Detection and Parameter Extraction of Low Probability of Intercept Radar Signals using the Hough Transform

Daniel L. Stevens, S. Schuckers
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引用次数: 2

Abstract

Digital intercept receivers are currently moving away from Fourier-based analysis and towards classical time-frequency analysis techniques, such as the Wigner-Ville distribution, Choi- Williams distribution, spectrogram, and scalogram, for the purpose of analyzing low probability of intercept radar signals (e.g. triangular modulated frequency modulated continuous wave and frequency shift keying). Although these classical time-frequency techniques are an improvement over the Fourier-based analysis, they still suffer from a lack of readability, due to cross-term interference, and a mediocre performance in low SNR environments. This lack of readability may lead to inaccurate detection and parameter extraction of these radar signals. In this paper, the use of the Hough transform, because of its ability to suppress cross-term interference, separate signals from cross-terms, and perform well in the presence of noise, is proposed as an improved signal analysis technique. With these qualities, the Hough transform has the potential to produce better readability and consequently, more accurate signal detection and parameter extraction metrics.
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基于霍夫变换的低概率截获雷达信号检测与参数提取
数字截获接收机目前正从基于傅里叶的分析转向经典时频分析技术,如Wigner-Ville分布、Choi- Williams分布、频谱图和尺度图,以分析低概率截获雷达信号(如三角调制频率调制连续波和频移键控)。尽管这些经典时频技术是对基于傅立叶的分析的改进,但由于交叉项干扰,它们仍然缺乏可读性,并且在低信噪比环境中性能一般。这种可读性的缺乏可能导致这些雷达信号的不准确检测和参数提取。在本文中,由于霍夫变换能够抑制交叉项干扰,从交叉项中分离信号,并且在存在噪声的情况下表现良好,因此提出了霍夫变换作为一种改进的信号分析技术。有了这些特性,霍夫变换有可能产生更好的可读性,因此,更准确的信号检测和参数提取指标。
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