Paper
25 May 2023 An imaging algorithm research for the airborne ultra-wideband synthetic aperture radar
Lingnan Wu, Jin Xia
Author Affiliations +
Proceedings Volume 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022); 1263651 (2023) https://doi.org/10.1117/12.2675254
Event: Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 2022, Shenyang, China
Abstract
In order to improve the imaging performance of the airborne Ultra-wideband synthetic aperture radar, the imaging algorithm is researched. Firstly, the characteristics of the airborne Ultra-wideband synthetic aperture radar and the key technical problems of imaging are analyzed. Then, aiming at its key technical problems, a Chirp Scaling imaging algorithm is adopted to correct range migration, reduce strong coupling, eliminate space-varying characteristics, and solve the dependence of range compression on azimuth frequency, etc. Finally, the traditional range-Doppler imaging algorithm and the Chirp Scaling imaging algorithm are applied to the airborne Ultra-wideband synthetic aperture radar imaging, and simulation and comparative analysis are carried out. The simulation results show that the echo signal strength of Chirp Scaling algorithm in range and azimuth is obviously better than that of range-Doppler algorithm, and Chirp Scaling algorithm is more suitable for the airborne Ultra-wideband synthetic aperture radar imaging system.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lingnan Wu and Jin Xia "An imaging algorithm research for the airborne ultra-wideband synthetic aperture radar", Proc. SPIE 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 1263651 (25 May 2023); https://doi.org/10.1117/12.2675254
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KEYWORDS
Synthetic aperture radar

Radar imaging

Radar

Detection and tracking algorithms

Imaging systems

Fourier transforms

Antennas

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