Abstract-Compressed sensing with cyclic-S Hadamard matrix for terahertz imaging applications

Esra Şengün Ermeydan,  I. Cankaya,

https://www.researchgate.net/publication/322467886_Compressed_sensing_with_cyclic-S_Hadamard_matrix_for_terahertz_imaging_applications

Compressed Sensing (CS) with Cyclic-S Hadamard matrix is proposed for single pixel imaging applications in this study. In single pixel imaging scheme, N = r · c samples should be taken for r×c pixel image where · denotes multiplication. CS is a popular technique claiming that the sparse signals can be reconstructed with samples under Nyquist rate. Therefore to solve the slow data acquisition problem in Terahertz (THz) single pixel imaging, CS is a good candidate. However, changing mask for each measurement is a challenging problem since there is no commercial Spatial Light Modulators (SLM) for THz band yet, therefore circular masks are suggested so that for each measurement one or two column shifting will be enough to change the mask. The CS masks are designed using cyclic-S matrices based on Hadamard transform for 9 × 7 and 15 × 17 pixel images within the framework of this study. The %50 compressed images are reconstructed using total variation based TVAL3 algorithm. Matlab simulations demonstrates that cyclic-S matrices can be used for single pixel imaging based on CS. The circular masks have the advantage to reduce the mechanical SLMs to a single sliding strip, whereas the CS helps to reduce acquisition time and energy since it allows to reconstruct the image from fewer samples.

Abstract-See-through Detection and 3D Reconstruction Using Terahertz Leaky-Wave Radar Based on Sparse Signal Processing

• Koji Murata, 
• Kosuke Murano, 
• Issei Watanabe, 
• Akifumi Kasamatsu, 
• Toshiyuki Tanaka, 
• Yasuaki Monnai

https://link.springer.com/article/10.1007%2Fs10762-017-0457-z

We experimentally demonstrate see-through detection and 3D reconstruction using terahertz leaky-wave radar based on sparse signal processing. The application of terahertz waves to radar has received increasing attention in recent years for its potential to high-resolution and see-through detection. Among others, the implementation using a leaky-wave antenna is promising for compact system integration with beam steering capability based on frequency sweep. However, the use of a leaky-wave antenna poses a challenge on signal processing. Since a leaky-wave antenna combines the entire signal captured by each part of the aperture into a single output, the conventional array signal processing assuming access to a respective antenna element is not applicable. In this paper, we apply an iterative recovery algorithm “CoSaMP” to signals acquired with terahertz leaky-wave radar for clutter mitigation and aperture synthesis. We firstly demonstrate see-through detection of target location even when the radar is covered with an opaque screen, and therefore, the radar signal is disturbed by clutter. Furthermore, leveraging the robustness of the algorithm against noise, we also demonstrate 3D reconstruction of distributed targets by synthesizing signals collected from different orientations. The proposed approach will contribute to the smart implementation of terahertz leaky-wave radar.