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A Unified Analytical Framework for Aircraft Separation Assurance and UAS Sense-and-Avoid

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Abstract

A novel analytical framework is presented addressing the need for a unified approach to aircraft separation assurance and Unmanned Aircraft System (UAS) Sense-and-Avoid (SAA). A brief review of the state-of-research in Separation Assurance and Collision Avoidance (SA&CA) technologies is included to highlight the benefits offered by the unified approach. In this approach, the employment of Adaptive Boolean Decision Logics (ABDL) allows automated selection of sensors/systems including passive and active Forward Looking Sensors (FLS), Traffic Collision Avoidance System (TCAS) and Automatic Dependent Surveillance – Broadcast (ADS-B). This system performance based selection approach supports trusted autonomous operations during all flight phases. After describing a SA&CA reference architecture, the mathematical models employed in the unified approach to compute the overall uncertainty volume in the airspace surrounding an intruder/obstacle are described. The algorithms support the translation of navigation errors affecting the host aircraft platform and tracking errors affecting the intruder sensor measurements to unified range and bearing uncertainty descriptors. Simulation case studies are presented to evaluate the performance of the unified approach on a representative UAS host platform and a number of intruder platforms in both cooperative and non-cooperative scenarios. The results confirm the validity of the proposed unified methodology in providing a pathway for certification of SA&CA systems. The significance of this approach is also discussed in the Communication, Navigation and Surveillance/Air Traffic Management and Avionics (CNS + A) context, with a focus on the evolving UAS Traffic Management (UTM) requirements.

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References

  1. Sabatini, R., Gardi, A., Ramasamy, S., Kistan, T., Marino, M., Blockley, R., Shyy, W.: Modern Avionics and ATM Systems for Green Operations, Encyclopedia of Aerospace Engineering. Wiley, Chichester (2015). https://doi.org/10.1002/9780470686652.eae1064

    Google Scholar 

  2. Kopardekar, P.H.: Unmanned aerial system (UAS) traffic management (UTM): enabling low-altitude airspace and UAS operations, NASA Technical Report (2014)

  3. Cook, S.P., Lacher, A.R., Maroney, D.R., Zeitlin, A.D.: UAS sense and avoid development - the challenges of technology, standards, and certification. In: 50th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition, Nashville, TN, USA (2012). https://doi.org/abs/10.2514/6.2012-959

  4. Dalamagkidis, K., Valavanis, K.P., Piegl, L.A.: On unmanned aircraft systems issues, challenges and operational restrictions preventing integration into the national airspace system. Prog. Aerosp. Sci. 44(7), 503–519 (2008). https://doi.org/10.1016/j.paerosci.2008.08.001

    Article  Google Scholar 

  5. The International Civil Aviation Organization (ICAO): Working Document for the Aviation System Block Upgrades - The Framework for Global Harmonization. Montreal, Canada (2013)

    Google Scholar 

  6. Amato, G.: EUROCAE WG-73 on Unmanned Aircraft Systems, ed: EUROCAE

  7. JAA: UAV TASK-FORCE, Final Report - A Concept for European Regulations for Civil Unmanned Aerial Vehicles (UAVs) (2004)

  8. Oztekinmet, A., Wever, R.: Development of a Regulatory Safety Baseline for UAS Sense and Avoid, Handbook of Unmanned Aerial Vehicles, pp. 1817–1839. Springer Verilag, Netherlands (2015)

    Book  Google Scholar 

  9. Yu, X., Zhang, Y.: Sense and avoid technologies with applications to unmanned aircraft systems: review and prospects. Prog. Aerosp. Sci. 74, 152–166 (2015)

    Article  Google Scholar 

  10. Pellebergs, J., Aeronautics, SAAB: The MIDCAS Project, SAAB Aeronautics (2012)

  11. Valavanis, K.P., George, J.V.: UAV Sense, Detect and Avoid: Introduction, Handbook of Unmanned Aerial Vehicles, pp. 1813–1816. Springer, Netherlands (2014)

