Aircraft Approach Angle Estimation: Vision Based Landing

In the past decade, there have been great advancements in the application of computer vision to UAV's and associated aerial visual surveillance. For example, [6] demonstrated how a high precision ego-motion estimate of a camera can be incorporated to achieve video annotations and insertion to reference imagery. An algorithm for estimating the approach angle of an Unmanned Aerial Vehicle (UAV) is presented. The Algorithm involves extracting the horizon and the focus-of-expansion (from opticflow employing robust statistics). Experimental results are presented to validate this approach. Many UAV implementations incorporate a Global Satellite Positioning System (GPS) or Inertial Navigation System (INS) for aircraft position and displacement measurements. The feasibility of using vision alone to extract aircraft position is demonstrated in [3]. By matching the real-time video feed with a set of reference IRS images or a Digital Evaluation Map (DEM), absolute position was estimated.