一种基于先期毁伤准则的防空火力优化分配

doi:10.7527/S1000-6893.2014.0048

电子与控制

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一种基于先期毁伤准则的防空火力优化分配

陈黎^1,2, 王中许¹, 武兆斌¹, 汪渤²

1. 中国人民解放军 63961部队, 北京 100012;
2. 北京理工大学自动化学院, 北京 100081

收稿日期:2013-11-25 修回日期:2014-04-11 出版日期:2014-09-25 发布日期:2014-04-17
通讯作者: 陈黎，Tel.：010-66749370 E-mail：hncschenli@126.com E-mail:hncschenli@126.com
作者简介:陈黎男，博士。主要研究方向：目标跟踪与多传感器数据融合、火力控制与指挥控制系统。Tel：010-66749370 E-mail：hncschenli@126.com；王中许男，博士，高级工程师。主要研究方向：控制理论与应用、火力控制与指挥控制系统、武器系统论证。E-mail：wangzhongxu1001@163.com
基金资助:
中国博士后科学基金（2012M521833）

A Kind of Antiaircraft Weapon-target Optimal Assignment Under Earlier Damage Principle

CHEN Li^1,2, WANG Zhongxu¹, WU Zhaobin¹, WANG Bo²

1. No. 63961 Unit, People's Liberation Army of China, Beijing 100012, China;
2. School of Automation, Beijing Institute of Technology, Beijing 100081, China

Received:2013-11-25 Revised:2014-04-11 Online:2014-09-25 Published:2014-04-17
Supported by:
China Postdoctoral Science Foundation (2012M521833)

摘要/Abstract

摘要：

针对防空火力分配中，在火力资源相对充足的情况下采用带资源约束的最大毁伤准则进行火力分配容易贻误战机的问题，提出了一种基于先期毁伤准则的防空火力分配新模型。该模型的思想是保证在满足毁伤概率门限的前提下，优先分配威胁度大的目标，并且利用目标到火力单元的飞临时间信息，选择尽量少的火力单元尽早毁伤目标；在毁伤目标的同时兼顾了火力资源的消耗情况和毁伤的时机，达到了以期望毁伤概率、较少火力资源尽早毁伤目标的目的。在此基础上，提出采用混沌和离散粒子群混合优化（CDPSO）算法求解防空火力分配问题，提高了算法的全局搜索能力，避免陷入局部极值。通过仿真验证了新模型的优点以及所提混合优化算法的有效性和优越性。

关键词: 整数规划, 火力分配, 先期毁伤, 混沌优化, 离散粒子群优化

Abstract:

In antiaircraft weapon-target assignment, damage time could be delayed under maximum damage principle with firepower resources constraint, when firepower resources are sufficient. To cope with the disadvantage, a new weapon-target assignment model under earlier damage is proposed. In the new model targets with high target threat are firstly assigned to a few weapons, which can damage these targets as early as possible, and the damage probability is greater than the preset threshold. That is to say, by using flying time from target to weapon, the damage time is considered except damage probability and firepower resources, and serious and earlier damage with fewer firepower resources can be achieved at the same time. Based on the new model, a mixed chaos and discrete particle swarm optimization (CDPSO) algorithm is presented to solve the weapon-target assignment problem. The proposed algorithm improves the seeking ability for the global optimal solution, so that the local extremum is avoided. Simulation results show the advantage of the new weapon-target assignment model, as well as the effectiveness and the superiority of the proposed mixed optimization algorithm.

Key words: integer programming, weapon-target assignment, earlier damage, chaos optimization, discrete particle swarm optimization

中图分类号:

陈黎, 王中许, 武兆斌, 汪渤. 一种基于先期毁伤准则的防空火力优化分配[J]. 航空学报, 2014, 35(9): 2574-2582.

CHEN Li, WANG Zhongxu, WU Zhaobin, WANG Bo. A Kind of Antiaircraft Weapon-target Optimal Assignment Under Earlier Damage Principle[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2014, 35(9): 2574-2582.

参考文献

[1] Zhang Z L, Wu W D. Method of aptitudinally distributing firepower in aerial defence[J]. Fire Control and Command Control, 2006, 31(2): 75-77. (in Chinese) 张自立, 武卫东. 防空智能火力分配的实现方法[J].火力与指挥控制, 2006, 31(2): 75-77.

[2] Huang L W, Xu P G, Wang Q. Firepower distribution problems based on Hungarian method[J]. Fire Control and Command Control, 2007, 32(6): 25-28. (in Chinese) 黄力伟, 许品刚, 王勤. 基于匈牙利算法求解的火力分配问题[J]. 火力与指挥控制, 2007, 32(6): 25-28.

[3] Ruan M Z, Li Q M, Liu T H. Modeling and optimization on fleet antiaircraft firepower allocation[J]. Acta Armamentarii, 2010, 31(11): 1525-1529. (in Chinese) 阮旻智, 李庆民, 刘天华. 编队防空火力分配建模及其优化方法研究[J]. 兵工学报, 2010, 31(11): 1525-1529.

