Abstract:

According to the characteristics of target allocation in formation cooperative air-to-ground combat (FCAGC), some issues about the application of improved binary particle swarm optimization (IBPSO) to target allocation are studied. Firstly, by computing the income and cost of damaging targets, an evaluation standard of target allocation is set up. Secondly, the formulas about the velocity and position of binary particle swarm optimization are improved by introducing into a series of operators. Then, IBPSO is applied to target allocation. Simulation results show that IBPSO has a more powerful global search capability and faster convergence velocity than the genetic algorithm (GA).