现代防御技术 ›› 2021, Vol. 49 ›› Issue (3): 73-79.DOI: 10.3969/j.issn.1009-086x.2021.03.009

• 指挥控制与通信 • 上一篇    下一篇

基于OKNN的目标战术意图识别方法

刘秋辉, 崇元   

  1. 中国人民解放军91550部队,辽宁 大连 116023
  • 收稿日期:2020-12-08 修回日期:2021-01-02 出版日期:2021-06-20 发布日期:2021-07-12
  • 通讯作者: 116023 辽宁省大连市91550部队42分队 E-mail:chongyuan_2008@126.com
  • 作者简介:刘秋辉(1974-),男,黑龙江铁力人。高工,硕士,研究方向为智能决策与辅助分析。
  • 基金资助:
    “十三五”预研共用技术(41416030204)

Tactical Intention Recognition Based on Operation Knowledge Neural Network

LIU Qiu-hui, CHONG Yuan   

  1. PLA,No.91550 Troop,Liaoning Dalian 116023,China
  • Received:2020-12-08 Revised:2021-01-02 Online:2021-06-20 Published:2021-07-12

摘要: 战术级意图识别为指挥员理解战场态势,制定接下来的作战计划提供辅助决策。意图识别模型的构建是态势分析过程中实体行为建模的难点之一。针对传统战术意图识别方法中战场态势不确定性的集成与传递,以及推理模板固化问题,在以获取目标动态作战知识用于解释敌方作战行动过程中行动要素的基础上,构建了目标战术意图推理框架;根据作战计划制定特点,提出了基于作战知识神经网络(operation knowledge neural network,OKNN)的目标战术意图识别方法。OKNN以空中目标群为单位,通过实时动态建立基于作战知识的实体片段集来增强模型推理的灵活性,模型基于经验的训练样本计划库,可动态自适应的调整目标战术意图空间分布结果,大大消减了不确定性的集成与传递。最后通过仿真实验验证了模型的有效性。

关键词: 意图识别, 计划推理, 作战知识, 神经网络, 战术行动过程

Abstract: Tactical intention recognition provides decision support for commanders to understand the battlefield posture and develop the plan operations.How to structure intention recognition is a challenging problem in situation analysis.Aiming at the integration and transmission of battlefield situational uncertainty in traditional tactical intent recognition methods and the solidification of inference templates,a target tactical intent inference framework is constructed based on the acquisition of dynamic operational knowledge of the target for explaining the operational elements in the course of enemy combat operations.Based on the characteristics of combat plan,a target tactical intention recognition method based on operational knowledge neural network (OKNN) is proposed. OKNN takes the air target group as the unit and enhances the flexibility of model reasoning by dynamically building a set of entity fragments based on operational knowledge in real time.The model is based on an empirical training sample plan library,which can dynamically and adaptively adjust the spatial distribution of target tactical intent results,greatly eliminating the integration and transmission of uncertainty.The simulation results indicate that the reasoning model is feasible and effective.

Key words: intention recognition, plan reasoning, operation knowledge, neural network, tactical operation process

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