Spaceborne SAR image formation enhancement using MOCO techniques

Synthetic aperture radar (SAR) is considered a prevailing tool for remote sensing. It benefits working with high efficiency in all weather and all-day circumstances, making SAR is very confident compared to other types of remote sensing. The SAR platform moves with constant velocity and height, with a linear path for ideal situations. However, this assumption is not realized in satellite movement, which is an elliptical orbiting that worsens the quality of the focused image. This paper introduces a methodology of motion compensation for motion errors due to satellite elliptical orbiting and perturbations in an orbital path. It represents two major contributions applied on a low earth orbit (LEO) spaceborne SAR. First, motion errors analysis in the range and azimuth directions. Second, an algorithm for motion error compensation (MOCO) combined with a chirp scaling algorithm (CSA) is performed. Moreover, a validation for the for-mulated algorithm is executed using sentinel-1 level-0 real raw data input, and the result is compared with the sentinel-1 level-1 single look complex (SLC) SAR image. The validation is performed using two different metrics. First, image quality measurement by sharpness, contrast, and entropy. Second, measuring the peak-sidelobe-ratio (PSLR), impulse-response-width (IRW), and integrated-sidelobe-ratio (ISLR) for five high power reflecting points in the scene area.(c) 2022 National Authority of Remote Sensing & Space Science. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).