    Google Scholar 

  12. Federal Aviation Administration: Pilot’s Role in Collision Avoidance, AC90-48C, Washington DC, USA (1983)

  13. DOT/FAA/CT-96-1: Human Factors Design Guide for Acquisition of Commercial-Off-the-Shelf subsystems, Non-Developmental Items, and Developmental Systems-Final Report and Guide (1996)

  14. FAA: Integration of Civil Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS) Roadmap, US Depatment of Transportation. Federal Aviation Administration, Washingston (2013)

    Google Scholar 

  15. Strohmeier, M., Schäfer, M., Lenders, V., Martinovic, I.: Realities and challenges of NextGen air traffic management: the case of ADS-B. IEEE Commun. Mag. 52(5), 111–118 (2014). https://doi.org/10.1109/MCOM.2014.6815901

    Article  Google Scholar 

  16. Melnyk, R., et al.: Sense and avoid requirements for unmanned aircraft systems using a target level of safety approach. Risk Anal. 34(10), 1894–1906 (2014)

    Article  Google Scholar 

  17. Mejias, L., Lai, J., Bruggemann, T.: Sensors for Missions. Handbook of Unmanned Aerial Vehicles (2015)

  18. Moses, A., Rutherford, M.J., Valavanis, K.P.: Scalable RADAR-Based Sense-and-Avoid System for Unmanned Aircraft, Handbook of Unmanned Aerial Vehicles, pp. 1895–1953. Springer, Berlin (2014)

    Google Scholar 

  19. Finn, A., Franklin, S.: Acoustic sense & avoid for UAV’s. In: IEEE Seventh International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) (2011)

  20. Wood, D.: Collision Avoidance System and Method Utilizing Variable Surveillance Envelope, U.S. Patent 6,804, 607 (2004)

  21. Smith, A., Coulter, D.M., Jones, C.S.: UAS collision encounter modeling and avoidance algorithm development for simulating collision avoidance. In: AIAA Modeling and Simulation Technologies Conference (2008)

  22. Mullins, M., Holman, M., Foerster, K., Kaabouch, N., Semke, W.: Dynamic separation thresholds for a small airborne sense and avoid system. In: AIAA Infotech@ Aerospace Conference, Boston, MA, USA, pp. 19–22 (2013)

  23. Smith, A.L., Harmon, F.G.: UAS Collision Avoidance Algorithm Minimizing Impact on Route Surveillance, AIAA Guidance Navigation, and Control Conferenc (2009)

  24. Euteneuer, E.A., Papageorgiou, G.: UAS insertion into commercial airspace: Europe and US standards perspective. In: 30th AIAA/IEEE Digital Avionics Systems Conference (DASC), pp. 5C5-1 (2011)

  25. De Crescenzio, F., Miranda, G., Persiani, F., Bombardi, T.: 3D obstacle avoidance strategies for UAS (Uninhabited Aerial System) mission planning and replanning. In: Proceedings of the 26th Congress of the International Council of the Aeronautical Sciences (2008)

  26. Marsh, R., Ogaard, K., Kary, M., Nordlie, J., Theisen, C.: Development of a mobile information display system for UAS operations in North Dakota. Int. J. Comput. Inf. Syst. Ind. Manag. Appl. 3, 435–443 (2011)

    Google Scholar 

  27. Hanlon, N., Cohen, K., Kivelevitch, E.: Sensor resource management to support UAS integration into the national airspace system. In: AIAA SciTech 2015 Conference (2015)

  28. Capitán, J., Merino, L., Ollero, A.: Coordination of multiple UAS for tracking under uncertainty. In: Proceedings of the 1st Workshop on Research, Education and Development on Unmanned Aerial Systems, RED-UAS (2011)

  29. Tadema, J., Theunissen, E., Kirk, K.M: Self separation support for UAS. In: American Institute of Aeronautics and Astronautics (AIAA) (2010)

