SBIR-STTR Award

The objective of this Phase I proposal is to demonstrate the feasibility of automating and optimizing the placement and routing of surveillance and reconnaissance systems. These systems consist of dissimilar cross-program space, air, sea and land-based platforms performing cooperative, simultaneous collects against many targets over a theater-wide region. Quality metrics such as geolocation accuracy will be used in place of previous metrics such as line-of-sight access and revisit times. This research proposes using genetic algorithms to optimally (1) choose fixed assets (2) route and place variable assets and (3) choose the best geolocation technique. Heuristics will be developed to initialize the solution population and guide the genetic algorithm evolution. These heuristics will encapsulate problem specific information to ensure operational viability

The objective of this Phase II proposal is to demonstrate the feasibility of automating and optimizing the placement and routing of surveillance and reconnaissance systems. These systems consist of dissimilar cross-program space, air, sea and lan-based platforms performing cooperative, simultanteous collectsagainst many targets over a theater-wide region. Quality metrics such as geolocation accuracy will be used in place of previous metrics such as line-of-site access and revisit times. This research proposes using genetic algorithms to optimally (1) choose fixed assetts (2) route and place variable assetts and (3) choose the best geolocation technique. Heuristics will be developed to intialize the solution population and guide the genetic algorith evolution. These heuristics will encapsulate problem-specific information to ensure operational viability.

Keywords:
GEOLOCATIONSIGNIT GENETIC ALGORITHMS ROUTE PLANNING MISSION PLANNING