Junliang Dong, Xiaolong Wu, Alexandre Locquet, David S. Citrin,
http://ieeexplore.ieee.org/document/7874211/
Terahertz sparse deconvolution based on an iterative shrinkage algorithm is presented in this study to characterize multilayered structures. With an upsampling approach, sparse deconvolution with superresolution is developed to overcome the time resolution limited by the sampling period in the measurement and increase the precision of the estimation of echo arrival times. A simple but effective time-domain model for describing the temporal pulse spreading due to the frequency-dependent loss is also designed and introduced into the algorithm, which greatly improves the performance of sparse deconvolution in processing time-varying pulses during the propagation of terahertz waves in materials. Numerical simulations and experimental measurements verify the algorithms and show that sparse deconvolution can be considered as an effective tool for terahertz nondestructive characterization of multilayered structures.
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