TY - GEN
T1 - Cooperative and non-cooperative sense-and-avoid in the CNS+A context
T2 - 2016 International Conference on Unmanned Aircraft Systems, ICUAS 2016
AU - Ramasamy, Subramanian
AU - Sabatini, Roberto
AU - Gardi, Alessandro
N1 - Funding Information:
Dr. Paquola was funded through a postdoctoral fellowship of the Transforming Autism Care Consortium (TACC). Drs. Bethlehem and Bernhardt received an MNI-Cambridge collaboration grant. Dr. Bernhardt acknowledges research support from the National Science and Engineering Research Council of Canada (NSERC, Discovery-1304413), the Canadian Institutes of Health Research (CIHR, FDN-154298), the Azrieli Center for Autism Research of the Montreal Neurological Institute (ACAR), SickKids Foundation (NI17-039), and received salary support from FRQS (Chercheur Boursier Junior 1). Mr. Vos de Wael was funded by a studentship of the Savoy Foundation. Dr. Wagstyl was supported by the Health Brain Healthy Lives (HBHL) Initiative. Dr. Bethlehem was supported by the Autism Research Trust and a British Academy Post-Doctoral Fellowship (PF2\180017). Mr. Seidlitz was supported by the NIH-Oxford/Cambridge Scholars Program. Dr. Smallwood was supported by a European Research Council Consolidator Grant (WANDERINGMINDS ? 646927). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Publisher Copyright:
© 2016 IEEE.
PY - 2016/6/30
Y1 - 2016/6/30
N2 - A unified approach to cooperative and non-cooperative Sense-and-Avoid (SAA) is presented that addresses the technical and regulatory challenges of Unmanned Aircraft Systems (UAS) integration into non-segregated airspace. In this paper, state-of-the-art sensor/system technologies for cooperative and non-cooperative SAA are reviewed and a reference system architecture is presented. 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) system is performed based on Boolean Decision Logics (BDL) to support trusted autonomous operations during all flight phases. The BDL adoption allows for a dynamic reconfiguration of the SAA architecture, based on the current error estimates of navigation and tracking sensors/systems. The significance of this approach is discussed in the Communication, Navigation and Surveillance/Air Traffic Management and Avionics (CNS+A) context, with a focus on avionics and ATM certification requirements. Additionally, the mathematical models employed in the SAA Unified Method (SUM) to compute the overall uncertainty volume in the airspace surrounding an intruder/obstacle are described. In the presented methodology, navigation and tracking errors affecting the host UAS platform and intruder sensor measurements are translated 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. The results confirm the validity of the proposed unified methodology providing a pathway for certification of SAA systems that typically employ a suite of non-cooperative sensors and/or cooperative systems.
AB - A unified approach to cooperative and non-cooperative Sense-and-Avoid (SAA) is presented that addresses the technical and regulatory challenges of Unmanned Aircraft Systems (UAS) integration into non-segregated airspace. In this paper, state-of-the-art sensor/system technologies for cooperative and non-cooperative SAA are reviewed and a reference system architecture is presented. 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) system is performed based on Boolean Decision Logics (BDL) to support trusted autonomous operations during all flight phases. The BDL adoption allows for a dynamic reconfiguration of the SAA architecture, based on the current error estimates of navigation and tracking sensors/systems. The significance of this approach is discussed in the Communication, Navigation and Surveillance/Air Traffic Management and Avionics (CNS+A) context, with a focus on avionics and ATM certification requirements. Additionally, the mathematical models employed in the SAA Unified Method (SUM) to compute the overall uncertainty volume in the airspace surrounding an intruder/obstacle are described. In the presented methodology, navigation and tracking errors affecting the host UAS platform and intruder sensor measurements are translated 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. The results confirm the validity of the proposed unified methodology providing a pathway for certification of SAA systems that typically employ a suite of non-cooperative sensors and/or cooperative systems.
KW - CNS+A framework
KW - Cooperative Systems
KW - Non-Cooperative Sensors
KW - Sense-and-Avoid
KW - Trusted Autonomy
KW - Unified Approach
KW - Unmanned Aerial Vehicle
KW - Unmanned Aircraft Systems
UR - http://www.scopus.com/inward/record.url?scp=84979780575&partnerID=8YFLogxK
U2 - 10.1109/ICUAS.2016.7502676
DO - 10.1109/ICUAS.2016.7502676
M3 - Conference contribution
AN - SCOPUS:84979780575
T3 - 2016 International Conference on Unmanned Aircraft Systems, ICUAS 2016
SP - 531
EP - 539
BT - 2016 International Conference on Unmanned Aircraft Systems, ICUAS 2016
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 7 June 2016 through 10 June 2016
ER -