基于深度神经网络的雷达信号识别

J. Matuszewski, Dymitr Pietrow
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引用次数: 0

摘要

本文提出了基于脉冲重复间隔、脉冲持续时间、射频频率和脉冲间时间结构等雷达参数,利用多层人工神经网络识别雷达信号源的问题。以实际雷达信号的参数作为训练数据集。利用仿真环境验证了该方法的正确性,验证了该方法在多个相互干扰的雷达信号存在以及噪声和干扰环境下的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Radar Signal Recognition Based on Deep Neural Networks
The article presents the problem of recognizing radar sources using multilayer artificial neural networks on the basis of radar parameters such as pulse repetition interval, pulse duration, radio frequency, and inter-pulse temporal structure of signals generated by these sources. Parameters of real radar signals were used as a set of training data. The correctness of the operation was tested using a simulation environment that verified the effectiveness of operation in the conditions of the presence of many radar signals that interfere with each other and in the environment of noise and interferences.
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