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Signal Processing of Ground Penetrating Radar Using Spectral Estimation Techniques to Estimate the Position of Buried Targets

机译:利用频谱估计技术估计地面穿透雷达信号的埋入目标位置

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摘要

Super-resolution is very important for the signal processing of GPR (ground penetration radar) to resolve closely buried targets. However, it is not easy to get high resolution as GPR signals are very weak and enveloped by the noise. The MUSIC (multiple signal classification) algorithm, which is well known for its super-resolution capacity, has been implemented for signal and image processing of GPR. In addition, conventional spectral estimation technique, FFT (fast Fourier transform), has also been implemented for high-precision receiving signal level. In this paper, we propose CPM (combined processing method), which combines time domain response of MUSIC algorithm and conventional IFFT (inverse fast Fourier transform) to obtain a super-resolution and high-precision signal level. In order to support the proposal, detailed simulation was performed analyzing SNR (signal-to-noise ratio). Moreover, a field experiment at a research field and a laboratory experiment at the University of Electro-Communications, Tokyo, were also performed for thorough investigation and supported the proposed method. All the simulation and experimental results are presented.
机译:超分辨率对于GPR(地面穿透雷达)的信号处理以解决紧密掩埋的目标非常重要。但是,由于GPR信号非常弱并且被噪声包围,因此要获得高分辨率并不容易。以其超分辨率能力而闻名的MUSIC(多种信号分类)算法已用于GPR的信号和图像处理。此外,传统的频谱估计技术FFT(快速傅立叶变换)也已实现用于高精度接收信号电平。在本文中,我们提出了CPM(组合处理方法),该方法将MUSIC算法的时域响应与常规IFFT(快速傅里叶逆变换)相结合,以获得超高分辨率和高精度信号电平。为了支持该建议,对SNR(信噪比)进行了详细的仿真分析。此外,还进行了研究领域的现场实验和东京电子通信大学的实验室实验,以进行全面研究,并支持所提出的方法。给出了所有的仿真和实验结果。

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