Flight Test of a Radar-Based Tracking System for UAS Sense and Avoid

Presented here is an analysis of an extensive flight campaign aimed at characterizing peculiarities, advantages, and limitations of an obstacle detection and tracking system based on a pulse radar. The hardware and software prototypical sensing system was installed onboard an optionally piloted flying laboratory from the very light aircraft (VLA) category. Test flights with a single intruder aircraft of the same class were carried out to demonstrate autonomous noncooperative unmanned aerial system (UAS) collision avoidance capability and to evaluate the level of achievable situational awareness. First, the adopted architecture and the developed tracking algorithm are presented. Subsequently, flight data gathered in various relative flight geometries, covering chasing flights and quasi-frontal encounters, are analyzed in terms of radar performance, including detection range and range and angle measurement accuracies. The analysis describes the impact of ground echoes and navigation uncertainties, system tracking reliability, and achievable accuracy in estimation of relative position and velocity. On the basis of Global Positioning System (GPS) data gathered simultaneously with obstacle detection flight experiments, a detailed error analysis is conducted. Special emphasis is given to the validation of proposed methodology to separate between intruder and ground echoes, which is a critical aspect for light aircraft due to their limited radar cross sections (RCS) and flight altitudes. In conclusion the radar demonstrates its potential to attain adequate situational awareness, however the limits of single sensor tracking are also pointed out. Above all the negative impact of poor angular accuracy on missed detection and false alarm rates is pointed out.

[1]  Giancarmine Fasano,et al.  Integrated Obstacle Detection System based on Radar and Optical Sensors , 2010 .

[2]  Giancarmine Fasano,et al.  An Innovative Procedure for Calibration of Strapdown Electro-Optical Sensors Onboard Unmanned Air Vehicles , 2010, Sensors.

[3]  Omid Shakernia,et al.  Sense and Avoid (SAA) Flight Test and Lessons Learned , 2007 .

[4]  Kim B. Housewright,et al.  Derivation and evaluation of improved tracking filter for use in dense multitarget environments , 1974, IEEE Trans. Inf. Theory.

[5]  Jim Cistone.  Next century aerospace traffic management: The sky is no longer the limit , 2004 .

[6]  A.D. Zeitlin,et al.  Safety of Cooperative Collision Avoidance for Unmanned Aircraft , 2006, 2006 ieee/aiaa 25TH Digital Avionics Systems Conference.

[7]  Michael Deschenes,et al.  Development of a Sense and Avoid System , 2005 .

[8]  Tarak Gandhi,et al.  Detection of obstacles in the flight path of an aircraft , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[9]  Alex Fung,et al.  Multi-Sensor Data Integration for Autonomous Sense and Avoid , 2011 .

[10]  Samuel S. Blackman,et al.  Multiple-Target Tracking with Radar Applications , 1986 .

[11]  B. Korn,et al.  UAS in civil airspace: Demonstrating “sense and avoid” capabilities in flight trials , 2008, 2008 IEEE/AIAA 27th Digital Avionics Systems Conference.

[12]  David Gibbs.  Sense and Avoid Flight Demonstration , 2007 .

[13]  A. Moccia,et al.  A hardware in the loop facility for testing multisensor sense and avoid systems , 2009, 2009 IEEE/AIAA 28th Digital Avionics Systems Conference.

[14]  Sanjiv Singh,et al.  Passive, Long-Range Detection of Aircraft: Towards a Field Deployable Sense and Avoid System , 2009, FSR.

[15]  Domenico Accardo,et al.  Laboratory Test Facility for Simulating a Sense and Avoid Flight System , 2010 .

[16]  Patrick Garrec,et al.  Sense and avoid radar using Data Fusion with other sensors , 2011, 2011 Aerospace Conference.

[17]  Cheryl Yuhas,et al.  Earth Observations and the Role of UAVs: A Capabilities Assessment , 2006 .

[18]  Giancarmine Fasano,et al.  DEVELOPMENT AND TEST OF AN INTEGRATED SENSOR SYSTEM FOR AUTONOMOUS COLLISION AVOIDANCE , 2008 .

[19]  Jason J. Ford,et al.  Vision-based detection and tracking of aerial targets for UAV collision avoidance , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[20]  Giancarmine Fasano,et al.  Multi-Sensor-Based Fully Autonomous Non-Cooperative Collision Avoidance System for Unmanned Air Vehicles , 2008, J. Aerosp. Comput. Inf. Commun..