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SAR image formation scheme implementation and endorsement sprouting from Level-0 data decoding.

Authors :
Azouz, Ahmed
Fouad, Mohamed
ELbohy, Ahmed
Abdalla, Ahmed
Mashaly, Ahmed
Source :
Egyptian Journal of Remote Sensing & Space Sciences; Aug2023, Vol. 26 Issue 2, p253-263, 11p
Publication Year :
2023

Abstract

Synthetic Aperture Radar (SAR) data processing evolving from level-0 raw data is complicated, especially in data decoding, manifesting in obtaining a well-focused SAR image. This paper is intended to present a complete MATLAB-based SAR data processing tool, which helps the end-user to treat simply the steps of image generation. This paper would enrich the research community in the field of SAR processors, especially in the area of understanding, handling, and developing a SAR processor based on space packet protocol standard (STD 01) used in many SAR systems such as Sentinel-1, ERS-1, CubeL, JPSS-2, 3, and 4. Also, this work opens the door for researchers to decode other space packet protocol standards and even to create an algorithm based on fully understanding the image formation algorithm from its roots. Moreover, the work in this paper could be a stepping-stone for the beginner in the field of SAR signal processing to become familiarized with SAR image generation procedures. The level-0 raw data used in this paper is based on Sentinel 1 SAR satellite obtained from the European Space Agency Copernicus website, a free open-source for level-0 and level-1 data types. The MATLAB program allows users to compare their generated image with the level-1 single-look complex (S1-L1-SLC) image utilizing entropy, contrast, and sharpness image quality metrics. The results showed that the images produced by the proposed algorithm are comparable to Sentinel-1 level-1 SAR images for the same scene and achieved satisfactory accuracy under the requirements for image quality. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
11109823
Volume :
26
Issue :
2
Database :
Supplemental Index
Journal :
Egyptian Journal of Remote Sensing & Space Sciences
Publication Type :
Academic Journal
Accession number :
164435360
Full Text :
https://doi.org/10.1016/j.ejrs.2023.03.002