Target parameter extraction based on neural network and scattering center model

被引：0
|
作者：
Luo Y. [1 ]
Chen Y. [1 ]
Guo K. [1 ]
Sheng X. [1 ]
Ma J. [2 ]
机构：
[1] Institute of Applied Electromagnetics, School of Information and Electronics, Beijing
[2] Beijing Simulation Center, Beijing
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2023年 / 45卷 / 01期
关键词：
neural network; parameter extraction; scattering center; time-frequency characteristics;
D O I：
10.12305/j.issn.1001-506X.2023.01.02
中图分类号：
学科分类号：
摘要：
Target geometry extraction from radar echoes are often subject to high computational cost, non-linearity, and other difficulties. In this paper, based on convolutional neural network and back propagation neural network, a method is proposed to automatically identify the target pattern and extract the target geometry parameters from the time-frequency image characteristics of scattering center. Since the construction of a neural network requires a large number of training data samples, and the computation of the scattering field of the extended target is very time-consuming, the scattering center model established based on the known target is used in this paper to quickly generate large sample training data, which effectively solves the problem of obtaining training samples. Taking warhead targets as an example, the neural networks are established, and the effectiveness of the proposed method is verified by numerical experiment results. © 2023 Chinese Institute of Electronics. All rights reserved.
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页码：9 / 14
页数：5
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