A5011954555- Terahertz technology and applications
- Advanced Optical Sensing Technologies
- Optical Systems and Laser Technology
- Advanced X-ray Imaging Techniques
- Advanced Fiber Laser Technologies
- Advanced SAR Imaging Techniques
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Indoor and Outdoor Localization Technologies
- Sparse and Compressive Sensing Techniques
- Photonic and Optical Devices
- Superconducting and THz Device Technology
- Antenna Design and Optimization
- Underwater Acoustics Research
National University of Defense Technology
2021-2024
A scanning radar based on terahertz metamaterial phased array (TMPA) is a novel system for forward-looking imaging. In this paper, waveform optimization method random hopping frequency (RHF) and amplitude modulation proposed to improve the performance of TMPA imaging radars. The RHF signal employed reduce sidelobes range ambiguity function improving measurement accuracy in range, while applied optimize convolution matrix composed samples antenna pattern, thereby enhancing azimuth...
In this paper, a forward-looking three-dimensional (3D) imaging method based on data-driven approach is proposed. The proposed adopts single-input-single-output (SISO) terahertz radar to obtain the one-dimensional range profile of target. 3D image then retrieved from using multi-layer perception (MLP) algorithm. Simulations and experiments are carried out demonstrate feasibility method.
Metamaterial-based coded aperture imaging (MCAI) is a forward-looking radar technique based on wavefront modulation. The scattering coefficients of the target can resolve as an ill-posed inverse problem. Data-based deep-learning methods provide efficient, but expensive, way for reconstruction. To address difficulty in collecting paired training data, untrained deep radar-echo-prior-based MCAI (DMCAI) optimization model proposed. DMCAI combines with modified U-Net predicting echo. A joint...
Phaseless terahertz coded-aperture imaging (PL-TCAI) is a promising radar technology that leverage the coded aperture antenna and phase recovery algorithm to achieve high-resolution, forward-looking staring without relying on relative motion. As known, it severely ill-conditioned inverse problem solve target scattering coefficient only from intensity measurements. To relieve illnesses reduce demand for measurements reconstruction, PL-TCAI method based generative model proposed. This utilizes...
Terahertz single-photon radar is a promising technique with extremely low noise level and fairly high detection sensitivity. In this paper, we propose 3D imaging method for terahertz without scanning wavefront modulation. The proposed utilizes single input output (SISO) architecture to obtain the photon-counting histograms of target, adopts Multilayer Perceptron (MLP) algorithm recover image from histogram. Theoretical analyses simulation experiments are implemented demonstrate feasibility method.
In this paper, a resolution analysis method for coded-aperture imaging (CAI) system based on statistical theory is proposed the first time. The energy-to-noise ratio (ENR) introduced into evaluation latest theoretical results of CAI system. two points closely in space transformed decision problem. minimum error probability (MEP) criterion Bayesian classification and correlation pattern spatial reference signal are utilized to fit curve which finally turns out be right-tailed function...
In this paper, to address the long-distance imaging problems, a novel forward-looking three-dimensional (3D) method based on terahertz single-photon radar is presented. The SISO architecture system and adopts data-driven approach named scaling training. training, by parameters of scene be imaged, parameter constructed, then it utilized collect training data train Artificial Neural Network (ANN) model. Once completed, 3D image can retrieved using ANN model from solely 1D photon-counting...
In this work, we propose a phaseless terahertz coded-aperture imaging (PL-TCAI) method, which is able to achieve high-resolution reconstruction of the target at low intensity measurements and signal-to-noise ratio (SNR) by utilizing compensating phase information deep generative model. Simulation experiments show that proposed method has competitive performance compared with state-of-the-art algorithms.