Unmanned aircraft systems (UAS) are poised to transform modern life. However, there remain barriers to increased adoption. NASA has recognized that current autonomous systems have poor perception of the environment. This is a problem because detecting and avoiding non-cooperative aircraft in all weather is a key requirement for operation in the National Airspace (NAS).
During Phase I of this SBIR, KMB Telematics performed a feasibility study to determine whether it was possible to design a small, lightweight radar that would allow small drones (<55 lbs.) see other small drones, as well as larger targets. This solves an unmet need in the market, as there is currently no DAA radar with low enough size, weight, power, and cost (SWAP-C) to be mounted on battery-operated small UAS (sUAS). This is a critical issue because sUAS use cases represent the majority of the total addressable market (TAM) currently imagined for the commercial drone market. To solve this problem, the approach taken was to evaluate KMB’s proprietary imaging radar technology which was originally developed over 18 months of IRAD for the autonomous vehicle (AV) market. The Phase I R&D concluded that it was possible to adapt KMB imaging radar to the UAS use case, resulting in a substantial improvement over the current state of the art.
Our goal in this SBIR Phase II is to develop a SWAP-C DAA radar system, which allows the sUAS to safely fly in the NAS. This would enable operators of these drones to obtain Part 107 waivers and hence directly enable BVLOS commercial drone operations. More specifically, we propose to build a prototype DAA radar whose key characteristics are:
This sensor would allow the Integrated Aviation System Program to use smaller, cheaper UAS to perform research like the development of detect and avoid algorithms, sensor fusion, pattern recognition, and decision-making algorithms. This sensor could be used to continue NASA's UAS Traffic Management (UTM) work to enable small UAS operation beyond visual line of sight. This sensor could be used as a collision avoidance sensor by the Resilient Autonomy project.
This sensor would enable commercial package delivery UAS operators to fly beyond visual line of sight, as well as electric vertical take-off and landing (eVTOL) and manned aircraft collision avoidance applications.