Compressive Sensing-Based SAR Image Reconstruction from Sparse Radar Sensor Data Acquisition in Automotive FMCW Radar System

In this paper, we propose a method for reconstructing synthetic aperture radar (SAR) images by applying a compressive sensing (CS) technique to sparsely acquired radar sensor data. In general, SAR image reconstruction algorithms require radar sensor data acquired at regular spatial intervals. Howeve...

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Autores principales:	Seongwook Lee, Yunho Jung, Myeongjin Lee, Wookyung Lee
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	compressive sensing frequency-modulated continuous wave range migration algorithm synthetic aperture radar Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/342861863adc46818701a3ee8d63c980
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spelling	oai:doaj.org-article:342861863adc46818701a3ee8d63c9802021-11-11T19:14:17ZCompressive Sensing-Based SAR Image Reconstruction from Sparse Radar Sensor Data Acquisition in Automotive FMCW Radar System10.3390/s212172831424-8220https://doaj.org/article/342861863adc46818701a3ee8d63c9802021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7283https://doaj.org/toc/1424-8220In this paper, we propose a method for reconstructing synthetic aperture radar (SAR) images by applying a compressive sensing (CS) technique to sparsely acquired radar sensor data. In general, SAR image reconstruction algorithms require radar sensor data acquired at regular spatial intervals. However, when the speed of the radar-equipped platform is not constant, it is difficult to consistently perform regular data acquisitions. Therefore, we used the CS-based signal recovery method to efficiently reconstruct SAR images even when regular data acquisition was not performed. In the proposed method, we used the l1-norm minimization to overcome the non-uniform data acquisition problem, which replaced the Fourier transform and inverse Fourier transform in the conventional SAR image reconstruction method. In addition, to reduce the phase distortion of the recovered signal, the proposed method was applied to each of the in-phase and quadrature components of the acquired radar sensor data. To evaluate the performance of the proposed method, we conducted experiments using an automotive frequency-modulated continuous wave radar sensor. Then, the quality of the SAR image reconstructed with data acquired at regular intervals was compared with the quality of images reconstructed with data acquired at non-uniform intervals. Using the proposed method, even if only 70% of the regularly acquired radar sensor data was used, a SAR image having a correlation of 0.83 could be reconstructed.Seongwook LeeYunho JungMyeongjin LeeWookyung LeeMDPI AGarticlecompressive sensingfrequency-modulated continuous waverange migration algorithmsynthetic aperture radarChemical technologyTP1-1185ENSensors, Vol 21, Iss 7283, p 7283 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	compressive sensing frequency-modulated continuous wave range migration algorithm synthetic aperture radar Chemical technology TP1-1185
spellingShingle	compressive sensing frequency-modulated continuous wave range migration algorithm synthetic aperture radar Chemical technology TP1-1185 Seongwook Lee Yunho Jung Myeongjin Lee Wookyung Lee Compressive Sensing-Based SAR Image Reconstruction from Sparse Radar Sensor Data Acquisition in Automotive FMCW Radar System
description	In this paper, we propose a method for reconstructing synthetic aperture radar (SAR) images by applying a compressive sensing (CS) technique to sparsely acquired radar sensor data. In general, SAR image reconstruction algorithms require radar sensor data acquired at regular spatial intervals. However, when the speed of the radar-equipped platform is not constant, it is difficult to consistently perform regular data acquisitions. Therefore, we used the CS-based signal recovery method to efficiently reconstruct SAR images even when regular data acquisition was not performed. In the proposed method, we used the l1-norm minimization to overcome the non-uniform data acquisition problem, which replaced the Fourier transform and inverse Fourier transform in the conventional SAR image reconstruction method. In addition, to reduce the phase distortion of the recovered signal, the proposed method was applied to each of the in-phase and quadrature components of the acquired radar sensor data. To evaluate the performance of the proposed method, we conducted experiments using an automotive frequency-modulated continuous wave radar sensor. Then, the quality of the SAR image reconstructed with data acquired at regular intervals was compared with the quality of images reconstructed with data acquired at non-uniform intervals. Using the proposed method, even if only 70% of the regularly acquired radar sensor data was used, a SAR image having a correlation of 0.83 could be reconstructed.
format	article
author	Seongwook Lee Yunho Jung Myeongjin Lee Wookyung Lee
author_facet	Seongwook Lee Yunho Jung Myeongjin Lee Wookyung Lee
author_sort	Seongwook Lee
title	Compressive Sensing-Based SAR Image Reconstruction from Sparse Radar Sensor Data Acquisition in Automotive FMCW Radar System
title_short	Compressive Sensing-Based SAR Image Reconstruction from Sparse Radar Sensor Data Acquisition in Automotive FMCW Radar System
title_full	Compressive Sensing-Based SAR Image Reconstruction from Sparse Radar Sensor Data Acquisition in Automotive FMCW Radar System
title_fullStr	Compressive Sensing-Based SAR Image Reconstruction from Sparse Radar Sensor Data Acquisition in Automotive FMCW Radar System
title_full_unstemmed	Compressive Sensing-Based SAR Image Reconstruction from Sparse Radar Sensor Data Acquisition in Automotive FMCW Radar System
title_sort	compressive sensing-based sar image reconstruction from sparse radar sensor data acquisition in automotive fmcw radar system
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/342861863adc46818701a3ee8d63c980
work_keys_str_mv	AT seongwooklee compressivesensingbasedsarimagereconstructionfromsparseradarsensordataacquisitioninautomotivefmcwradarsystem AT yunhojung compressivesensingbasedsarimagereconstructionfromsparseradarsensordataacquisitioninautomotivefmcwradarsystem AT myeongjinlee compressivesensingbasedsarimagereconstructionfromsparseradarsensordataacquisitioninautomotivefmcwradarsystem AT wookyunglee compressivesensingbasedsarimagereconstructionfromsparseradarsensordataacquisitioninautomotivefmcwradarsystem
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Compressive Sensing-Based SAR Image Reconstruction from Sparse Radar Sensor Data Acquisition in Automotive FMCW Radar System

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