Abstract
This research considers the problem of maximizing information collection and exchange between unmanned resources and a control station in a bandwidth constrained environment. Unmanned aerial vehicles (UAVs) are utilized in disaster response to gather data and aid in intelligence, surveillance, and reconnaissance (ISR). They are regularly equipped with multiple gimbal-mounted heterogeneous sensors, generating large amounts of data which are to be routed through a communications network back to mission managers. A mixed integer linear program (MILP) is formulated for this problem. However, due to the complexity of this problem, the MILP is only able to solve trivially-sized problems. A three-phase heuristic approach is proposed which, through extensive testing, is proven to efficiently solve large-sized problems. Our analysis also gives insight into the features of this problem and their impact on mission success.
•Defined a bandwidth-constrained sensor tasking problem for unmanned aerial vehicles.•Developed a mixed integer linear program and a heuristic approach to solve problem.•Heuristic approach outperforms math model in large and complex instances.•Analysis indicates that sensors with large fields-of-regard provide the most benefit.