Optimization of Radar Networks for Airspace Surveillance in UAM and AAM Scenarios

The paper presents an optimization strategy aimed at determining the optimal locations and orientations of a set of ground-based radar sensors distributed around a region of interest providing airspace surveillance in Urban Air Mobility scenarios. Network geometry definition occurs through an optimization procedure which takes into account altogether maximization of airspace coverage and probability of detection, and minimization of the Cramer-Rao Bound. The approach tries to retrieve optimal locations starting from a large set of candidates which are automatically defined as a function of the area of interest and the scenario topology. Candidates' selection allows efficient a-priori elimination of non-feasible and non-appropriate candidate radar positions. Results of the proposed approach are tested on two different real world scenarios, achieving a coverage of 88.9 per cent for mountainous regions and of 99.2 per cent for almost flat terrain regions when a six elements radar network is considered. The full automation of the entire pipeline allows it to be easily applied to several surveillance scenarios and required performance levels.