超视距空战战术控制距离解算研究  

A Study on Calculation of Tactical Control Range in Beyond Visual Range Air Combat

作　　者：张洁[1] 高伟男 ZHANG Jie;GAO Weinan(Chinese Flight Test Establishment,Xi'an Shaanxi 710089,China;Nanjing Research Institute of Electronics Technology,Nanjing Jiangsu 210039,China)

机构地区：[1]中国飞行试验研究院,陕西西安710089 [2]南京电子技术研究所,江苏南京210039

出　　处：《现代雷达》2023年第7期28-32,共5页Modern Radar

摘　　要：现代空战信息复杂度日益提升,传统空战行为量化指标仅能单一地从进攻角度为飞行员提供信息支撑,难以满足现代空战的决策要求。针对这一问题,文中结合空战行为过程与常见战术策略的分析,提出了战术控制距离(TCR)的新概念,建立了相应离线解算模型构建样本库。然后引入深度神经网络理论,设计了一种基于稀疏自编码网络(SAE)的深度拟合方法。仿真实验表明:SAE模型提高了解算精确性与时效性,其平方根均方误差控制在150 m以内,满足超视距空战火控计算误差要求;TCR有效弥补了超视距空战节点信息的缺失,为飞行员提供了更加明确、直观的决策依据,具有较强的工程实用性与有效性。With the increasing complexity of information in beyond visual range(BVR)air combat,traditional information indications can only provide support for pilots from the perspective of attack,which is difficult to meet the decision-making requirements in modern air combat.To address these problems,a new concept of tactical control range(TCR)is proposed under the consideration of escape maneuver in this paper.Firstly,the corresponding offline simulation model is given and the sample database is established.Then,fitting algorithm based on sparse auto encoder(SAE)network is designed by introducing the deep learning theory.The simulation results show that the SAE network improves the computing accuracy while greatly reducing the computing time.The simulation shows that the SAE model improves computational accuracy and timeliness,and its square root mean square error is controlled within 150 m,meeting the error requirements for BVR air combat fire control calculations.TCR can effectively makes up for the lack of information support and provide pilots with more timely decision basis in air combat,which is practical for improving the combat efficiency.

关 键 词：超视距空战 战术控制距离 深度学习 稀疏自编码网络 

分 类 号：TN958.53[电子电信—信号与信息处理]