This study focuses on the optimization of hit probability in deep-water anti-submarine warfare in complex sea areas

particularly considering the random errors in submarine positioning. The research is divided into three parts. First

under the condition that the submarine's depth is accurately located but its horizontal coordinates have a normal distribution error

a two-dimensional normal distribution is used to describe the uncertainty of the submarine's position. By combining three scenarios of contact fuzes and depth fuzes

the hit probability is calculated using integral methods. Through Python numerical simulations and Monte Carlo method validation

the optimal drop point (0

0) and its maximum hit probability are determined. Second

under the condition that the submarine's X

Y

and Z coordinates all have errors

and the Z coordinate follows a one-sided truncated normal distribution

a mathematical model is established. The hit probability is solved using triple integrals

and the optimal detonation depth is optimized. Finally

for the scenario where an anti-submarine aircraft carries multiple depth charges

a planar array-based bombing strategy is designed to optimize the bombing interval and maximize the hit probability. The research shows that reasonable optimization of detonation depth and bombing array can significantly improve the success rate of deep-water anti-submarine warfare. The research results have important theoretical significance and practical value for improving the combat effectiveness of anti-submarine weapons.