Radar emitter identification based on EPSD-DFN

被引:0
作者
Jin, Qiu [1 ]
Wang, Hongyan [1 ]
Yang, Kaizhi [1 ]
机构
[1] Space Engn Univ, Beijing 101416, Peoples R China
来源
PROCEEDINGS OF 2018 IEEE 3RD ADVANCED INFORMATION TECHNOLOGY, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IAEAC 2018) | 2018年
关键词
radar emitter identification; estimation parameter s ample diagram (EPSD); Deep Feedforward Network (DFN); nume rical sequence;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Aimed at the problem that the radar emitter characteristic parameters are not fully used in the identification process and the stability of the radar parameter of sample map is not stable enough, the estimation parameter sample diagram (EPSD) is used to describe the characteristic parameter description model of the radar radiant source. A radar emitter identification method combining EPSD with Deep Feedforward Network (DFN) is proposed. By calculating the statistic corresponding to the numerical sequence in the radar emitter parameter of sample map, the numerical sequence is replaced by the obtained statistic in the parameter sample diagram, thus the parameter sample map mixed with the numerical and numerical sequence is simplified as the estimation parameter sample diagram. DFN is used to train the training samples of EPSD, and network precision adjustment is achieved through test results. Simulation results verify the effectiveness and stability of the PESM-DFN method.
引用
收藏
页码:360 / 363
页数:4
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