Evolutionary Allocation of Mobile Assets in a Distributed Surveillance Network

摘要

Wide area surveillance using a distributed network of autonomous assets is an increasingly important application for homeland security, harbor defense, and airborne target cueing. Optimal allocation of these autonomous assets remains a challenging endeavor; the surveillance area is large, assets may have a limited ability to communicate with each other, and the contact's position is uncertain. We present an evolutionary algorithm that balances the objectives of maximum network endurance and minimum contact free time. Simulation results are presented that demonstrate the effectiveness of the approach.