Fractional OAM Vortex SAR Imaging Based on Chirp Scaling Algorithm
Vortex electromagnetic wave carries orbital angular momentum. Combined with Doppler information provided by radar platform movement, vortex electromagnetic wave can achieve higher resolution target imaging in SAR Imaging technology. In this paper, fractional order OAM vortex SAR imaging is studied....
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| Published in: | Radio science Vol. 60; no. 3 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Washington
Blackwell Publishing Ltd
01.03.2025
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| Subjects: | |
| ISSN: | 0048-6604, 1944-799X |
| Online Access: | Get full text |
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| Summary: | Vortex electromagnetic wave carries orbital angular momentum. Combined with Doppler information provided by radar platform movement, vortex electromagnetic wave can achieve higher resolution target imaging in SAR Imaging technology. In this paper, fractional order OAM vortex SAR imaging is studied. Firstly, the side‐looking strip SAR imaging model is established. Then, the scattering echo equation of fractional order OAM is derived. Finally, the imaging simulation of multi‐point target and single point target under Gaussian SNR is carried out by Chirp Scaling algorithm. The experimental results show that compared with the integer order OAM Vortex SAR Imaging, the fractional order OAM Vortex SAR Imaging in this paper has stronger robustness in Multi‐target and Noise environment, which proves the effectiveness of the fractional order Vortex SAR Imaging.
Plain Language Summary
We verify by Chirp Scaling Algorithm. In this paper, the fractional‐order OAM Vortex SAR Imaging has strong robustness in Multi‐target and Noise environment.
Key Points
We derive the echo formula for Fractional Vortex SAR Imaging
We simulate the amplitude and phase patterns of plane wave and integral and fractional order vortex wave
We have done imaging experiments of multiple targets and single target under Gaussian Signal‐to‐Noise Ratio |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 0048-6604 1944-799X |
| DOI: | 10.1029/2024RS008112 |