Task Allocation Method for UAV Swarm Ground Attack Based on IPSO

The ground attack task allocation of unmanned aerial vehicle (UAV) swarm is the key and difficult problem in the UAV ground attack mission planning. In response to this problem, the mathematical model is designed, in which the objective function is to maximize the target attack gain and minimize the target attack cost, and the target coverage, the target damage effect, the UAV attack threshold and the UAV range constraints are taken into account. And an improved particle swarm optimization (IPSO) including encoding and decoding rules, constraint handling rules and particle update rules are designed to solve the model. The simulation results show that, the proposed algorithm can effectively solve the task allocation model, and compared with other algorithms, the proposed algorithm has certain advantages.