Image Processing Algorithm for Integrated Sense And Avoid Systems

To allow Unmanned Aircraft Systems (UAS) accessing National Airspace System (NAS) “Equivalent levels of safety” to the ones of human vision must be guaranteed. Therefore, an appropriate “Sense and Avoid” technology must be developed that is capable of detecting, tracking, and avoiding obstacles. The Department of Aerospace Engineering at University of Naples has been involved in a project funded by the Italian Aerospace Research Centre (CIRA) for the realization of a prototypical “Obstacle Detection & Identification” (ODID) System. It is installed onboard a Very Light Aircraft (VLA) and it is characterized by a hierarchical sensor configuration in which the radar is the main sensor while EO cameras are the auxiliary ones in order to increase accuracy and data rate so that anti-collision requirements are fulfilled. This paper focuses on the Image Processing algorithm for the panchromatic camera. Among the several techniques listed in literature the edge detection – labeling one resulted as the best compromise in terms of computational load, detection range, false alarm rate, miss detection rate and adaptability at different background luminosity conditions. Moreover it has been customized in order to allow for reliable operation in a wide range of flight and luminance configurations and it has been tested and run on a sequence of real images taken during flight tests. At the end, a table that summarizes those results is presented. Indeed, the output tracking measurements accuracy increases by an order of magnitude with respect to standalone radar one.