A sensor tasking algorithm for EO/IR sensors carried by UAVs

摘要

We address the problem of controlling EO/IR sensors carried by UAVs, in a context where multiple UAVs are employedto 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 adegree 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 anexpected reward stream that would be accrued if the task were put into effect. The size of the MDP state space increasesexponentially with the number of candidate tasks, so generic MDP solutions are inapplicable. Instead we propose asolution using Gittins indices.Our problem includes time sensitive tasks, where the probability of receiving a reward decays with system time. Theproblem also includes tasks that are not time sensitive. The combination of time-sensitive and non-time-sensitive tasks ischallenging for an index policy. Our contribution is to create a combination of index algorithms that approximatelysolves 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.