Opportunistic Sensor Resource Management for Extended Operating Conditions

"DSR will apply the application of proven artificial intelligence (AI) technology to the problem of controlling distributed Intelligence, Surveillance, and Reconnaissance (ISR) assets in extended operating conditions. DSR has demonstrated these AItechnologies to the Air Force Research Lab for their Unmanned Combat Vehicles (UCAV) and Miniature Air Launched Vehicles (MALV). In today's war fighting environment, it is a given that ISR is crucial in deciding the outcome. This is because precisionstrike targeting (PST) requires a sensor capability which can detect, track, identify, and maintain contact with multiple targets to selectively mass firepower where needed. Clearly, successful time critical targeting (TCT) requires rapid engagement oftargets, especially fleeting or emerging targets. This can only be achieved by unprecedented coordination and interoperability in sensor asset management or the Command and Control of ISR (C2ISR). Dynamically adaptive real-time asset algorithms canmitigate the time factor and reduce the amount of information that needs to be communicated over exiting bandwidth limited links. DSR's proposal for Neural Network AI algorithm development is an innovative approach of acceptable risk, leveraging theoperational and cost benefits of coordinating ISR assets to achieve full battle space dominance to include TCT engagement and automatic target recognition (ATR). This problem is very similar to a metropolit