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计算机工程 ›› 2011, Vol. 37 ›› Issue (21): 152-154,158. doi: 10.3969/j.issn.1000-3428.2011.21.052

• 人工智能及识别技术 • 上一篇    下一篇

基于多Agent的战场目标分群方法

赵 鹏1,2,常天庆1,魏 巍1,张 波1   

  1. (1. 装甲兵工程学院控制工程系,北京 100072;2. 防空兵指挥学院防空导弹系,郑州 450052)
  • 收稿日期:2011-03-15 出版日期:2011-11-05 发布日期:2011-11-05
  • 作者简介:赵 鹏(1976-),男,讲师、博士,主研方向:计算机自动测试,战车指控与火控系统智能化;常天庆,教授、博士生导师;魏 巍、张 波,讲师、博士

Battlefield Target Grouping Method Based on Multi-Agent

ZHAO Peng 1,2, CHANG Tian-qing 1, WEI Wei 1, ZHANG Bo 1   

  1. (1. Department of Control Engineering, Academy of Armored Forces Engineering, Beijing 100072, China; 2. Department of Surface-to-Air Missile, Air Defence Forces Command Academy, Zhengzhou 450052, China)
  • Received:2011-03-15 Online:2011-11-05 Published:2011-11-05

摘要: 针对陆战场的态势识别问题,提出一种用于多Agent的态势识别系统战场目标分群方法。在陆战场目标分群过程中,管理Agent与实体Agent相互协作,以相似度计算作为分群的依据,考虑每个实体Agent的地形、相互间机动性能等因素,提出各自的分群方案,由管理Agent分发数据并合并结果。模拟结果表明,该方法能够解决传统方法在地形分割中的分群错误问题。

关键词: 多Agent, 目标分群, 态势识别, 道路匹配, 相似度计算

Abstract: A method that uses multi-Agent to resolve the situation recognition problem in land battle is given. The method uses two kinds Agent, management Agent and entity Agent. These two kinds Agent work together to solve this complex problem. Entity Agent calculates similarity that considers terrain and motive ability of other Agent nearby it, and gives a result of target grouping, management Agent distributes information data and union result of entity Agent. Simulation result shows that this method can solve grouping problems of terrain segmentation by traditional methods.

Key words: multi-Agent, target grouping, situation recognition, road matching, similarity computing

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