Synthetic Multimode Orbital Angular Momentum Generation and Its Object Detection Application

This study proposes a novel method for generating virtual orbital angular momentum (OAM) using a synthetic uniform circular array (SUCA). In the proposed method, the base array is rotated to various spatial locations, with the feeding phases modified accordingly, and the generated fields at various...

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Bibliographic Details
Published in:IEEE transactions on antennas and propagation 2023-12, Vol.71 (12), p.9905-9913
Main Authors: Yang, Yang, Chen, Zijun, Wang, Yu, Fu, Jiangnan, Gao, Yuan, Wang, Shaomeng, Shen, Fei, Jiang, Haibo, Gong, Yubin
Format: Article
Language:English
Subjects:
Angular momentum
Antenna arrays
Antennas
Circular polarization
Finite element analysis
Frequency ranges
Horn antennas
Imaging
Multimode
Object detection
Object recognition
Phased arrays
Spirals
synthetic uniform circular array (SUCA)
virtual orbital angular momentum (OAM)
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Summary:This study proposes a novel method for generating virtual orbital angular momentum (OAM) using a synthetic uniform circular array (SUCA). In the proposed method, the base array is rotated to various spatial locations, with the feeding phases modified accordingly, and the generated fields at various spatial locations are superimposed. The proposed method exchanges the cost of the time domain for more spatial degrees of freedom, which can overcome the limit of space and configure more virtual array elements to generate vortex electromagnetic (EM) waves carrying virtual multimode OAMs. To validate the effectiveness of the proposed method, a radially placed SUCA is designed with four actual elements of a circularly polarized (CP) horn antenna and sixteen virtual elements. The SUCA is then simulated and measured, and it successfully generates fifteen virtual OAMs in the frequency range of 5-6.5 GHz. Furthermore, 2-D object detection experiments of three metal targets with different scales at different positions based on the SUCA were conducted. The experimental results show that the three targets can be distinguished clearly, indicating that our work has the potential to generate more virtual OAMs and improve object detection resolution in practical applications.
ISSN:0018-926X
1558-2221
DOI:10.1109/TAP.2023.3325581