The future of UAS operations requires adequate and efficient Sense and Avoid strategies to ensure their safe and secure integration in both controlled and uncontrolled airspace. To make onboard implementation of these strategies feasible, research must focus on the development of sensing and tracking solutions, taking size, weight and power (SWaP) constraints as well as the challenging scenarios characterizing low altitude operations, into account. In this framework, visual cameras and low SWaP radars are among the most popular sensing choices. Hence, exploiting such sensing solutions, this paper proposes both single and multi-sensor detection and tracking approaches and compares their performance. Specifically, the developed techniques are tested on data retrieved during ground-to-air tests which involve a small UAV flying near collision geometries, starting from a range of about 550 m. Different tracking strategies are considered including standalone visual, standalone radar, and fused radar-visual. Concerning intruder detection, several visual-based techniques are investigated based on machine learning, morphological filtering and template matching. Radar detections are filtered and centroided with ad hoc algorithms. While in clear air conditions comparable declaration ranges, larger than 500 m, are provided by all the tested approaches, results show the advantages of using a fused strategy to attain sub-degree angular and angular rate tracking accuracy coupled with the highly accurate range and range rate, around 2 m and 1 m/s, respectively, typical of radars. Conflict detection performance is proven to also benefit from the use of a fused strategy in terms of smaller errors in the estimation of the distance at closest point of approach.

Ground-to-air experimental assessment of low SWaP radar-optical fusion strategies for low altitude Sense and Avoid

Federica Vitiello;Flavia Causa;Roberto Opromolla;Giancarmine Fasano
2022

Abstract

The future of UAS operations requires adequate and efficient Sense and Avoid strategies to ensure their safe and secure integration in both controlled and uncontrolled airspace. To make onboard implementation of these strategies feasible, research must focus on the development of sensing and tracking solutions, taking size, weight and power (SWaP) constraints as well as the challenging scenarios characterizing low altitude operations, into account. In this framework, visual cameras and low SWaP radars are among the most popular sensing choices. Hence, exploiting such sensing solutions, this paper proposes both single and multi-sensor detection and tracking approaches and compares their performance. Specifically, the developed techniques are tested on data retrieved during ground-to-air tests which involve a small UAV flying near collision geometries, starting from a range of about 550 m. Different tracking strategies are considered including standalone visual, standalone radar, and fused radar-visual. Concerning intruder detection, several visual-based techniques are investigated based on machine learning, morphological filtering and template matching. Radar detections are filtered and centroided with ad hoc algorithms. While in clear air conditions comparable declaration ranges, larger than 500 m, are provided by all the tested approaches, results show the advantages of using a fused strategy to attain sub-degree angular and angular rate tracking accuracy coupled with the highly accurate range and range rate, around 2 m and 1 m/s, respectively, typical of radars. Conflict detection performance is proven to also benefit from the use of a fused strategy in terms of smaller errors in the estimation of the distance at closest point of approach.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/902446
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