关键词: 多弹药, 毁伤评估, 瞄准点选择, 累积毁伤, 联合毁伤, 复杂面目标

Abstract: An improved particle swarm optimization (IPSO) algorithm is proposed to select the optimal aiming point of multiple projectiles when striking complex surface targets. When constructing the aiming point selection model, the influence of complex factors such as the shape of area target area, the correlation between different areas, the different power area of ammunition, the different hit accuracy of ammunition, the cumulative damage and the combined damage of multiple bullets on the target damage effect is considered comprehensively. Particle swarm optimization (PSO) is improved by preassigning particle positions and introducing particle activation energy, which not only improves the convergence speed but also ensures the global search ability. The performance of the proposed algorithm is verified by a typical complex surface target test case. The results show that compared with the commonly used Monte Carlo algorithm and particle swarm optimization algorithm, the proposed IPSO algorithm has better aiming point selection ability, average damage benefit increased by 4.3%, and the average aiming selection time is only 1/4 to 1/3, which has obvious advantages in damage benefit and computing efficiency.

Key words: multiple ammunition, damage assessment, aiming point selection, cumulative damage, combined injury, complex surface target