基于多传感器组合导航系统的自适应算法研究

Research on Adaptive Algorithm Based on Multi-sensor Combined Navigation System

针对组合导航系统中Kalman滤波算法的噪声方差阵异常或动态模型不准确而导致滤波精度下降的问题,提出了一种基于SINS/偏振光/GPS组合导航的自适应滤波算法。该算法首先通过对导航系统中不同导航器件冗余测量值进行差分序列统计分析,估计出近似真实的量测噪声统计特性,在此基础上根据新息协方差对系统噪声方差阵进行调整,从而实现自适应调节噪声方差阵来提高滤波精度。通过组合导航仿真实验,结果表明:该算法在系统动态模型不准确,量测噪声统计特性未知或者观测信息发生突变的情况下,可以有效改进滤波精度。

An adaptive filtering algorithm based on combined SINS/polarized light/GPS navigation is proposed for the problem of degradation of filtering accuracy due to abnormal noise variance array or inaccurate dynamic model of Kalman filtering algorithm in combined navigation system.The algorithm firstly estimates the statistical characteristics of the approximate real measurement noise by performing statistical analysis of the redundant measurements of different navigation devices in the navigation system,and then adjusts the noise variance array of the system based on the innovation variance matrix to achieve adaptive adjustment of the noise variance array to improve the filtering accuracy.Through the combined navigation simulation experiments,the results show that the algorithm can effectively improve the filtering accuracy when the dynamic model of the system is inaccurate,the statistical characteristics of the measurement noise are unknown or the observation information has changed abruptly.