基于视觉的无人作战飞机自主着陆导航方案

提出了基于视觉的无人作战飞机自主着陆组合导航方案.基于视觉的自主着陆 组合导航系统,可以根据视觉、惯导、高度表等传感器系统的特点,融合各机载传感器的测 量信息,在不依赖外部导航信息的情况下,得到无人作战飞机(UCAV)相对于跑道的着陆导 航信息.由于视觉信息在导航系统中的重要作用,对计算机视觉算法及其实时性进行了讨论 .对如何将视觉信息与惯导、高度表信息融合,构造多速率扩展Kalman滤波器进行了阐述. 通过自主开发的"UCAV自主着陆实时仿真验证平台"对该方案进行仿真,得到了满意的结果.

Vision-based autonomous landing integrated navigation scheme of unmanned combat aerial vehicles

A computer-vision-based integrated navigation scheme for autonomous landing of an unmanned combat air vehicle(UCAV) was presented.Based on this scheme,vision information with measurements of other on-board sensors,including inertial navigation system(INS) and altimeter system,could be fused according to the characteristics of these sensor systems.The scheme gave navigation information without the help of external navigation equipments with high measurement accuracy.Since computer vision played an important role in this navigation scheme,the vision algorisms were complicated processes and were discussed,so that the vision sensor measurement could be output with a delay in a low bandwidth.A multi-rate extended Kalman filter was constructed to fuse multi-rate information and gave high bandwidth attitude and pose estimations based on the output bandwidth of INS.The navigation scheme could run properly on the real-time simulation system for autonomous landing of the UCAV.