Radar signal recognition based on time-frequency representations and multidimensional probability density function estimator

K. Konopko, Y. Grishin, D. Janczak
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引用次数: 16

Abstract

A radar signal recognition can be accomplished by exploiting the particular features of a radar signal observed in presence of noise. The features are the result of slight radar component variations and acts as an individual signature. The paper describes radar signal recognition algorithm based on time frequency analysis, noise reduction and statistical classification procedures. The proposed method is based on the Wigner-Ville Distribution with using a two-dimensional denoising filter which is followed by a probability density function estimator which extracts the features vector. Finally the statistical classifier is used for the radar signal recognition. The numerical simulation results for the P4-coded signals are presented.
基于时频表示和多维概率密度函数估计的雷达信号识别
雷达信号识别可以通过利用在存在噪声的情况下观察到的雷达信号的特定特征来完成。这些特征是雷达成分轻微变化的结果,并作为单独的特征。介绍了基于时频分析、降噪和统计分类程序的雷达信号识别算法。该方法基于Wigner-Ville分布,使用二维去噪滤波器,然后使用概率密度函数估计器提取特征向量。最后将统计分类器用于雷达信号识别。给出了p4编码信号的数值模拟结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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