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7 October 2019 A sensor tasking algorithm for EO/IR sensors carried by UAVs
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We address the problem of controlling EO/IR sensors carried by UAVs, in a context where multiple UAVs are employed to perform a surveillance mission. Swarm-based ISTAR can deliver commanders a more complete situational picture, but controlling a swarm becomes increasingly complex with each additional vehicle. A practical system requires a degree of autonomy to avoid overwhelming operators with detail and/or to avoid requiring too many operators. We present a sensor tasking algorithm which chooses a sequence of tasks for an EO/IR sensor located on an air vehicle. The tasking problem is formulated as a Markov Decision Process (MDP), in which each task is associated with an expected reward stream that would be accrued if the task were put into effect. The size of the MDP state space increases exponentially with the number of candidate tasks, so generic MDP solutions are inapplicable. Instead we propose a solution using Gittins indices. Our problem includes time sensitive tasks, where the probability of receiving a reward decays with system time. The problem also includes tasks that are not time sensitive. The combination of time-sensitive and non-time-sensitive tasks is challenging for an index policy. Our contribution is to create a combination of index algorithms that approximately solves the MDP for a combination of time-sensitive and non-time-sensitive tasks. EO/IR stands for Electro-Optic / Infra-Red. UAV stands for Unmanned Aerial Vehicle. ISTAR stands for Intelligence, Surveillance, Target Acquisition and Reconnaissance.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Steve Sykes "A sensor tasking algorithm for EO/IR sensors carried by UAVs", Proc. SPIE 11166, Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies III, 111660K (7 October 2019);

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