Three-Dimensional Interferometric Imaging With Vortex Electromagnetic Wave Radar Based on Uniform Circular Array

Due to the unique phase wavefront structure modulated by orbital angular momentum (OAM), vortex electromagnetic wave (VEMW) radar can obtain more target information and improve imaging performance. However, in most existing 3-D VEMW imaging methods, relative motion between radar and target is necessary, leading to the need of complex motion compensation. Some other methods although not relying on relative motion, the accuracy of 3-D VEMW imaging is insufficient. In addition, the absence of effective Bessel function compensation further reduces the imaging performance of existing methods. In this article, based on the uniform circular array (UCA), a 3-D VEMW imaging method with phase interferometry among array elements is proposed without relative motion. First, a 2-D VEMW imaging method with negative Bessel function compensation is proposed, where the coarse elevation information of target scattering points is obtained by simple phase interferometry, and then, the coarse elevation information is utilized to identify the negative Bessel functions that need to be compensated to achieve accurate range-azimuth 2-D imaging results. On this basis, a two-step interferometry processing method for accurate elevation reconstruction is proposed with avoiding phase unwrapping, in which the receiving array elements employed for phase interferometry are selected from UCA based on the azimuth of each scattering point to reduce reconstruction error. As a result, 3-D VEMW imaging can be achieved. Simulations demonstrate the accuracy and robustness of the proposed method.

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Publication Details

Journal
IEEE Sensors Journal
Published
2024-09-10
DOI
https://doi.org/10.1109/jsen.2024.3453869
Citations
6
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
1.23

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article

Three-Dimensional Interferometric Imaging With Vortex Electromagnetic Wave Radar Based on Uniform Circular Array

Jia Liang, Yijun Chen, Ying Luo, Siyuan Wang et al.
6 citations
IEEE Sensors Journal
Soil Moisture and Remote Sensing
1.23
article

Three-Dimensional Interferometric Imaging With Vortex Electromagnetic Wave Radar Based on Uniform Circular Array

Jia Liang, Yijun Chen, Ying Luo, Siyuan Wang, Yi Qu
article en
6 citations

Abstract

Due to the unique phase wavefront structure modulated by orbital angular momentum (OAM), vortex electromagnetic wave (VEMW) radar can obtain more target information and improve imaging performance. However, in most existing 3-D VEMW imaging methods, relative motion between radar and target is necessary, leading to the need of complex motion compensation. Some other methods although not relying on relative motion, the accuracy of 3-D VEMW imaging is insufficient. In addition, the absence of effective Bessel function compensation further reduces the imaging performance of existing methods. In this article, based on the uniform circular array (UCA), a 3-D VEMW imaging method with phase interferometry among array elements is proposed without relative motion. First, a 2-D VEMW imaging method with negative Bessel function compensation is proposed, where the coarse elevation information of target scattering points is obtained by simple phase interferometry, and then, the coarse elevation information is utilized to identify the negative Bessel functions that need to be compensated to achieve accurate range-azimuth 2-D imaging results. On this basis, a two-step interferometry processing method for accurate elevation reconstruction is proposed with avoiding phase unwrapping, in which the receiving array elements employed for phase interferometry are selected from UCA based on the azimuth of each scattering point to reduce reconstruction error. As a result, 3-D VEMW imaging can be achieved. Simulations demonstrate the accuracy and robustness of the proposed method.

IEEE Sensors JournalVol. 24(20)
Air Force Engineering University (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 23%
Soil Moisture and Remote Sensing
1.23
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