新型自适应滤波算法在惯导/双星组合中的应用  

An Adaptive Filtering Algorithm and its Application in INS/DS Integrated Navigation System

作　　者：赵龙[1] 李铁军[1] 陈璞[2] 

机构地区：[1]北京航空航天大学控制一体化技术国家级重点实验室,北京100191 [2]西安飞行自动控制研究所,陕西西安710065

出　　处：《全球定位系统》2010年第6期1-6,共6页Gnss World of China

基　　金：航空基础科学基金(20090818004;20100851018)

摘　　要：在系统模型误差和噪声统计特性未知时,为防止滤波发散和提高系统的实时性,提出了一种模糊自适应Kalman滤波算法。该算法利用滤波异常判据获得一个滤波状态因子,进而利用模糊推理系统在线调整量测噪声协方差阵的值,使滤波实现自适应。将该算法应用到惯导/双星组合导航系统中,并和简化的Sage-Husa自适应滤波算法进行仿真比较。仿真结果表明:在滤波精度相当的情况下,该算法简化了运算,提高了实时性。In order to avoid the divergence and improve the real-time property of the filter,an Adaptive Kalman Filtering（AKF） algorithm is presented,which obtained a factor of filtering state by using the criterion of filtering anomalies,and the measurement noise covariance matrix is confirmed by using this factor.AFK is realized by changing the measurement noise covariance according to the state of the filtering.AKF is applied to the INS/DS（Inertial Navigation System/Double-star System） integrated navigation system,and compared it with the conventional Kalman filtering and the simplified Sage-Husa filtering,the simulation results showed that the AKF simplified the computation and improved the real-time property with the same accuracy of simplified Sage-Husa filtering.

关 键 词：组合导航系统 自适应滤波 KALMAN滤波 模糊推理 

分 类 号：V666.1[航空宇航科学技术]