Multi-objective Optimization of Observation Scheduling Avoiding Attitude Maneuvering Conflict

To solve the complicated scheduling problem of many observations in earth-observing satellites, we propose an effective multi-objective combinatorial optimization method using a genetic algorithm (GA) to maximize speed, visibility, and the number of adoptions of target points according to the priority. A characteristic of the proposed method is the constraint of "one observation per point." Another is that conflict between the observation tasks is considered. To determine the conflicts, the attitude maneuver time is calculated by assuming a triangular or trapezoidal linear angular velocity profile in order to reduce the computation time and obtain an actual control time that is as close as possible. The simulation results indicate that the proposed method can adopt more target points than the comparative method without considering the attitude maneuvering time. Moreover, the Nankai-Trough earthquake demonstration shows the effectiveness of disaster monitoring.