Orbit design for ground surveillance using genetic algorithms

The possibility of using genetic algorithms (GA) to search for natural orbits that achieves ground surveillance mission requirements is discussed. The GA have been adopted to solve the ground surveillance problem as the problem is characterized by many local minima. The GA solution is used as a starting point to find a local minimum solution through traditional optimization methodologies. Two kinds of constraints are considered in the solution of the problem. The first mission searches for maximum resolution for each site for a given imaging sensor. The second mission attempts to maximize the observation time. The objective of the solution is to minimize the penalty function which is a function of a state vector whose elements are orbital parameters. For best resolution case, a candidate optimality criterion is to minimize a weighted sum of squares of the distance between each site and the nearest ground track point.

Orbit design for ground surveillance using genetic algorithms Academic Article