基于双因子抗差卡尔曼滤波在动态导航中的应用

Robust Estimate of Kalman Filtering based on Bifactor and its Application in Dynamic Navigation

针对动态导航卡尔曼(Kalman)滤波的异常扰动影响问题,根据观测量中的粗差对状态向量滤波值的影响规律,引入了双因子算法,导出基于预报残差的抗差卡尔曼滤波模型,该模型具有良好的抗差性,利用实测数据加模拟粗差进行验证,结果表明:抗差卡尔曼滤波可以很好的控制状态对滤波估值的影响,精度相对于标准卡尔曼滤波有明显的提高。

Basing on the rules that the outliers in the observation influence the state vectors, a robust Kalman filtering is applied in dynamic navigation to control the influences of outlying movement disturbances . In this paper, the bifactors were given to construct robust Kalman fitering model. By real data processing, it was shown that the robust Kalman filtering could resist the influence of the state disturbances, and the precision of the navigation is higher than that of the standard Kalman filtering.