Affiliation:
1. Department of Industrial Engineering, University of Naples Federico II, 80125 Naples, NA, Italy
Abstract
This paper provides an analytical framework to address the definition of sensing requirements in non-cooperative UAS sense and avoid. The generality of the approach makes it useful for the exploration of sensor design and selection trade-offs, for the definition of tailored and adaptive sensing strategies, and for the evaluation of the potential of given sensing architectures, also concerning their interface to airspace rules and traffic characteristics. The framework comprises a set of analytical relations covering the following technical aspects: field of view and surveillance rate requirements in azimuth and elevation; the link between sensing accuracy and closest point of approach estimates, expressed though approximated derivatives valid in near-collision conditions; the diverse (but interconnected) effects of sensing accuracy and detection range on the probabilities of missed and false conflict detections. A key idea consists of focusing on a specific target time to closest point of approach at obstacle declaration as the key driver for sensing system design and tuning, which allows accounting for the variability of conflict conditions within the aircraft field of regard. Numerical analyses complement the analytical developments to demonstrate their statistical consistency and to show quantitative examples of the variation of sensing performance as a function of the conflict geometry, as well as highlighting potential implications of the derived concepts. The developed framework can potentially be used to support holistic approaches and evaluations in different scenarios, including the very low-altitude urban airspace.
Subject
Artificial Intelligence,Computer Science Applications,Aerospace Engineering,Information Systems,Control and Systems Engineering
Reference28 articles.
1. Sense and avoid for unmanned aircraft systems;Fasano;IEEE Aerosp. Electron. Syst. Mag.,2016
2. Angelov, P. (2012). Sense and Avoid in UAS: Research and Applications, Wiley. [1st ed.]. Chapter 2.
3. Radar/electro-optical data fusion for non-cooperative UAS sense and avoid;Fasano;Aerosp. Sci. Technol.,2015
4. Proof-of-concept airborne sense and avoid system with ACAS-XU flight test;Kotegawa;IEEE Aerosp. Electron. Syst. Mag.,2016
5. (2023, August 23). UAS Traffic Management (UTM) Project Technical Interchange Meeting (TIM), Available online: https://nari.arc.nasa.gov/events/utm2021tim/.