High Sparsity and Low Sidelobe Near-field Focused Sparse Array for Three-Dimensional Imagery

YANG Lei; SONG Hao; SHEN Ruiyang; CHEN Yingjie; HU Zhongwei; HUO Xin; XING Mengdao

doi:10.11999/JEIT231278

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YANG Lei, SONG Hao, SHEN Ruiyang, CHEN Yingjie, HU Zhongwei, HUO Xin, XING Mengdao. High Sparsity and Low Sidelobe Near-field Focused Sparse Array for Three-Dimensional Imagery[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT231278

Citation:

YANG Lei, SONG Hao, SHEN Ruiyang, CHEN Yingjie, HU Zhongwei, HUO Xin, XING Mengdao. High Sparsity and Low Sidelobe Near-field Focused Sparse Array for Three-Dimensional Imagery[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT231278

Citation:

YANG Lei, SONG Hao, SHEN Ruiyang, CHEN Yingjie, HU Zhongwei, HUO Xin, XING Mengdao. High Sparsity and Low Sidelobe Near-field Focused Sparse Array for Three-Dimensional Imagery[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT231278

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High Sparsity and Low Sidelobe Near-field Focused Sparse Array for Three-Dimensional Imagery

doi: 10.11999/JEIT231278

1.
College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China
2.
National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China

Funds: The National Natural Science Foundation of China (62271487)

Received Date: 2023-11-20
Rev Recd Date: 2024-11-11

Available Online: 2024-11-19

Abstract

Abstract

In active electrical scanning millimeter-wave security imaging, the uniform array antenna has the bottleneck of uncontrolled cost and high complexity, which is difficult to be widely applied in practices. To this end, a near-field focused sparse array design algorithm for high sparsity and low sidelobes is proposed in this paper. It applies an improved three dimensional (3D) time-domain imaging algorithm to achieve high-accuracy 3D reconstruction. Firstly, the near-field focusing sparse array antenna model is constructed by taking the near-field focusing position and peak sidelobe level as constraints, where the $ {\ell _p} $(0<$ p $<1) norm of the weight vector regularization is established as the objective function. Secondly, by introducing auxiliary variables and establishing equivalent substitution models between sidelobe and focus position constraints and auxiliary variables, the problem of solving the array weight vector in the coupling of the objective function and complex constraints is developed. The model is simplified and solved through the idea of equivalent substitution. Then, the array excitation and position are optimized using a combination of complex number differentiation and heuristic approximation methods. Finally, the Alternating Direction Method of Multipliers (ADMM) is employed to achieve the focus position, peak sidelobe constraint, and array excitation in a cooperative manner. The sparse array 3D imaging is realized by improving the 3D time-domain imaging algorithm. The experimental results show that the proposed method is capable of obtaining lower sidelobe level with fewer array elements under the condition of satisfying the radiation characteristics of array antenna and near-field focusing. Applying raw millimeter-wave data, the advantages of sparse array 3D time-domain imaging algorithm are verified in terms of high accuracy and high efficiency.
- Near field imaging,
- Sparse array,
- Three-dimensional imaging,
- Alternating Direction Method of Multipliers (ADMM)

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References(24)

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