[4] Guo Y H, Li Y T, Yang F Y. Mutation ant colony algorithm for weapon-target assignment problem based on threshold of damage probability[J]. Journal of Gun Launch & Control, 2006(4): 1-5. (in Chinese) 郭蕴华, 李运涛, 杨福缘. 考虑毁伤概率门限的火力分配变异蚁群算法[J]. 火炮发射与控制学报, 2006(4): 1-5.

[5] Yang F, Wang Q, Hou Y Z. Weapon-target assignment in multi-launcher system based on improved integer field particle swarm optimization algorithm[J]. Acta Armamentarii, 2011, 32(7): 906-912. (in Chinese) 杨飞, 王青, 侯砚泽. 基于整数域改进粒子群优化算法的多平台武器目标分配[J]. 兵工学报, 2011, 32(7): 906-912.

[6] Li Y, Dong Y N. Weapon-target assignment based on simulated annealing and discrete particle swarm optimization in cooperative air combat[J]. Acta Aeronautica et Astronautica Sinica, 2010, 31(3): 626-631. (in Chinese) 李俨, 董玉娜. 基于SA-DPSO混合优化算法的协同空战火力分配[J]. 航空学报, 2010, 31(3): 626-631.

[7] Wang Y X, Guo Z. Fire distribution of missile-gun integrated air defense system under earlier damage principle[J]. Acta Armamentarii, 2009, 30(4): 481-485. (in Chinese) 王艳霞, 郭治. 先期毁伤准则下弹炮结合防空武器系统的火力分配[J]. 兵工学报, 2009, 30(4): 481-485.

[8] Liu W D, Jiang Q S, Li Y, et al. Fire distribution of the network centric ship-to-air missile based on earlier damage[J]. Ship Science and Technology, 2011, 33(2): 98-101. (in Chinese) 刘卫东, 姜青山, 李勇, 等. 基于先期毁伤的舰空导弹网络化协同反导火力分配[J]. 舰船科学技术, 2011, 33(2): 98-101.

[9] Lee Z J, Su S F, Lee C Y. Efficiently solving general weapon-target assignment problem by genetic algorithms with greedy eugenics[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2003, 33(1): 113-121.

[10] Luo D L, Duan H B, Wu S X, et al. Research on air combat decision-making for cooperative multiple target attack using heuristic ant colony algorithm[J]. Acta Aeronautica et Astronautica Sinica, 2006, 27(6): 1166-1170. (in Chinese) 罗德林, 段海滨, 吴顺详, 等. 基于启发式蚁群算法的协同多目标攻击空战决策研究[J]. 航空学报, 2006, 27(6): 1166-1170.

[11] Wu X J, Yang Z Z, Zhao M. A uniform searching particle swarm optimization algorithm[J]. Acta Electronica Sinica, 2011, 39(6): 1261-1266. (in Chinese) 吴晓军, 杨战中, 赵明. 均匀搜索粒子群算法[J]. 电子学报, 2011, 39(6): 1261-1266.

[12] Zhang C S, Sun J G, Ouyang D T. A self-adaptive discrete particle swarm optimization algorithm[J]. Acta Electronica Sinica, 2009, 37(2): 299-304. (in Chinese) 张长胜, 孙吉贵, 欧阳丹彤. 一种自适应离散粒子群算法及其应用研究[J]. 电子学报, 2009, 37(2): 299-304.

[13] Sun Y X, Wang Z H, Chen Z Q, et al. Chaotic particle swarm optimization and analysis[J]. Journal of System Simulation, 2008, 20(21): 5920-5923. (in Chinese) 孙艳霞, 王增会, 陈增强, 等. 混沌粒子群优化及其分析[J]. 系统仿真学报, 2008, 20(21): 5920-5923.

[14] Ye W, Zhu A H, Ouyang Z H, et al. Multi-UCAV cooperation mission assignment based on hybrid discrete particle swarm optimization algorithm[J]. Acta Armamentarii, 2010, 31(3): 331-336. (in Chinese) 叶文, 朱爱红, 欧阳中辉, 等. 基于混合离散粒子群算法的多无人作战飞机协同目标分配[J]. 兵工学报, 2010, 31(3): 331-336.

[15] Wang L F, Zeng J C. A cooperative evolutionary algorithm based on particle swarm optimization and simulated annealing algorithm[J]. Acta Automatica Sinica, 2006, 32(4): 630-635. (in Chinese) 王丽芳, 曾建潮. 基于微粒群算法与模拟退火算法的协同进化方法[J]. 自动化学报, 2006, 32(4): 630-635.

[16] Ji Z, Liao H L, Wu Q H. Particle swarm optimization and its application[M]. Beijing: Science Press, 2009: 48-53. (in Chinese) 纪震, 廖惠连, 吴青华. 粒子群算法及应用[M]. 北京: 科学出版社, 2009: 48-53.

E-mail：hkxb@buaa.edu.cn

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

一种基于先期毁伤准则的防空火力优化分配

A Kind of Antiaircraft Weapon-target Optimal Assignment Under Earlier Damage Principle

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