Airborne FMCW SAR sparse data processing via frequency-scaling algorithm

Using the continuous-wave technology to replace the conventional pulse-mode, frequency-modulation continuous-wave (FMCW) synthetic aperture radar (SAR) has shown good potentials of reducing the weight of the system and the sensors' peak transmission power. In order to relax the requirements of...

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Main Authors: Bi, Hui, Zhang, Jingjing, Wang, Peng, Bi, Guoan
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/159712
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1597122022-06-30T01:38:21Z Airborne FMCW SAR sparse data processing via frequency-scaling algorithm Bi, Hui Zhang, Jingjing Wang, Peng Bi, Guoan School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Airborne Data Processing Frequency-Modulation Continuous Wave Using the continuous-wave technology to replace the conventional pulse-mode, frequency-modulation continuous-wave (FMCW) synthetic aperture radar (SAR) has shown good potentials of reducing the weight of the system and the sensors' peak transmission power. In order to relax the requirements of data bandwidth and storage, and increase the swath, the SAR system will collect the downsampled data, which makes the traditional matched filtering (MF)-based method unable to recover the considered scene, leading to failed reconstruction. To solve this problem, this letter presents an FMCW SAR sparse imaging method based on the frequency-scaling algorithm (FSA). Experimental results on the real data show that compared with the MF-based FMCW SAR imaging algorithms, the proposed method can improve the recovered image performance effectively. For the sparse surveillance region, it can achieve accurate recovery even from the downsampled data. Because the computational complexity of the proposed method is in the same order as that of MF, the sparse imaging of large-scale scenes can also be realized in the FMCW SAR. This work was supported in part by the Fundamental Research Funds for the Central Universities under Grant NE2020004, in part by the National Natural Science Foundation of China under Grant 61901213, in part by the Natural Science Foundation of Jiangsu Province under Grant BK20190397, in part by the Aeronautical Science Foundation of China under Grant 20182052013, and in part by the Young Science and Technology Talent Support Project of Jiangsu Science and Technology Association. 2022-06-30T01:38:21Z 2022-06-30T01:38:21Z 2020 Journal Article Bi, H., Zhang, J., Wang, P. & Bi, G. (2020). Airborne FMCW SAR sparse data processing via frequency-scaling algorithm. IEEE Geoscience and Remote Sensing Letters, 18(7), 1224-1228. https://dx.doi.org/10.1109/LGRS.2020.2995943 1545-598X https://hdl.handle.net/10356/159712 10.1109/LGRS.2020.2995943 2-s2.0-85112429926 7 18 1224 1228 en IEEE Geoscience and Remote Sensing Letters © 2020 IEEE. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Airborne Data Processing
Frequency-Modulation Continuous Wave
spellingShingle Engineering::Electrical and electronic engineering
Airborne Data Processing
Frequency-Modulation Continuous Wave
Bi, Hui
Zhang, Jingjing
Wang, Peng
Bi, Guoan
Airborne FMCW SAR sparse data processing via frequency-scaling algorithm
description Using the continuous-wave technology to replace the conventional pulse-mode, frequency-modulation continuous-wave (FMCW) synthetic aperture radar (SAR) has shown good potentials of reducing the weight of the system and the sensors' peak transmission power. In order to relax the requirements of data bandwidth and storage, and increase the swath, the SAR system will collect the downsampled data, which makes the traditional matched filtering (MF)-based method unable to recover the considered scene, leading to failed reconstruction. To solve this problem, this letter presents an FMCW SAR sparse imaging method based on the frequency-scaling algorithm (FSA). Experimental results on the real data show that compared with the MF-based FMCW SAR imaging algorithms, the proposed method can improve the recovered image performance effectively. For the sparse surveillance region, it can achieve accurate recovery even from the downsampled data. Because the computational complexity of the proposed method is in the same order as that of MF, the sparse imaging of large-scale scenes can also be realized in the FMCW SAR.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Bi, Hui
Zhang, Jingjing
Wang, Peng
Bi, Guoan
format Article
author Bi, Hui
Zhang, Jingjing
Wang, Peng
Bi, Guoan
author_sort Bi, Hui
title Airborne FMCW SAR sparse data processing via frequency-scaling algorithm
title_short Airborne FMCW SAR sparse data processing via frequency-scaling algorithm
title_full Airborne FMCW SAR sparse data processing via frequency-scaling algorithm
title_fullStr Airborne FMCW SAR sparse data processing via frequency-scaling algorithm
title_full_unstemmed Airborne FMCW SAR sparse data processing via frequency-scaling algorithm
title_sort airborne fmcw sar sparse data processing via frequency-scaling algorithm
publishDate 2022
url https://hdl.handle.net/10356/159712
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