Abstract-Broadband stepped-frequency modulated continuous terahertz wave tomography for non-destructive inspection of polymer materials

Xiaoxuan Zhang, Qijia Guo, Tianying Chang, Hong-Liang Cui,


https://www.sciencedirect.com/science/article/pii/S0142941818320683

An all-solid-state electronic three-dimensional terahertz tomography system designed specifically for non-destructive inspection of polymer materials is demonstrated, which is capable of determining the positions and shapes of hidden defects accurately. The imaging radar system, based on stepped-frequency modulated continuous wave (SFMCW), with center frequency at 180 GHz, bandwidth of 60 GHz, and average power 0.5 mW, is tested against thick Teflon (polytetrafluoroethylene, PTFE) plates with internal voids as samples. The locations and shapes of the hidden holes are obtained in both electromagnetic simulation and experimental measurements with a three-dimensional image reconstruction algorithm, which features advantages of accurate reconstructed image details and fast computation speed, demonstrating that the terahertz imaging radar system combined with the algorithm developed is capable of detecting internal defects of thick polymers. Key resolution parameters are established experimentally in detail, demonstrating 2.5 mm and 1.7 mm range resolutions in free space and in Teflon separately, and lateral spot diameters ranging from 3.4 mm to 8 mm at imaging distances from 5 mm to 60 mm.

Abstract-Reliable Origin Identification of Scutellaria Baicalensis Based on Terahertz Time-Domain Spectroscopy and Pattern Recognition

Jie Liang, Qijia Guo, Tianying Chang, Ke Li, Hong-Liang Cui



https://www.sciencedirect.com/science/article/pii/S0030402618311574

An effective approach for identification of the origin of Scutellaria baicalensis, an essential member of the family of Chinese herbal medicine and known to be an effective anti-inflammatory, is proposed based on terahertz time-domain spectroscopy (THz-TDS) and pattern recognition. Terahertz absorption spectra of Scutellaria baicalensis collected from its main growth areas in China, including Inner Mongolia, Shanxi and Shaanxi are investigated using the proposed method, in the frequency range from 0.2 to 1.7 THz. To reduce the dimensionality of the original spectral data and extract useful features of the data, principal component analysis is employed. The matrix of the selected principal component scores is fed into a classification model established by support vector machines. We use the particle swarm optimization to optimize the parameters of the classification model to achieve an identification rate of 95.56% for the samples, demonstrating that terahertz time-domain spectroscopy combined with particle swarm-support vector machines approach can be efficiently utilized for automatic identification of the origin of Scutellaria baicalensis.

Abstract-Hilbert-Transform-Based Accurate Determination of Ultrashort-Time Delays in Terahertz Time-Domain Spectroscopy

Tianying Chang ;  Qijia Guo ;  Lingyu Liu ;  Hong-Liang Cui

http://ieeexplore.ieee.org/document/7951024/

Accurate determination of time delays is crucial for distinguishing a sample's different interfaces in terahertz time-domain spectroscopy (THz-TDS), especially for ultrathin samples or interfacial gaps. In this paper, Hilbert transform (HT) is invoked, along with posttransform signal spectral estimation of several varieties, including the conventional, that based on multiple-signal classification spectrum estimation (HT-MUSIC), and that based on autoregressive spectrum estimation using Yule–Walker law (HT-AR), to determine the sample's different interfaces. The results are compared with the traditional method of obtaining time delays in THz-TDS, along with analysis of the resolution and accuracy, as well as advantages and deficiencies of the various approaches. It is demonstrated that HT is an effective method for determining different interfaces of an ultrathin sample by simulation and experiments. The simulation results show that MUSIC-HT has the best resolution, at about 0.35 ps and AR-HT has the best accuracy, whose error is less than 0.075 ps. Experimental results for ultrathin air gaps and polymer films confirmed that MUSIC-HT can distinguish time delays as short as 0.44 ps from the THz time-domain spectra.

Abstract-A High Precision Terahertz Wave Image Reconstruction Algorithm

Qijia Guo 1, Tianying Chang 1,2,*, Guoshuai Geng 1, Chengyan Jia 1 and Hong-Liang Cui 1

1

School of Instrumentation Science and Electrical Engineering, Jilin University, Changchun 130012, China

2

Institute of Automation, Shandong Academy of Sciences, Jinan 250014, China

*

Correspondence: Tel.: +86-186-1251-9976

Academic Editors: Vincenzo Spagnolo and Dragan Indjin

http://www.mdpi.com/1424-8220/16/7/1139/htm

With the development of terahertz (THz) technology, the applications of this spectrum have become increasingly wide-ranging, in areas such as non-destructive testing, security applications and medical scanning, in which one of the most important methods is imaging. Unlike remote sensing applications, THz imaging features sources of array elements that are almost always supposed to be spherical wave radiators, including single antennae. As such, well-developed methodologies such as Range-Doppler Algorithm (RDA) are not directly applicable in such near-range situations. The Back Projection Algorithm (BPA) can provide products of high precision at the the cost of a high computational burden, while the Range Migration Algorithm (RMA) sacrifices the quality of images for efficiency. The Phase-shift Migration Algorithm (PMA) is a good alternative, the features of which combine both of the classical algorithms mentioned above. In this research, it is used for mechanical scanning, and is extended to array imaging for the first time. In addition, the performances of PMA are studied in detail in contrast to BPA and RMA. It is demonstrated in our simulations and experiments described herein that the algorithm can reconstruct images with high precision.