Trajectory optimization for high-altitude long endurance UAV maritime radar surveillance

Brown, A. and Anderson, D. (2020) Trajectory optimization for high-altitude long endurance UAV maritime radar surveillance. IEEE Transactions on Aerospace and Electronic Systems, 56(3), pp. 2406-2421. (doi: 10.1109/TAES.2019.2949384)

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For an unmanned aerial vehicle (UAV) carrying out a maritime radar surveillance mission, there is a tradeoff between maximizing information obtained from the search area and minimizing fuel consumption. This paper presents an approach for the optimization of a UAV's trajectory for maritime radar wide area persistent surveillance to simultaneously minimize fuel consumption, maximize mean probability of detection, and minimize mean revisit time. Quintic polynomials are used to generate UAV trajectories due to their ability to provide complete and complex solutions while requiring few inputs. Furthermore, the UAV dynamics and surveillance mission requirements are used to ensure a trajectory is realistic and mission compatible. A wide area search radar model is used within this paper in conjunction with a discretized grid in order to determine the search area's mean probability of detection and mean revisit time. The trajectory generation method is then used in conjunction with a multi-objective particle swarm optimization (MOPSO) algorithm to obtain a global optimum in terms of path, airspeed (and thus time), and altitude. The performance of the approach is then tested over two common maritime surveillance scenarios and compared to an industry recommended baseline.

Item Type:Articles
Additional Information:This research was also supported by Leonardo MW Ltd (Application of Machine Learning and Artificial Iintelligence Techniques to Improve Autonomy in Maritime Surveillance Radar Systems S.o.W Reference SELEX/GU/2015/SOW01)
Glasgow Author(s) Enlighten ID:Brown, Angus and Anderson, Dr David
Authors: Brown, A., and Anderson, D.
College/School:College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
Journal Name:IEEE Transactions on Aerospace and Electronic Systems
ISSN (Online):1557-9603
Published Online:01 November 2019
Copyright Holders:Copyright © 2019 IEEE
First Published:First published in IEEE Transactions on Aerospace and Electronic Systems 56(3): 2406-2421
Publisher Policy:Reproduced under a Creative Commons licence

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
172233Anderson ICASE 2015 (Selex)Heather LambieEngineering and Physical Sciences Research Council (EPSRC)IND CASE EP/N509176/1S&E - Academic & Student Administration