Abstract: For the high-speed target tracking in aerospace, sensor resource scheduling has problems such as lack of task latency time, multiple matching of sensor resources and observation time fragmentation. To solve these problems, this paper proposes a multi-source heterogeneous sensor scheduling multi-objective optimization model and a multi-objective flexible fruit fly algorithm for solving the model. In order to solve the problem of time fragmentation, the target-time-sensor three-dimensional coding method is designed by using flexible segmentation scheduling time. To avoid the search to fall into local optimum caused by evolution of similar individuals, the crossover operator and mutation operator based on individual features are proposed. Focusing on the problems of time fragmentation and repeated observation during evolution, a flexible adjustment operator is presented. Finally, the model and algorithm proposed in this paper are verified by two test problems. The experimental results show that the proposed algorithm can solve the multi-source heterogeneous sensor resource scheduling problems reasonably, and the proposed algorithm has better properties than the comparison algorithm in convergence and distribution.

Key words: fruit fly algorithm, multi-objective, sensor resource schedule, high speed target