摘要
在现代战争中,各种新型电子设备及武器使用愈发广泛,战场环境越来越复杂。雷达侦察担负着无可替代的任务。通常只能通过人工经验的方式对雷达功能进行辨识,这显然不能满足现代战争需求。利用聚类等数学方法对截获信号进行分类,然后结合参数划分及幅度统计分布情况对雷达搜索、跟踪波形进行自动识别,推断雷达工作模式。这种识别方法适用于多平台雷达,运算量小,易于实现。仿真结果验证了该方法的有效性及可行性。
In modern warfare, new types of electronic equipment and weapons have been widely used, and the environment of war is becoming more and more complex and changeable. Radar reconnaissance is an irreplaceable task. Radar function can only be identified by artificial experience, which obviously can’t satisfy the requirement of modern warfare. In this paper, the intercepted signals are classified by clustering and other mathematical methods. Then based on the division of parameters and the distribution of amplitude statistics, the waveforms of radar for searching and tracking are automatically identified. The recognition of work mode will be realized. This method can be applied to the multi-platform radars and has a low computation, which is easy to realize. Simulation results show the effectiveness and feasibility of the method.
作者
林龙
吴碧
LIN Long;WU Bi(91388 Unit of PLA,Zhanjiang 524022,China)
出处
《指挥控制与仿真》
2020年第2期65-69,共5页
Command Control & Simulation
关键词
聚类
脉冲幅度
正态分布
工作模式
clustering
pluses amplitude
normal distribution
work mode
