We proposed and are currently developing a multichannel radar to provide small unmanned aerial vehicles (uavs) with knowledge regarding the relative position and velocities of nearby objects (both…

This federal contract award to the University of Kansas Center for Research Inc. involves the development of a multichannel radar system to provide small unmanned aerial vehicles (UAVs) with collision avoidance capabilities. The $795,102.50 Cooperative Agreement, funded by the National Aeronautics and Space Administration (NASA), aims to create a lightweight, frequency-modulated, continuous-wave radar that can detect nearby objects and enable UAVs to alter their flight paths to avoid collisions. This radar system is intended to support the integration of UAVs into the National Airspace System by enhancing their sense-and-avoid capabilities. The contract does not have a set-aside designation. This award leverages the research and development expertise of the University of Kansas to advance technologies that can improve the safety and viability of commercial and industrial UAV operations.

We proposed and are currently developing a multichannel radar to provide small unmanned aerial vehicles (uavs) with knowledge regarding the relative position and velocities of nearby objects (both mobile and fixed) that may pose a collision risk. With this knowledge, the uavs onboard flight director may alter course to avoid collisions and thus reduce its potential hazards to society. By increasing the safety of autonomous UAV operations, various commercial and industrial flight services may become economically viable. A low-power, multichannel, lightweight, frequency-modulated, continuous-wave (fmcw) radar was developed with NASA learn phase i funding and flight tested onboard a manned cessna aircraft to validate the concept. The radar incorporates programmable, radar-ready integrated circuits from analog devices (developed for the automotive collision-avoidance market) thus enabling significant miniaturization. With phase II funding a multicore processor will be added allowing a miniaturized version of this radar to be automated and fly aboard a 50-LB. UAV. The flight director, autopilot, and a vision system (added to complement the radar) will also hosted by the multicore processor optimized for real-time processing. The radar can detect targets with radar cross sections as small as one square meter (characteristic of a human or a small aircraft) at ranges up about 800 m with a 10 HZ update rate. From digital signal processing accurate real-time range and radial velocity estimates can be derived. An array of low-gain receive antennas enables determination of each objects azimuth and elevation position relative to the UAV by comparing the signals received phases (i.e., no antenna scanning is required). Operating in the 2.45 GHZ ISM band, the radar will employ cognitive processes to dynamically assign its operating frequency in quiet portions of this band. An option to tradeoff sensitivity for latency as a function of range providing data on nearby targets with higher update rates (with reduced sensitivity) while data on more distant targets is reported with reduced updated rates to boost the sensitivity by using longer dwell times consistent with the needs of the flight director. Flight tests aboard manned surrogate aircraft as well as free-flying uavs are planned during this 12-month project. The successful completion this proejct will offer several benefits to the UAV community. The proposed airborne radar represents a technology building block for assessing the capabilities and limitations of this class of sense-and-avoid radar across a range of airspace environments, a critical step for integration of uavs into the national airspace system (NAS). The nextgen concept of airspace operations (to be operational in the 2025 time frame) will involve self-separation concepts for manned and unmanned aircraft that the proposed radar could support, both for inter-aircraft and aircraft-terrain spacings. Successful deployment of a multicore processor to execute multiple time-critical simultaneously will demonstrate the viability of such high-performance computing systems in this environment. With an integrated flight director and autopilot, the capability provided by this system will permit the UAV researcher and developer to focus on mission-specific goals (e.g., optimizing flight-control models) when conducting flight tests.