High Resolution Imaging from Azimuth Missing SAR Raw Data via Segmented Recovery

Synthetic Aperture Radar (SAR) raw data missing occurs when radar is interrupted by various influences. In order to cope with this problem, a new method is proposed to focus the azimuth missing SAR raw data via segmented recovery in this paper. A reference function in time domain is designed to make...

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Main Authors: Yulei Qian, Daiyin Zhu
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Electronics
Subjects:
Online Access:http://www.mdpi.com/2079-9292/8/3/336
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spelling doaj-0d6e47d1dc1d4cf1a28e619bb6231f132020-11-24T21:36:40ZengMDPI AGElectronics2079-92922019-03-018333610.3390/electronics8030336electronics8030336High Resolution Imaging from Azimuth Missing SAR Raw Data via Segmented RecoveryYulei Qian0Daiyin Zhu1Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, College of Electronic Information Engineering, Nanjing University of Aeronautics and Astronautics, 29 Jiangjun Avenue, Nanjing 211100, ChinaKey Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, College of Electronic Information Engineering, Nanjing University of Aeronautics and Astronautics, 29 Jiangjun Avenue, Nanjing 211100, ChinaSynthetic Aperture Radar (SAR) raw data missing occurs when radar is interrupted by various influences. In order to cope with this problem, a new method is proposed to focus the azimuth missing SAR raw data via segmented recovery in this paper. A reference function in time domain is designed to make the missing raw data sparser in two dimensional frequency domain. Afterwards, greedy algorithms are available to recover the missing data in two dimensional frequency domain. In addition, in order to avoid range frequency aliasing problem caused by reference function multiplication in time domain, the missing raw data is split into several parts in range direction and is recovered with a segmented recovery strategy. Then, the recovered raw data is available to be focused with traditional SAR imaging algorithms. The range migration algorithm is chosen to deal with the recovered raw data in this paper. Point target and area target simulations are carried out to validate the effectiveness of the proposed method on azimuth missing SAR raw data. Moreover, the proposed method is implemented on real SAR data in order to further provide convincing demonstration.http://www.mdpi.com/2079-9292/8/3/336SAR imaginghigh resolutionmissing dataStOMP
collection DOAJ
language English
format Article
sources DOAJ
author Yulei Qian
Daiyin Zhu
spellingShingle Yulei Qian
Daiyin Zhu
High Resolution Imaging from Azimuth Missing SAR Raw Data via Segmented Recovery
Electronics
SAR imaging
high resolution
missing data
StOMP
author_facet Yulei Qian
Daiyin Zhu
author_sort Yulei Qian
title High Resolution Imaging from Azimuth Missing SAR Raw Data via Segmented Recovery
title_short High Resolution Imaging from Azimuth Missing SAR Raw Data via Segmented Recovery
title_full High Resolution Imaging from Azimuth Missing SAR Raw Data via Segmented Recovery
title_fullStr High Resolution Imaging from Azimuth Missing SAR Raw Data via Segmented Recovery
title_full_unstemmed High Resolution Imaging from Azimuth Missing SAR Raw Data via Segmented Recovery
title_sort high resolution imaging from azimuth missing sar raw data via segmented recovery
publisher MDPI AG
series Electronics
issn 2079-9292
publishDate 2019-03-01
description Synthetic Aperture Radar (SAR) raw data missing occurs when radar is interrupted by various influences. In order to cope with this problem, a new method is proposed to focus the azimuth missing SAR raw data via segmented recovery in this paper. A reference function in time domain is designed to make the missing raw data sparser in two dimensional frequency domain. Afterwards, greedy algorithms are available to recover the missing data in two dimensional frequency domain. In addition, in order to avoid range frequency aliasing problem caused by reference function multiplication in time domain, the missing raw data is split into several parts in range direction and is recovered with a segmented recovery strategy. Then, the recovered raw data is available to be focused with traditional SAR imaging algorithms. The range migration algorithm is chosen to deal with the recovered raw data in this paper. Point target and area target simulations are carried out to validate the effectiveness of the proposed method on azimuth missing SAR raw data. Moreover, the proposed method is implemented on real SAR data in order to further provide convincing demonstration.
topic SAR imaging
high resolution
missing data
StOMP
url http://www.mdpi.com/2079-9292/8/3/336
work_keys_str_mv AT yuleiqian highresolutionimagingfromazimuthmissingsarrawdataviasegmentedrecovery
AT daiyinzhu highresolutionimagingfromazimuthmissingsarrawdataviasegmentedrecovery
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