This research paper proposes a novel technique to overcome common challenges in synthetic aperture radar (SAR) imaging, such as the effects of shadows, layover, and multipath interference. The key innovation of the proposed approach lies in two main contributions.  First, the strategic use of navigation data to compensate for antenna
steering, which introduces irregularities in the missing data regions of SAR images. The technique can effectively mitigate the impact of the aforementioned SAR imaging artifacts. Second, the proposed scheme results indicate due to the integration of digital signal processing (DSP) methods played a crucial role in enabling efficient and effective
remedy steps within the image formation algorithm preprocessing. This combined approach is based on platform navigation data powered by DSP when followed by a chirp-scaling algorithm (CSA), one of the most powerful SAR image formation algorithms. This approach when applied to real-world data from the Sentinel-1 satellite has yielded impressive
and unprecedented results in compensating the antenna steering and mitigating the backfill, producing reconstructed images that closely resemble the original Sentinel-1 SAR products. To comprehensively validate the performance of the proposed technique, the reconstructed images were assessed against the reference Sentinel-1 data using a suite
of established objective metrics, including entropy, contrast, sharpness, Mean Opinion Score (MOS), and structural similarity index measure (SSIM).These quantitative analyses conclusively confirmed the efficacy of the new method in enhancing the overall fidelity and visual quality of SAR imagery.This is very clear as the degree of similarity was recorded
on average as (98.4%) and obtained score on the standard scale of MOS is (4.82 out of 5).