  30. Upchurch, J., Munoz, C., Narkawicz, A., Chamberlain, J.: Chamberlain, Analysis of Well-Clear Boundary Models for the Integration of UAS in the NAS, Langley Research Center, Hampton, Virginia, TM–2014–218280, NASA (2014)

  31. CASA: CASR Part 101 - Unmanned, aircraft and rockets, CASA Regulations. Civil Aviation Safety Authority, Canberra (2016)

    Google Scholar 

  32. Cappello, F., Ramasamy, S., Sabatini, R.: A low-cost and high performance navigation system for small rpas applications. Aerosp. Sci. Technol. 58, 529–545 (2016). https://doi.org/10.1016/j.ast.2016.09.002

    Article  Google Scholar 

  33. Rodriguez, L., Sabatini, R., Ramasamy, S., Gardi, A.: A novel system for non-cooperative UAV sense-and-avoid. In: European Navigation Conference (ENC 2013), Vienna, Austria (2013)

  34. Betts, J. T.: Survey of numerical methods for trajectory optimization. J. Guid. Control. Dyn. 21, 193–207 (1998)

    Article  MATH  Google Scholar 

  35. Lai, C.K., Lone, M., Thomas, P., Whidborne, J., Cooke, A.: On-board trajectory generation for collision avoidance in unmanned aerial vehicles. In: Proceedings of the IEEE Aerospace Conference, pp. 1–14 (2011). https://doi.org/10.1109/AERO.2011.5747526

  36. Yu, T., Tang, J., Bai, L., Lao, S.: Collision avoidance for cooperative UAVs with rolling optimization algorithm based on predictive state space. Appl. Sci. 7(4), 329 (2017)

    Article  Google Scholar 

  37. Gardi, A., Sabatini, R., Ramasamy, S.: Multi-objective optimisation of aircraft flight trajectories in the ATM and avionics context. Prog. Aerosp. Sci. 83, 1–36 (2016). https://doi.org/10.1016/j.paerosci.2015.11.006

    Article  Google Scholar 

  38. Lai, C.K.: A Novel Collision Avoidance Logic for Unmanned Aerial Vehicles using Real-Time Trajectory Planning. PhD Thesis, Cranfield Univeristy, UK (2014)

  39. Ramasamy, S., Sabatini, R., Gardi, A.: LIDAR obstacle warning and avoidance system for unmanned aerial vehicle sense-and-avoid. Aerosp. Sci. Technol. 55, 344–358 (2016). https://doi.org/10.1016/j.ast.2016.05.020

    Article  Google Scholar 

  40. Sabatini, R., Moore, T., Hill, C.: Avionics based GNSS integrity augmentation for mission- and safety-critical applications. In: Paper presented at 25th International Technical Meeting of the Satellite Division of the Institute of Navigation: ION GNSS-2012, Nashville (Tennessee) (2012)

  41. Gardi, A., Ramasamy, S., Sabatini, R., Kistan, T., Blockley, R., Shyy, W.: Terminal Area Operations: Challenges and Opportunities, Encyclopedia of Aerospace - UAS. Wiley, Chichester (2016). https://doi.org/10.1002/9780470686652.eae1141

    Google Scholar 

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Authors and Affiliations

  1. School of Engineering – Aerospace Engineering and Aviation Discipline, Melbourne, VIC, 3000, Australia

    Subramanian Ramasamy, Roberto Sabatini & Alessandro Gardi

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  1. Subramanian Ramasamy
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  2. Roberto Sabatini
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  3. Alessandro Gardi
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Correspondence to Roberto Sabatini.

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Ramasamy, S., Sabatini, R. & Gardi, A. A Unified Analytical Framework for Aircraft Separation Assurance and UAS Sense-and-Avoid. J Intell Robot Syst 91, 735–754 (2018). https://doi.org/10.1007/s10846-017-0661-z

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  • DOI: https://doi.org/10.1007/s10846-017-0661-z

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