基于迭代字典更新的稀疏信号处理的电介质材料表征
Characterization of Dielectric Materials by Sparse Signal Processing with Iterative Dictionary Updates
摘要：
在许多应用中，在不对被测材料（MUT）造成损坏的情况下估计各种材料的参数和性质是重要的。因此，在这封信中，我们通过无线传感来解决这个问题。这里，估计的准确性取决于对来自MUT的反射信号的属性的准确估计（例如，反射次数、它们的幅度和时间延迟）。对于分层MUT，存在多个反射，并且由于接收器处的有限带宽，这些反射彼此重叠。由于来自MUT的反射的数量是有限的，我们提出稀疏信号处理（SSP）来分解反射信号。在SSP中，需要所谓的字典来获得信号的稀疏表示。在这里，而不是一个固定的字典，字典更新技术，提出了改善反射信号的估计。为了验证所提出的方法，使用基于矢量网络分析仪（VNA）的测量设置。结果表明，估算的介电常数与文献报道的MUT的介电常数非常一致。此外，所提出的方法优于最先进的基于模型的曲线拟合方法在厚度估计。
英文摘要：
Estimating parameters and properties of various materials without causing damage to the material under test (MUT) is important in many applications. Thus, in this letter, we address this by wireless sensing. Here, the accuracy of the estimation depends on the accurate estimation of the properties of the reflected signal from the MUT (e.g., number of reflections, their amplitudes and time delays). For a layered MUT, there are multiple reflections and, due to the limited bandwidth at the receiver, these reflections superimpose each other. Since the number of reflections coming from the MUT is limited, we propose sparse signal processing (SSP) to decompose the reflected signal. In SSP, a so called dictionary is required to obtain a sparse representation of the signal. Here, instead of a fixed dictionary, a dictionary update technique is proposed to improve the estimation of the reflected signal. To validate the proposed method, a vector network analyzer (VNA) based measurement setup is used. It turns out that the estimated dielectric constants are in close agreement with the dielectric constants of the MUTs reported in literature. Further, the proposed approach outperforms the state-of-the-art model-based curve-fitting approach in thickness estimation.
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