为研究GPS 故障或失效情况下无人机的备用导航技术，提出了基于自然地标的动态关键帧景象匹配视觉导航算法。首先，分析机载摄像机获取的实时图序列，自主寻找并描述特征明显的自然地标；然后，将包含自然地标的关键帧抽取出来，并与卫星数字基准图进行景象配准，计算其大地坐标作为辅助定位的依据。利用实时图帧间的相关性，将实时图当前帧与计算的动态关键帧图像进行“相对”景象匹配，进而实现当前帧在基准图上的精确定位。实验结果表明，该算法在提高配准概率的同时可大幅度提高景象匹配的实时性与精确性。

To study a backup navigation scheme for allowing temporally GPS faults or degradations, a natural-landmark scene matching visual navigation method based on dynamic keyframe is proposed for Unmanned Aerial Vehicle(UAV).Firstly, this method could autonomously describe and check featured natural landmarks by analyzing image sequence from on-board camera. After abstraction of keyframes including featured natural landmark, UAV will be located by the means of NLSM (Natural-Landmark Scene Matching) based on dynamic keyframe. Additionally, this navigation scheme adopts interframe scene matching algorithm in order to improve the navigation performance of accuracy, reliability and runtime. Experiments show that the backup navigation scheme proposed meets the requirements of navigation in complex and unknown environment for UAV.