11 December 2018 Microwave computational imaging in frequency domain with reprogrammable metasurface
Zhenlong Luo, Yongqiang Cheng, Kaicheng Cao, Yuliang Qin, Hongqiang Wang
Author Affiliations +
Abstract
Recently, microwave computational imaging systems have had various applications ranging from security screening to biomedical diagnosis. However, existing methods are sensitive to noise and have a heavy computational burden in a three-dimensional (3-D) imaging scene. A computational imaging method approached in frequency domain is proposed, which improves imaging quality under noisy conditions and reduces computation complexity. The signal-to-noise ratio of the echo signal is improved by dechirping pulse compression method, which obtains the range resolution concurrently. According to the information of range resolution, the scene is divided into some range bins. With computational imaging algorithms, the azimuth and elevation resolution are obtained in each range bin by spatially diverse patterns of reprogrammable metasurface. A sparse 3-D image can be obtained by combining the reconstructed subimages. The simulation result shows that the proposed method outperforms the conventional methods with better antinoise ability and lower computational complexity in sparse 3-D scene imaging.
© 2018 SPIE and IS&T 1017-9909/2018/$25.00 © 2018 SPIE and IS&T
Zhenlong Luo, Yongqiang Cheng, Kaicheng Cao, Yuliang Qin, and Hongqiang Wang "Microwave computational imaging in frequency domain with reprogrammable metasurface," Journal of Electronic Imaging 27(6), 063019 (11 December 2018). https://doi.org/10.1117/1.JEI.27.6.063019
Received: 2 July 2018; Accepted: 13 November 2018; Published: 11 December 2018
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CITATIONS
Cited by 7 scholarly publications.
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KEYWORDS
Computational imaging

Microwave radiation

Signal to noise ratio

3D image processing

Reconstruction algorithms

Detection and tracking algorithms

Imaging systems

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