Enhanced AAM Surveillance Using Radar/Visual Distributed Sensing

The Advanced Air Mobility (AAM) landscape is evolving rapidly, with Uncrewed Aircraft Systems (UAS) technology advancing at a fast pace and regulation efforts being carried out worldwide to make room for autonomous flights in the civil airspace. Focusing on the surveillance aspect for AAM, strategies should be designed to cope with dense volumes of operations of small targets flying close to the ground in and around urban areas. In this framework, this paper proposes a distributed sensing solution to enhance AAM surveillance by exploiting different ground-based nodes equipped with radars and cameras. The strategy exploits a node-level fusion, where radar and camera measurements are used to estimate the position and velocity of targets, and a network-level fusion to merge such estimates enhancing accuracy and coverage. Aiming to go beyond the purely non-cooperative approach, the proposed strategy also foresees the possibility to include information shared by cooperative platforms, notifying the surrounding traffic about their instantaneous position. The proposed strategy is tested on data collected during experimental tests with up to five UAS, assumed cooperative, and three ground-based nodes. The results achieved show that the strategy enables confirmation of all cooperative targets with a coverage above 90 %. Other non-cooperative targets, such as birds, are also identified thus achieving a comprehensive picture of the monitored low-altitude airspace.