Enhanced Resolution of Martian Polar Stratigraphy via Structure Enhancement Denoising and Sparse Deterministic Deconvolution of SHARAD Data

The Martian North Polar Layered Deposits (NPLD) are a thick sequence of ice and dust layers that serve as a primary archive of the planet’s recent climate history. The Shallow radar (SHARAD) sounder provides critical data for probing this stratigraphy, but its resolution is limited by the radar wavelet and the signal-to-noise ratio (SNR). Deconvolution aims to overcome the resolution limitation, with recent techniques like sparse deterministic deconvolution (SDD) showing promise. However, the performance of these methods is fundamentally constrained by noise, which can obscure weak reflectors from deep or subtle layers and introduce artifacts into the results. This study proposes a two-stage workflow that directly addresses the noise problem by applying structure enhancement denoising (SED) to improve the SNR and reflector echo power of SHARAD radargrams prior to deconvolution, thereby enhancing the overall fidelity of the results. The efficacy of this integrated SED-SDD workflow is validated first on synthetic radargrams, demonstrating a marked reduction in reflectivity error and superior preservation of structural detail compared to the baseline SDD method, especially under low-SNR conditions. Subsequently, the workflow is applied to a real SHARAD observation of the NPLD, revealing enhanced lateral continuity of subtle reflectors and a significant reduction in noise-induced artifacts. The results demonstrate that this synergistic approach provides a powerful tool for extracting higher-resolution stratigraphic information from noisy planetary orbital radar data, thereby advancing our ability to interpret the sedimentary history of Mars.