电子与控制

一种基于先期毁伤准则的防空火力优化分配

  • 陈黎 ,
  • 王中许 ,
  • 武兆斌 ,
  • 汪渤
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  • 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
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

收稿日期: 2013-11-25

  修回日期: 2014-04-11

  网络出版日期: 2014-04-17

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 ,
  • WANG Zhongxu ,
  • WU Zhaobin ,
  • WANG Bo
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  • 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 date: 2013-11-25

  Revised date: 2014-04-11

  Online published: 2014-04-17

Supported by

China Postdoctoral Science Foundation (2012M521833)

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。

本文引用格式

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 . DOI: 10.7527/S1000-6893.2014.0048

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.

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