The Sensors Directorate of the Air Force Research Laboratory (AFRL), in conjunction with the Global Hawk
Systems Group, the J-UCAS System Program Office and contractor Defense Research Associates, Inc. (DRA) is
conducting an Advanced Technology Demonstration (ATD) of a sense-and-avoid capability with the potential to
satisfy the Federal Aviation Administration's (FAA) requirement for Unmanned Aircraft Systems (UAS) to
provide "an equivalent level of safety, comparable to see-and-avoid requirements for manned aircraft". This FAA
requirement must be satisfied for UAS operations within the national airspace. The Sense-and-Avoid, Phase I
(Man-in-the-Loop) and Phase II (Autonomous Maneuver) ATD demonstrated an on-board, wide field of regard,
multi-sensor visible imaging system operating in real time and capable of passively detecting approaching
aircraft, declaring potential collision threats in a timely manner and alerting the human pilot located in the
remote ground control station or autonomously maneuvered the aircraft. Intruder declaration data was collected
during the SAA I & II Advanced Technology Demonstration flights conducted during December 2006. A total of
27 collision scenario flights were conducted and analyzed. The average detection range was 6.3 NM and the mean
declaration range was 4.3 NM. The number of false alarms per engagement has been reduced to approximately 3
per engagement.
The Sensors Directorate at the Air Force Research Laboratory (AFRL) along with Defense Research Associates, Inc. (DRA) conducted a flight demonstration of technology that could potentially satisfy the Federal Aviation Administration's (FAA) requirement for Unmanned Aerial Vehicles (UAVs) to sense and avoid local air traffic sufficient to provide an "...equivalent level of safety, comparable to see-and-avoid requirements for manned aircraft". This FAA requirement must be satisfied for autonomous UAV operation within the national airspace. The real-time on-board system passively detects approaching aircraft, both cooperative and non-cooperative, using imaging sensors operating in the visible/near infrared band and a passive moving target indicator algorithm. Detection range requirements for RQ-4 and MQ-9 UAVs were determined based on analysis of flight geometries, avoidance maneuver timelines, system latencies and human pilot performance. Flight data and UAV operating parameters were provided by the system program offices, prime contractors, and flight-test personnel. Flight demonstrations were conducted using a surrogate UAV (Aero Commander) and an intruder aircraft (Beech Bonanza). The system demonstrated target detection ranges out to 3 nautical miles in nose-to-nose scenarios and marginal visual meteorological conditions. (VMC) This paper will describe the sense and avoid requirements definition process and the system concept (sensors, algorithms, processor, and flight rest results) that has demonstrated the potential to satisfy the FAA sense and avoid requirements.
The Passive Ground Moving Target Indication (PGMTI) program was a demonstration of the feasibility of autonomously detecting and tracking moving targets on the ground in real-time. Several scenarios were coordinated with ground vehicles and personnel so that the performance capabilities as well as any limitations of the system could be demonstrated. The objectives of the program were to demonstrate the following for the PGMTI system:
1.Process data in real time
*PMTD Algorithm
*High Pass Spatial Filter
*Tracker, Declaration Logic and Data Logger
2.Meet performance metrics
*Probability of Detection; PD >= 80%
*Probability of False Detection; PFD <= 0.02%
*Probability of Track; PT >= 90%
*Probability of False Track; PFT <= 0.01%
DRA used two different sensors to demonstrate the PGMTI performance; a near-IR and a mid-IR sensor. The near-IR system operated in real-time, and the mid-IR system was non-real-time. The approach to demonstrate the performance of the PGMTI system was to perform the following two tasks for each planned scenario containing the ground moving targets:
1)Collect the real-time processed data, from the near-IR sensor, which consists of the sensor data and a track file containing data on all tracks established by the system, and to analyze the results on the ground.
2)Collect raw data from the mid-IR sensor, post-process this data, and analyze results to determine performance. The analysis showed that all objectives were met provided there was at least 5% contrast between the ground moving target and its background. The PGMTI system concept demonstrated excellent performance and continued development is warranted.
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