Compressed Sensing for THz FMCW Radar 3D Imaging

A terahertz (THz) frequency-modulated continuous wave (FMCW) imaging radar system is developed for high-resolution 3D imaging recently. Aiming at the problems of long data acquisition periods and large sample sizes for the developed imaging system, an algorithm based on compressed sensing is propose...

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Bibliographic Details
Published inComplexity (New York, N.Y.) Vol. 2021; no. 1
Main Authors Gu, Shanshan, Xi, Guangrong, Ge, Lingyu, Yang, Zhong, Wang, Yizhi, Chen, Weina, Yu, Zhenzhong
Format Journal Article
LanguageEnglish
Published Hoboken Hindawi 2021
Hindawi Limited
Wiley
Subjects
Algorithms
Bandwidths
Continuous radiation
Efficiency
Fourier transforms
Image reconstruction
Image resolution
Imaging radar
Radar
Radar equipment
Radar imaging
Signal processing
Three dimensional imaging
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Summary:A terahertz (THz) frequency-modulated continuous wave (FMCW) imaging radar system is developed for high-resolution 3D imaging recently. Aiming at the problems of long data acquisition periods and large sample sizes for the developed imaging system, an algorithm based on compressed sensing is proposed for THz FMCW radar 3D imaging in this paper. Firstly, the FMCW radar signal model is built, and the conventional range migration algorithm is introduced for THz FMCW radar imaging. Then, compressed sensing is extended for THz FMCW radar 3D imaging, and the Newton smooth L0-norm (NSL0) algorithm is presented for sparse measurement data reconstruction. Both simulation and measurement experiments demonstrate the feasibility of reconstructing THz images from measurements even at the sparsity rate of 20%.
ISSN:1076-2787
1099-0526
DOI:10.1155/2021/5576782