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作 者:周谦 高社生[2] 高朝辉 夏娟 洪根元 ZHOU Qian;GAO Shesheng;GAO Zhaohui;XIA Juan;HONG Genyuan(Research and Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen 518057, China;School of Automation, Northwestern Polytechnical University, Xi′an 710072, China;School of Geological Engineering and Geomatics, Chang′an University, Xi′an 710054, China)
机构地区:[1]西北工业大学深圳研究院,广东深圳518057 [2]西北工业大学自动化学院,陕西西安710072 [3]长安大学地质工程与测绘学院,陕西西安710054
出 处:《西北工业大学学报》2021年第3期617-623,共7页Journal of Northwestern Polytechnical University
基 金:国家自然科学基金(41904028);陕西省自然科学基础研究(2020JQ-150);陕西省重点研发计划2018ZDXM-GY-024;深圳市知识创新计划(JCYJ 20180306171439979)资助。
摘 要:针对侦查无人机(reconnaissance unmanned aerial vehicle,RUAV)/攻击型无人机(unmanned combat aerial vehicle,UCAV)对目标作战的任务分配问题,提出了一种考虑目标期望摧毁概率的高效分配方法。该方法在以摧毁目标价值总和最大为目标的基础上,改进设计了模型的收益函数以及约束条件。模型中加入调节因子实现资源的均衡分配;引入目标期望摧毁概率作为约束条件,防止资源的过度分配。随后,设计了基于边缘受益最大化的贪婪算法对所提模型进行求解。仿真结果表明,改进后的模型算法在实现实时性任务分配的基础上,既满足作战效能又提高了经济效能。To solve the combat task assignment of reconnaissance unmanned aerial vehicle(RUAV)/unmanned combat aerial vehicle(UCAV),this paper proposed an efficient task assignment method that takes into account the expected destruction probability of target.This method improves the utility function and constraint of the model that based on the goal of destroying the total sum of the target value.The adjustment factor is added to the model to achieve a balanced distribution of RUAVs/UCAVs resources;the expected destruction probability of target is introduced as a constraint to prevent the excessive distribution of RUAVs/UCAVs resources.Subsequently,a greedy algorithm based on maximizing marginal-return is designed to solve the proposed model.The simulation results show that the improved algorithm not only meets the combat effectiveness but also improves the economic performance on the basis of real-time task allocation.
分 类 号:TP273.5[自动化与计算机技术—检测技术与自动化装置]
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