SINS组合导航自适应滤波算法

GPS/SINS Integrated Navigation Adaptive Filtering Algorithm with Improved Adjustment Factor

针对传统卡尔曼滤波在复杂、高动态条件下滤波不稳定的问题,提出一种改进调节因子的Sage-Husa自适应滤波算法。该算法利用全球定位系统(GPS)三维速度信息对滤波异常判定条件中的调节因子进行实时优化,动态估计量测噪声的协方差阵,提高组合导航系统的自适应性。仿真结果表明,改进的Sage-Husa自适应滤波算法计算量明显降低,与传统卡尔曼滤波相比,能够保持较高的自适应性,明显改善定位精度。

Aiming at the problem of instability of traditional Kalman filter under complex and high dynamic conditions, a Sage-Husa adaptive filtering algorithm based on improved adjustment factor is proposed. The GPS three-dimensional speed information of this algorithm is used to optimize the adjustment factors in the filter abnormality judgment conditions in real time, the noise covariance matrix is dynamically estimated and the adaptability of the integrated navigation system is improved. The simulation results show that the improved Sage-Husa adaptive filtering algorithm has a significantly reduction of calculation amount. By comparing with the traditional Kalman filter, it can maintain higher adaptability and significantly improves the positioning precision.