Abstract:

Space object surveillance has a vital role in the smooth development of space mission. To solve the large-scale and complex scheduling problem of space object ground-based surveillance, a mathematical model with multiple constraints and optimal objectives is established. Through discussing a hybrid strategy of algorithms to local optimize a part of the global solution using the genetic algorithm to improve utilization of sensor resources, a hybrid algorithm with genetic algorithm and simulated annealing algorithm is constructed. A heuristic method is used to construct parts of solution for vague requirements, and a method named window trimming is used to solve time window conflicts in the hybrid algorithm. Simulation results show that the genetic-simulated annealing algorithm and window trimming method can receive a satisfactory solution in the acceptable term, which verifies that the model and algorithm are validity.