Dual-Angle Radar Image Reconstruction With Geometrical Theory of Diffraction Model

When the radar observation angle is sparse and the target is stationary, it is difficult to image by traditional methods. Therefore, we propose a dual-angle radar image reconstruction method to achieve dual-angle radar imaging. Firstly, the scattering centers estimation strategy based on GTD model is used and solved by ADMM to obtain the target scattering center information. Then the scattering center, distance and coefficient information are used to score and match the strong scattering points of the two HRRPs. Finally, the image is reconstructed by tracing the points. The effectiveness of the proposed algorithm is verified by simulation.

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Publication Details

Published
2024-11-22
DOI
https://doi.org/10.1109/icsidp62679.2024.10869069
Primary Topic
Numerical methods in inverse problems
Type
article
Field-Weighted Citation Impact
0.00

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Dual-Angle Radar Image Reconstruction With Geometrical Theory of Diffraction Model

Guanxing Wang, Zhan Song, Pucheng Li, Zehua Dong et al.
Numerical methods in inverse problems
article

Dual-Angle Radar Image Reconstruction With Geometrical Theory of Diffraction Model

Guanxing Wang, Zhan Song, Pucheng Li, Zehua Dong, Kefeng He, Jianping Wang
article en

Abstract

When the radar observation angle is sparse and the target is stationary, it is difficult to image by traditional methods. Therefore, we propose a dual-angle radar image reconstruction method to achieve dual-angle radar imaging. Firstly, the scattering centers estimation strategy based on GTD model is used and solved by ADMM to obtain the target scattering center information. Then the scattering center, distance and coefficient information are used to score and match the strong scattering points of the two HRRPs. Finally, the image is reconstructed by tracing the points. The effectiveness of the proposed algorithm is verified by simulation.

Beijing Institute of Technology (CN)
National Natural Science Foundation of China
Sustainable cities and communities
Openalex Percentile: Top 58%
Numerical methods in inverse problems
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