基于MEMS-INS/GNSS组合导航抗差自适应Kalman滤波算法

Robust Adaptive Kalman Filtering Algorithm for Integrated Navigation Based on MEMS-INS/GNSS

标准的Kalman滤波器在组合导航领域得到了广泛的应用,然而在实际运动过程中,载体的运动模型是复杂多变的,无法准确掌握系统的动态特性。针对高动态环境下载体动态复杂多变特性带来的动力学模型难以精确构建问题,以及卫星跟踪环路信号易受扰动导致的观测信息出现异常粗差问题,设计了一种基于MEMS-INS/GNSS组合导航系统抗差自适应Kalman滤波算法,研究了优化自适应因子的求解方法。通过跑车试验证明了该算法能够有效地抑制误差发散,提供更加精确的导航定位结果,更好地控制观测信息误差以及动力学模型异常所带来的影响。

The standard Kalman filter has been widely used in the field of integrated navigation. However, in the actual process of motion, the motion model of the carrier is complex and changeable, and the dynamic characteristics of the system can not be accurately mastered. In the case of high dynamic environment, the dynamic model caused by the dynamic and complex characteristics of the downloading body is difficult to be constructed accurately, and the abnormal information of the observation information caused by the disturbance of the satellite tracking loop signals is abnormal. In this paper, a robust adaptive Kalman filtering algorithm for integrated navigation system based on MEMS/GNSS is designed. The experiment shows that the algorithm can effectively suppress the error divergence, provide, more and the influence of the anomaly of the dynamic model.