Volume 12 Issue 5
Oct.  2023
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Article Navigation >  Journal of Radars  > 2023  >  12(5): 1000-1013
Hu Ke-bin, Zhang Xiao-ling, Shi Jun, Wei Shun-jun. A High-precision Motion Compensation Method for SAR Based on Image Intensity Optimization[J]. Journal of Radars, 2015, 4(1): 60-69. doi: 10.12000/JR15007
Citation: MA Yuxin, HAI Yu, LI Zhongyu, et al. 3D high-resolution imaging algorithm with sparse trajectory for millimeter-wave radar[J]. Journal of Radars, 2023, 12(5): 1000–1013. doi: 10.12000/JR23001
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3D High-resolution Imaging Algorithm with Sparse Trajectory for Millimeter-wave Radar

DOI: 10.12000/JR23001

  • School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China

Funds:  The National Natural Science Foundation of China (62171084, 61922023, 62101096), Science and Technology on Electronic Information Control Laboratory Foundation
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    Abstract
  • In recent years, millimeter-wave radar has been widely used in safety detection, nondestructive detection of parts, and medical diagnosis because of its strong penetration ability, small size, and high detection accuracy. However, due to the limitation of hardware transmission bandwidth, achieving ultra-high two-dimensional resolution using millimeter-wave radar is challenging. Two-dimensional high-resolution imaging of altitude and azimuth can be realized using radar platform scanning to form a two-dimensional aperture. However, during the scanning process, the millimeter-wave radar produces sparse tracks in the height dimension, resulting in a sparse sampling of the altitude echo, thus reducing the imaging quality. In this paper, a high-resolution three-dimensional imaging algorithm for millimeter-wave radar based on Hankel transformation matrix filling is proposed to solve this problem. The matrix filling algorithm restores the sparse sampling echo, which guarantees the imaging accuracy of the millimeter-wave radar in the scanning plane. First, the low-rank prior characteristics of the millimeter-wave radar's elevation-range section were analyzed. To solve the problem of missing whole rows and columns of data during sparse trajectory sampling, the echo data matrix was reconstructed using the Hankel transform, and the sparse low-rank prior characteristics of the constructed matrix were analyzed. Furthermore, a matrix filling algorithm based on truncated Schatten-p norm combining low-rank and sparse priors was proposed to fill and reconstruct the echoes to ensure the three-dimensional resolution of the sparse trajectory millimeter-wave radar. Finally, using simulation and several sets of measured data, the proposed method was proved to achieve high-resolution three-dimensional imaging even when only 20%–30% of the height echo was used.

     

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