自学习自适应INS／Doppler组合导航系统

本文通过引入文［１］提出的自学习适应Ｋａｌｍａｎ滤波，而将氢此组成的具有自学习功能的智能组合导航系统直接建立在噪声分布密度的异步自学习估计上，由于此时的ＬＡＫＦ在每次重复滤波实验后可离线异步地学习模型与量测噪声的统计特性，从而可有效地避免滤波发散现象并能确保实时性。文中结合某飞行器，对ＩＮＳ／Ｄｏｐｐｌｅｒ组合导航系统进行了仿真研究，所得结果十分满意。

INS/DOPPLER INTEGRATED NAVIGATION SYSTEM BASED ON LEARNING ADAPTIVE KALMAN FILTERING

In this paper the intelligent integrated navigation system with learning ablity,by using the learning adaptive Kalman filtering(LAKF) proposed by ref.1],is given,which is directly based on asynchronous learning estimation of noise is estimated offline after every filtering trial,the filtering divergence problem montioned above can be avoided bandly and the real-time filtering can also be guaranteed.To confirm its effectiveness,Ins/Doppler integrated navigation system of some Model of anti-ship missile is demosctrated by simulation,which gives very satisfactory results.