针对智能雷场采用的探测组件仅能够量测目标的距离和径向速度,造成命中概率不高且多个弹药节点可能重复攻击同一目标的问题,文中建立了一种雷场协同探测智能决策的模型。通过提出协同探测方法、目标航迹预测方法和智能决策方法,实现对目标的协同探测智能决策,并采用蒙特卡洛(Monte-Carlo)法,对单个弹药节点的命中概率和智能雷场命中单个目标的耗弹量进行仿真分析。分析结果表明:采用协同探测智能决策模型后,命中概率由不小于62%提高到不小于85%,命中单个目标的平均耗弹量由不大于2.166降低到不大于1.165。研究结果证明,采用协同探测智能决策模型可明显提高命中概率、降低平均耗弹量。

The detection assembly used in intelligent minefield can only measure the radial velocity and distance of the target. Therefore the hit probability is not high and more ammunition nodes may repeat attack the same target. To solve the problem, an intelligent decision-making model of minefield is developed. The intelligent decision on target is realized by collaborative detection method, the target track prediction method and the intelligent decision method. By Monte-Carlo method, the hit probability of single ammunition node and amount of bomb consuming are simulated and analyzed. The analysis results show after adopting the intelligent decision-making model the hit probability is increased from more than 62% to more than 85%, and the average amount of bomb consumption is reduced from less than 2. 166 to less than 1. 165. The research results show that adopting the intelligent decision-making model can obviously increase the hit probability and reduce the average bomb consumption.