Airborne Tracking Based on Particle Filtering for UAS Sense and Avoid

Airborne Obstacle Tracking has a significant role onboard Unmanned Aerial Systems. The primary function of this system is to detect and track location of obstacles in the flight path in an accurate and timely manner. Advanced filtering methodologies, such as Particle Filters, can provide very accurate estimates of the target state when the aircraft trajectories are described by non-linear dynamic models and linear filters could cause a loss of accuracy. The paper focuses on algorithm and test results from an Obstacle Tracking system based on Particle Filter. A customized version of the Particle Filter has been developed by exploiting data acquired during flight tests by means of a Very Light Aircraft in the framework of a research project carried out by the Italian Aerospace Research Centre and the University of Naples “Federico II”. First of all, a brief description of the hardware/software architecture installed onboard the aircraft is presented. Then, the Particle Filter performance is analyzed in order to point out the impact of non-linear filters on the estimate of the Distance at Closest Point of Approach