An improved genetic algorithm for task scheduling of electro-magnetic detection satellite with uncertain detecting duration

Electro-magnetic Detection Satellite (EDS) is an important branch of Earth Observation Satellites (EOSs). It has been widely applied in industry and military areas. The detecting duration of EDS is different from imagery satellites, for it is an imprecise parameter because of the uncertain electromagnetic environment within space surrounding targets. This factor makes the task scheduling for EDS becoming a complex combinatorial optimization problem. With consideration of this special property, we used fuzzy set and possibility theory to model imprecise parameters, other physical constraints, like on-board energy and transition time between different working patterns and sensor´s rebooting, were also taken into account in the model. We presented an improved genetic algorithm to solve this problem by introducing new method of elitist and parents selection. The model and the algorithm have been tested by five experiments derived from STK´s satellite database.