In-flight performance analysis of a non-cooperative radar-based sense and avoid system

This paper discusses the outcome of flight experiments relevant to non-cooperative sense and avoid that were carried out in the framework of a collaboration between the Italian Aerospace Research Center and the University of Naples '‘Federico II’’. Within the project, aimed at full autonomy for medium/large Unmanned Aircraft Systems, an integrated radar/electro-optical system configuration was adopted, and real-time data fusion/automatic decision-making algorithms were developed to estimate intruders’ motion, and generate and follow proper escape trajectories. All the systems were designed to guarantee collision avoidance without any dependence on the command and control link. The hardware/software sense and avoid system was installed onboard an optionally piloted flying laboratory of Very Light Aircraft category, and a single intruder aircraft of the same class was considered for avoidance experiments. In particular, the paper focuses on the results from radar-based autonomous avoidance flight tests. Performance is analyzed in terms of situational awareness before and during the maneuver, and effectiveness in performing safe avoidance maneuvers while generating smooth commands and minimizing the deviation from nominal trajectory. Statistics relevant to several encounters show that in spite of a small number of valid sensor measurements, the tracking algorithm is able to keep a satisfying level of situational awareness, thus enabling safe avoidance. However, the limits deriving from coarse radar accuracy, low scan rate, and interaction between mechanical scanning and aircraft flight dynamics are also pointed out. While these limits did not impact avoidance safety in the considered tests due to the favorable operating environment in terms of time to collision, radar detection range, and ownship maneuverability, they confirm the need of improved sensing concepts in more challenging avoidance scenarios, such as adoption of radar/electro-optical data fusion and electronic scanning technologies.