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Sensors 2017, 17(3), 630; doi:10.3390/s17030630

Electromagnetic Vortex-Based Radar Imaging Using a Single Receiving Antenna: Theory and Experimental Results

School of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China
These authors contributed equally to this work.
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Academic Editor: Ram M. Narayanan
Received: 13 February 2017 / Revised: 10 March 2017 / Accepted: 16 March 2017 / Published: 19 March 2017
(This article belongs to the Section Remote Sensors)
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Abstract

Radar imaging based on electromagnetic vortex can achieve azimuth resolution without relative motion. The present paper investigates this imaging technique with the use of a single receiving antenna through theoretical analysis and experimental results. Compared with the use of multiple receiving antennas, the echoes from a single receiver cannot be used directly for image reconstruction using Fourier method. The reason is revealed by using the point spread function. An additional phase is compensated for each mode before imaging process based on the array parameters and the elevation of the targets. A proof-of-concept imaging system based on a circular phased array is created, and imaging experiments of corner-reflector targets are performed in an anechoic chamber. The azimuthal image is reconstructed by the use of Fourier transform and spectral estimation methods. The azimuth resolution of the two methods is analyzed and compared through experimental data. The experimental results verify the principle of azimuth resolution and the proposed phase compensation method. View Full-Text
Keywords: radar imaging; orbital angular momentum (OAM); vortical radio wave; uniform circular array (UCA); phase compensation; azimuth resolution radar imaging; orbital angular momentum (OAM); vortical radio wave; uniform circular array (UCA); phase compensation; azimuth resolution
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Yuan, T.; Wang, H.; Cheng, Y.; Qin, Y. Electromagnetic Vortex-Based Radar Imaging Using a Single Receiving Antenna: Theory and Experimental Results. Sensors 2017, 17, 630.

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