Abstract
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%.
Highlights
Terahertz (THz) wave lies between infrared wave and millimeter wave, which is an electromagnetic wave that has not been fully recognized and utilized by human beings
Because the recovery accuracy of greedy search reconstruction algorithms like orthogonal matching pursuit (OMP) [14, 15], stage-wise orthogonal matching pursuit (StOMP) [16], regularized orthogonal matching pursuit (ROMP) [17], and compressive sampling matching pursuit (CoSaMP) [18] is poor with lower signal noise ratio (SNR), an improved smoothed L0-norm minimization (SL0) algorithm based on the convex optimization is presented in this paper
An algorithm for THz frequencymodulated continuous wave (FMCW) synthetic aperture radar (SAR) imaging based on compressed sensing is investigated in this paper. e developed 220 GHz FMCW imaging radar system is introduced, and the signal model is built firstly
Summary
Terahertz (THz) wave lies between infrared wave and millimeter wave, which is an electromagnetic wave that has not been fully recognized and utilized by human beings. An active FMCW imaging system ranging from 514 to 565 GHz (frequency centered at 540 GHz) is studied to image objects with a resolution of millimeter [8]. Imaging algorithms in the time domain have a heavy calculation burden though they are able to process SAR data under a great variety of imaging geometries. The range migration algorithm (RMA) in wavenumber domain is preferable for THz FMCW SAR imaging [8, 13]. A single transceiver is moved in a grid-like manner to acquire data for THz FMCW SAR imaging in most cases. To reduce imaging data acquirement time and to improve imaging efficiency, an algorithm based on compressed sensing is proposed for 3D imaging of THz FMCW SAR in this paper.
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