RUNWAY DETECTING AND TRACKING OF AN UNMANNED AERIAL LANDING VEHICLE BASED ON VISION

摘要

When a monocular vision-based unmanned aerial vehicle (UAV) is flown to the final approach to intercept the glide slope, the position and orientation of the airport runway in the image must be detected accurately for a host of suitable procedures to be followed. The approaching marking on the runway is showed as some white spots of high intensity as well as the complicated backgrounds. In our paper, we use pin-hole perspective principle, the constraint condition of the rectangle in inertial space, the front shot constraint condition of the target, as well as the clustering algorithm to identify the runway and output its position and orientation in image space. The results of the experiments show that by this algorithm, even from a place far away from the runway with marks being unclear, effective detection is possible. After all, single-frame detection errors exist, so we extend the basic runway-detection algorithm to the runway tracking. A full filtering strategy using particle filter can guard against potentially catastrophic results and improve the detection rate. Apparently, the whole algorithm of our paper can be treated as a special vision sensor for landing equipment of UAV.