• Key dates

    Issue of call for abstracts :
    mid-February 2018

    Deadline for abstract submission:
    25 May 2018

    Notification of abstract selection:
    20 June 2018

    Deadline submission of full papers:
    3 Sep 2018

    Provision of peer-review evaluation:
    3 Oct 2018

    Deadline submission of final version of papers: 23 Nov 2018


  • Jiyun Lee
    Assoc. Professor, Korea Advanced Institute of Science and Technology, South Korea
    Local-Area Differential GNSS for UAV Applications

    As civilian use of unmanned aerial vehicles (UAVs) increases, safe operation of UAVs while preventing collisions with either humans or ground structures has become a significant concern. High accuracy and reliability of navigation solutions should be achieved to perform autonomous UAV missions especially Beyond Visual Line-Of-Sight (BVLOS) or in low-altitude airspace safely. This motivates the development of a cost-effective local-area UAV network that utilizes a Local-Area Differential Global Navigation Satellite System (LAD-GNSS) navigation solution. The LAD-GNSS meets the required level of integrity requirements (comparable to those of GBAS Category I – III operations) by monitoring navigation faults at both the reference station and UAV and by broadcasting integrity information to the UAV. By utilizing the integrity information which defines navigation system error models, the UAVs can compute their conservative position error bounds (i.e., protection levels (PL)) and consequently safe separation distances in real time. A concept of UAV operation is to support “in network” UAVs using LAD-GNSS with a minimum operating altitude of either 50 ft plus obstacle height (within 5 km of the ground facility) or 150 ft plus obstacle height (within 20 km of the ground facility).
    The LAD-GNSS architecture for local-area UAV network proposed in previous work includes several methods of simplifying the current GBAS integrity monitoring algorithms and hardware configurations to lower cost and complexity of the system while maintaining an acceptable level of safety. The performance and integrity of LAD-GNSS can also improve by designing additional modules using airborne monitors or an airborne-to-ground datalink. Position Domain Monitoring at a remote site helps detect atmospheric and satellite ephemeris errors that are not easy to observe at the primary site. The addition of a simplified form on solution-separation RAIM, modeled on "Advanced RAIM" or ARAIM, will also be considered to reduce the ephemeris failure threat. The use of a two-way datalink to relay UAV information back to the ground station provides a significant advantage over the conventional GBAS and makes the real-time allocation possible. Since the LAD-GNSS ground station can be notified about the satellite geometry which the UAV utilizes for its positioning, it is possible to compute the PLs for all fault scenarios and optimally allocate the integrity and continuity budgets in order to make the PLs to be identical for all fault scenarios. The integrity status of each UAV, including its current PLs, is maintained by the ground facility and is used to guide each vehicle while maintaining safe separation from nearby obstacles and other UAVs. A prototype of both ground and airborne modules was developed and tested to evaluate the performance of the proposed architecture.

    Dr Jiyun Lee received a B.S. degree in astronomy and atmospheric science from Yonsei University in Seoul, Republic of Korea, an M.S. degree in aerospace engineering sciences from the University of Colorado at Boulder, Boulder, CO, USA, and a Ph.D. degree in aeronautics and astronautics from Stanford University, Stanford, CA, USA, in 2005. She is an Associate Professor in the Department of Aerospace Engineering at Korea Advanced Institute of Science and Technology in Daejeon, Republic of Korea. As part of her professional experience, she worked as a Consulting Professor with Stanford University, a Principal Systems Engineer with Tetra Tech AMT, and a Senior GPS Systems Engineer with SiRF Technology, Inc. She has published over 80 research papers in the field of GNSS applications, multi-sensor navigation, safety-critical systems, atmospheric science and remote sensing. She was awarded the FAA Recognition Award in 2013.
    Jason Rife
    Assoc. Prof., Tufts University, USA
    Software and GNSS Fault-Monitoring for Automated Aircraft

    As aircraft automation becomes increasingly sophisticated, new challenges arise in maintaining our air transportation systems’ exceptional safety record. This talk discusses current research on detecting and responding to rare faults in two areas of aircraft automation. A first topic will be monitoring for GNSS faults should they occur during automated landing of commercial aircraft. Error analysis methods will be discussed with application to the Ground Based Augmentation System (GBAS). A second topic will be monitoring for bugs in the flight management system (FMS) for autonomous drones. Recent work in using machine learning for FMS bug detection will be discussed, with an emphasis on the potential applications for streamlining the increasingly costly and time-consuming activity of proving safety for drone systems.
    Jason Rife is an Associate Professor at Tufts University, with a primary appointment in Mechanical Engineering and an adjunct appointment in Electrical and Computer Engineering. He directs the Automation Safety and Robotics Laboratory (ASAR), which applies theory and experiment to characterize robots and autonomous vehicle systems for safety-of-life applications.  He received his B.S. in Mechanical and Aerospace Engineering from Cornell University and his M.S. and Ph.D. degrees in Mechanical Engineering from Stanford University. 

    Catherine Ronfle-Nadaud
    Drone Program Manager, Direction des Services de la Navigation Aérienne (DSNA), France
    Risk Assessment for Drones Operations

    The safe integration of drones in the airspace rely on the assessment of the operational risks. EASA (European Aviation Safety Agency) and JARUS (Joint Authorities for Rulemaking on Unmanned Systems) have proposed a new methodology, SORA (Specific Operational Risk Assessment) in order to evaluate the ground risk and the air risk of an operation. When it comes to assess the air risk, the confidence about the drone trajectory is very important.
    In this presentation, we will focus on the air risk. The problem of airspace management will first be explained. It will be followed by a presentation of how it is possible to evaluate the air risk taking into account all parameters including navigation accuracy. Some on-going projects and experiments will be used to illustrate and clarify specific points.

    Catherine Ronflé-Nadaud is Drone Program Manager at the “Direction de la Technique et de l’Innovation” (DTI) of DSNA, the French Air Navigation Service Provider. From January 2006 to June 2015, she was the head of the UAV Program at ENAC, the French Civil Aviation Academy. In 1989, she received the ENAC engineer diploma, then a Master of Science in “Fundamental Computer Science and Parallel Computing” from INP Toulouse. She became a DGAC Professional Pilot in 1991 (IFR November 2000, Twin Engine Qualification May 2010). From 1994 to 2005, she was the Head of the Computer Network Team at ENAC.

    Todd Walter
    Senior Research Engineer, Stanford University, USA
    RFI Mitigation for Civil Navigation

    The effects of radio frequency interference (RFI) is one of the largest challenges facing satellite navigation. RFI can overwhelm the desired signals and lead to a loss of navigation.  Even more concerning, is the possibility that undesired signals can be interpreted as the intended signals, leading to corrupted positioning that may go undetected by the user.  This latter spoofing threat may be inadvertent or part of a deliberate attack. The navigation community is working on several powerful technologies to overcome these dangers. These solutions include internal receiver validity checks, advanced receiver autonomous integrity monitoring (ARAIM), antenna-based detection, and comparison to other sensors (such as accelerometers).  ARAIM combats spoofing, because it is difficult to simultaneously replace all of the received signals with counterfeit signals.  However, all of these approaches have limitations. The lecture will describe the threats as well as the trade-offs between the various proposed solutions.
    Todd Walter received his Ph.D. in Applied Physics from Stanford University in 1993.  He is a Senior Research Engineer in the Department of Aeronautics and Astronautics at Stanford University. His research focuses on implementing high-integrity air navigation systems.  He has received the ION Thurlow and Kepler awards.  He is also a fellow of the ION and has served as its president.

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