最小均值交叉熵的时频峰值滤波在探地雷达信号去噪中的应用
Application of time-frequency peak filtering with minimum mean cross-entropy in ground penetrating radar signal denoising
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摘要: 在探地雷达的实际探测作业中,环境噪声与仪器误差等不利因素常导致信号中混杂大量噪声,严重削弱了信号品质及分析结果的可信度。鉴于此,提出了一种融合最小均值交叉熵的时频峰值滤波方法(TFPF-MMCE)用于探地雷达信号的去噪处理。该方法将时频峰值滤波技术与交叉熵函数相结合,通过精准优化信号的时频表征,实现了对噪声的有效抑制与有效信号的精准保留,从而显著提升了探地雷达信号的质量。通过数值模拟与实地探地雷达实验验证,TFPF-MMCE具有很好的噪声去除能力,能够有效去除信号中的随机噪声,显著提升了信号的清晰度与可靠性。相较于传统的去噪方法,TFPF-MMCE在去噪效果与抗噪稳定性上均展现出显著优势,预示着其在探地雷达信号处理领域的广泛应用前景与重要实践价值。Abstract: In practical detection operations using ground-penetrating radar (GPR), factors such as environmental noise and instrument errors frequently cause signals to be mixed with substantial noise, seriously reducing signal quality and the reliability of analytical results. To address this issue, this study proposed a time-frequency peak filtering method combined with minimum mean cross-entropy (TFPF-MMCE) for denoising GPR signals. This method combined time-frequency peak filtering with the cross-entropy function, enabling effective noise suppression and precise preservation of valid signals through precise optimization of the time-frequency representation, thereby significantly improving the quality of GPR signals. Numerical simulation and field GPR experiments validated that the TFPF-MMCE method exhibited a high noise removal capability and, thus, can effectively eliminate random noise while significantly improving signal clarity and reliability. Compared to traditional denoising methods, TFPF-MMCE shows significant advantages in denoising effectiveness and noise resistance stability, suggesting promising application potential and practical value in the field of GPR signal processing.
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