亚丁湾护航中直升机识别海盗目标路径优化模型及算法

针对舰载直升机执行伴随护航任务时查证可疑船只的路径优化问题,对直升机在选择巡逻查证路径时所面临的各种复杂情况进行了分析。文中结合可疑船只与编队的相对运动特点以及海面可疑船只威胁程度评估指标,以保障被护航编队受到的累计威胁值最小为目标,构建了直升机查证可疑船只时的路径优化模型。为提高蚁群算法的求解效率,文中将混沌映射扰动引入到信息素的全局更新过程中,从而有效降低算法陷入局部最优的概率。另外,文中对蚁群算法中状态转移规则和信息素更新等核心环节进行了优化设计,提高了算法对最优路径的搜索能力。最后,以我国海军亚丁湾护航任务为背景进行实例分析,并将其结果与遗传算法和禁忌搜索算法进行对比,验证了所建模型和算法的合理性和有效性。

Path Optimization Model and Algorithm for Helicopter Identifying Suspicious Pirate Targets in the Gulf of Aden

In view of the need to the optimal path plan for verifying suspicious ships when carrying out escort missions for ship-borne helicopters,this paper builds a path optimization model for helicopters to identify suspicious ships.This model combines the relative motion of suspicious ships with the assessment of threat indicators of these ships,and the optimal target of the model is to ensure that the escorted fleet is threatened to a minimum.In order to improve the efficiency of ant colony algorithm,chaos mapping disturbance is introduced into the global updating process of pheromone, so as to effectively reduce the probability of the algorithm falling into local optimum.In addition,the core links of ant colony algorithm,such as state transition rule and pheromone update,are optimized to improve the search ability of the algorithm.Finally,this paper analyzes the case of the Chinese Navy’s escort in the Gulf of Aden,and examines the feasibility of the model and algorithm.