A Data-Driven Approach to SAR Data-Focusing
Synthetic Aperture RADAR (SAR) is a radar imaging technique in which the relative motion of the sensor is used to synthesize a very long antenna and obtain high spatial resolution. Several algorithms for SAR data-focusing are well established and used by space agencies. Such algorithms are model-bas...
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MDPI AG
2019-04-01
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Online Access: | https://www.mdpi.com/1424-8220/19/7/1649 |
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author | Cataldo Guaragnella Tiziana D’Orazio |
author_facet | Cataldo Guaragnella Tiziana D’Orazio |
author_sort | Cataldo Guaragnella |
collection | DOAJ |
description | Synthetic Aperture RADAR (SAR) is a radar imaging technique in which the relative motion of the sensor is used to synthesize a very long antenna and obtain high spatial resolution. Several algorithms for SAR data-focusing are well established and used by space agencies. Such algorithms are model-based, i.e., the radiometric and geometric information about the specific sensor must be well known, together with the ancillary data information acquired on board the platform. In the development of low-cost and lightweight SAR sensors, to be used in several application fields, the precise mission parameters and the knowledge of all the specific geometric and radiometric information about the sensor might complicate the hardware and software requirements. Despite SAR data processing being a well-established imaging technique, the proposed algorithm aims to exploit the SAR coherent illumination, demonstrating the possibility of extracting the reference functions, both in range and azimuth directions, when a strong point scatterer (either natural or manmade) is present in the scene. The Singular Value Decomposition is used to exploit the inherent redundancy present in the raw data matrix, and phase unwrapping and polynomial fitting are used to reconstruct clean versions of the reference functions. Fairly focused images on both synthetic and real raw data matrices without the knowledge of mission parameters and ancillary data information can be obtained; as a byproduct, azimuth beam pattern and estimates of a few other parameters have been extracted from the raw data itself. In a previous paper, authors introduced a preliminary work dealing with this problem and able to obtain good-quality images, if compared to the standard processing techniques. In this work, the proposed technique is described, and performance parameters are extracted to compare the proposed approach to RD, showing good adherence of the focused images and pulse responses. |
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issn | 1424-8220 |
language | English |
last_indexed | 2024-04-13T07:07:54Z |
publishDate | 2019-04-01 |
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spelling | doaj.art-a3f440a3e5cd42f29e03313d3c72458a2022-12-22T02:56:56ZengMDPI AGSensors1424-82202019-04-01197164910.3390/s19071649s19071649A Data-Driven Approach to SAR Data-FocusingCataldo Guaragnella0Tiziana D’Orazio1DEI—Department of Electrical and Information Engineering, Politecnico di Bari, 70126 Bari, ItalySTIIMA—Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, CNR—Italian National Research Council, 70124 Bari, ItalySynthetic Aperture RADAR (SAR) is a radar imaging technique in which the relative motion of the sensor is used to synthesize a very long antenna and obtain high spatial resolution. Several algorithms for SAR data-focusing are well established and used by space agencies. Such algorithms are model-based, i.e., the radiometric and geometric information about the specific sensor must be well known, together with the ancillary data information acquired on board the platform. In the development of low-cost and lightweight SAR sensors, to be used in several application fields, the precise mission parameters and the knowledge of all the specific geometric and radiometric information about the sensor might complicate the hardware and software requirements. Despite SAR data processing being a well-established imaging technique, the proposed algorithm aims to exploit the SAR coherent illumination, demonstrating the possibility of extracting the reference functions, both in range and azimuth directions, when a strong point scatterer (either natural or manmade) is present in the scene. The Singular Value Decomposition is used to exploit the inherent redundancy present in the raw data matrix, and phase unwrapping and polynomial fitting are used to reconstruct clean versions of the reference functions. Fairly focused images on both synthetic and real raw data matrices without the knowledge of mission parameters and ancillary data information can be obtained; as a byproduct, azimuth beam pattern and estimates of a few other parameters have been extracted from the raw data itself. In a previous paper, authors introduced a preliminary work dealing with this problem and able to obtain good-quality images, if compared to the standard processing techniques. In this work, the proposed technique is described, and performance parameters are extracted to compare the proposed approach to RD, showing good adherence of the focused images and pulse responses.https://www.mdpi.com/1424-8220/19/7/1649SAR systemefficient focusing of SAR datainverse problemremote sensingSAR data-focusingsynthetic aperture radarSingular Value Decompositionblind deconvolutionsignal processingparameter estimationcomputational modeling |
spellingShingle | Cataldo Guaragnella Tiziana D’Orazio A Data-Driven Approach to SAR Data-Focusing Sensors SAR system efficient focusing of SAR data inverse problem remote sensing SAR data-focusing synthetic aperture radar Singular Value Decomposition blind deconvolution signal processing parameter estimation computational modeling |
title | A Data-Driven Approach to SAR Data-Focusing |
title_full | A Data-Driven Approach to SAR Data-Focusing |
title_fullStr | A Data-Driven Approach to SAR Data-Focusing |
title_full_unstemmed | A Data-Driven Approach to SAR Data-Focusing |
title_short | A Data-Driven Approach to SAR Data-Focusing |
title_sort | data driven approach to sar data focusing |
topic | SAR system efficient focusing of SAR data inverse problem remote sensing SAR data-focusing synthetic aperture radar Singular Value Decomposition blind deconvolution signal processing parameter estimation computational modeling |
url | https://www.mdpi.com/1424-8220/19/7/1649 |
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