Antenna Phase Error Compensation for Terahertz Coded-Aperture Imaging

Coded-aperture antenna plays an important role in terahertz coded-aperture imaging radar system. However, the performance of a system is inevitably affected by the phase errors introduced by the coded-aperture antenna elements. In this paper, we propose a phase error compensation method by deducing a formula to compute all element phase errors accurately. According to the formula, the phase errors can be calibrated by using a calibrator and can be used to compensate the imaging model of the system. Numerical simulations demonstrate that the proposed method can effectively improve the imaging quality when the elemental phase error exceeds 10 ∘ .

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Strip-Mode Microwave Staring Correlated Imaging with Self-Calibration of Gain–Phase Errors

Sensors ◽

10.3390/s19051079 ◽

2019 ◽

Vol 19 (5) ◽

pp. 1079 ◽

Cited By ~ 1

Author(s):

Rui Xia ◽

Yuanyue Guo ◽

Weidong Chen ◽

Dongjin Wang

Keyword(s):

Error Estimation ◽

Phase Error ◽

Super Resolution ◽

Image Splicing ◽

Initial Value ◽

Self Calibration ◽

Phase Errors ◽

Imaging Model ◽

Multiple Imaging ◽

Imaging Performance

Microwave staring correlated imaging (MSCI) can realize super resolution imaging without the limit of relative motion with the target. However, gain–phase errors generally exist in the multi-transmitter array, which results in imaging model mismatch and degrades the imaging performance considerably. In order to solve the problem of MSCI with gain–phase error in a large scene, a method of MSCI with strip-mode self-calibration of gain–phase errors is proposed. The method divides the whole imaging scene into multiple imaging strips, then the strip target scattering coefficient and the gain–phase errors are combined into a multi-parameter optimization problem that can be solved by alternate iteration, and the error estimation results of the previous strip can be carried into the next strip as the initial value. All strips are processed in multiple rounds, and the gain–phase error estimation results of the last strip can be taken as the initial value and substituted into the first strip for the correlated processing of the next round. Finally, the whole imaging in a large scene can be achieved by multi-strip image splicing. Numerical simulations validate its potential advantages to shorten the imaging time dramatically and improve the imaging and gain–phase error estimation performance.

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Phaseless Terahertz Coded-Aperture Imaging for Sparse Target Based on Phase Retrieval Algorithm

Sensors ◽

10.3390/s19214617 ◽

2019 ◽

Vol 19 (21) ◽

pp. 4617 ◽

Cited By ~ 1

Author(s):

Peng ◽

Luo ◽

Deng ◽

Wang ◽

Chen ◽

...

Keyword(s):

Phase Retrieval ◽

Computational Imaging ◽

Retrieval Algorithm ◽

Coded Aperture ◽

Imaging Method ◽

Coded Aperture Imaging ◽

Imaging Model ◽

Random Frequency ◽

Resolution Imaging ◽

Sparse Prior

Phaseless terahertz coded-aperture imaging (PL-TCAI) is a novel radar computational imaging method that utilizes the coded aperture and the incoherent detector array to achieve forward-looking and high-resolution imaging without relying on relative motion. In this paper, we propose a more reasonable and compact architecture for the PL-TCAI system and derive the imaging model of PL-TCAI based on the random frequency-hopping signal. Since most phase retrieval algorithms for PL-TCAI utilize only the intensity of echo signals to accurately reconstruct the target, excessive measurement samples are usually required. In order to reduce the number of measurement samples required for imaging, this paper proposes a sparse Wirtinger flow algorithm with optimal stepsize (SWFOS) by using the sparse prior of the target. The specific procedures of the SWFOS algorithm include the support recovery, initialization by truncated spectral method, iteration via gradient descent scheme, hard threshold operation, and stepsize optimization of iteration. Numerical simulations are performed, and the results show that the SWFOS algorithm not only has good performance for the PR problem, but can also sharply reduce the number of measurement samples required for imaging in the PL-TCAI system.

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SNR of the coded aperture imaging system

Optical Review ◽

10.1007/s10043-020-00639-z ◽

2021 ◽

Vol 28 (1) ◽

pp. 106-112

Author(s):

Jianwei Wang ◽

Yan Zhao

Keyword(s):

Image Quality ◽

Imaging System ◽

Reconstructed Image ◽

Coded Aperture ◽

Inverse Filtering ◽

Light Emitting ◽

Coded Aperture Imaging ◽

Imaging Model ◽

Better Than

AbstractIn this paper, the expression for the SNR has been developed through the imaging model. It is concluded that the image SNR decreases with the increase of the number of light-emitting points of the target under the same hardware conditions and experimental parameters. Using uniform bright squares of different sizes as the target, the SNR of the reconstructed image is calculated. Simulation and prototype experiments have proved the correctness of the conclusion. Based on this conclusion, a method of segmented area imaging is proposed to improve the reconstructed image quality. The quality of all the images using this method with Wiener inverse filtering, R-Lucy deconvolution, and ADMM is better than the image quality obtained by full-area imaging.

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