Range-angle Imaging Based on the Prior of Target Scattering Characteristics in Distributed Arrays

We consider the problem of target range-angle imaging using distributed arrays. High resolution imaging requires a large array aperture. However, due to the limited number of array elements, the subarrays are usually sparsely located, which results in severe under-sampling and ambiguity problem, degrading the imaging performance. To this end, we propose a range-angle imaging method based on the prior of target scattering characteristic to resolve the ambiguity. The main idea is to use the information increment of priors to reduce the dependence on the measurements. Particularly, we first statistically extract the prior distribution of target scattering intensity by data analysis on the target images. Then we use these priors to design weighting parameters and achieve the ambiguity-free images by solving a weighted sparse recovery problem. Finally, numerical simulation results verify the feasibility of the proposed method.

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Publication Details

Published
2024-11-22
DOI
https://doi.org/10.1109/icsidp62679.2024.10868140
Primary Topic
Advanced SAR Imaging Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Range-angle Imaging Based on the Prior of Target Scattering Characteristics in Distributed Arrays

Yongfeng Mei, Tianyao Huang, Guangbin Zhang, Yan Wang
Advanced SAR Imaging Techniques
article

Range-angle Imaging Based on the Prior of Target Scattering Characteristics in Distributed Arrays

Yongfeng Mei, Tianyao Huang, Guangbin Zhang, Yan Wang
article en

Abstract

We consider the problem of target range-angle imaging using distributed arrays. High resolution imaging requires a large array aperture. However, due to the limited number of array elements, the subarrays are usually sparsely located, which results in severe under-sampling and ambiguity problem, degrading the imaging performance. To this end, we propose a range-angle imaging method based on the prior of target scattering characteristic to resolve the ambiguity. The main idea is to use the information increment of priors to reduce the dependence on the measurements. Particularly, we first statistically extract the prior distribution of target scattering intensity by data analysis on the target images. Then we use these priors to design weighting parameters and achieve the ambiguity-free images by solving a weighted sparse recovery problem. Finally, numerical simulation results verify the feasibility of the proposed method.

Beijing Institute of Technology (CN), University of Science and Technology Beijing (CN)
National Natural Science Foundation of China, Beijing Nova Program
Affordable and clean energy
Openalex Percentile: Top 55%
Advanced SAR Imaging Techniques
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