在无混叠探地雷达调查中防止幅度失真的采样率最小阈值

M. Dossi, E. Forte, M. Pipan
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引用次数: 0

摘要

我们研究了无混叠GPR数据集中与采样相关的幅度失真,并将其与影响记录信号的其他因素进行了比较。特别地,我们分析了采样的峰值振幅在不同采样率下的变化。,并建议采样率的最小阈值,以便将最大峰值幅度误差包含在可接受的范围内。数据采集过程中采样率的选择通常基于奈奎斯特-香农定理。,它提供了实用的下限,以避免混叠效应,并准确地保留原始模拟信号的频谱内容。然而。,我们证明Nyquist-Shannon定理不能防止可能的振幅失真。即使在无混叠的数据集中,也可能发生重大且不可恢复的数据丢失。我们还表明插值和重采样只能提供有限的解决方案。,因为重构信号的精度取决于所实现的插值方法。,而随后的重新采样只是重新引入了最初的问题。根据我们的分析。,我们建议在数据采集期间使用至少等于信号中心频率12倍的采样率。,这比普遍采用的标准要高。,以便将最大峰值幅度误差限制在5%以内。
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Minimum threshold for the sampling rate to prevent amplitude distortions in aliasing-free GPR surveys
We study sampling-related amplitude distortions within aliasing-free GPR data sets, and compare them with other factors which can affect the recorded signal. In particular, we analyze how much the sampled peak amplitudes can change with different sampling rates., and recommend a minimum threshold for the sampling rate in order to contain the maximum peak amplitude error within acceptable limits. The selection of the sampling rate during data acquisition is commonly based on the Nyquist-Shannon theorem., which offers practical lower limits in order to avoid aliasing effects and to accurately preserve the spectral content of the original analog signal. However., we show that the Nyquist-Shannon theorem does not prevent possible amplitude distortions., and that significant and unrecoverable data loss can occur even in aliasing-free data sets. We also show that interpolation and re-sampling offer only limited solutions., since the accuracy of the reconstructed signal depends on the implemented interpolation method., while its subsequent resampling simply reintroduces the initial problem. Based on our analysis., we recommend using during data acquisition a sampling rate equal to at least 12 times the signal central frequency., which is higher than the commonly adopted standards., in order to limit the maximum peak amplitude error within 5%.
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