Comparative Analysis of PSD Estimation Techniques for Wind Gust Signals: From Flight Campaigns to Satellite Data

This paper presents a methodological analysis of wind gust spectra, with a focus on estimating the wind gust power spectral density (PSD). Three spectral estimation approaches are systematically investigated: zero-padding, Welch’s method, and a length-weighted PSD formulation. The main objective is to evaluate the accuracy, robustness, and practical suitability of these techniques when applied to wind-gust signals obtained from two distinct sources: measurements from onboard sensors collected during a dedicated flight test campaign and measurements from a low-Earth orbit (LEO) satellite platform. Comparative results show that Welch’s method yields the most stable and reliable PSD estimates for flight-test data, particularly in terms of variance reduction and spectral smoothness. The same approach can be extended to satellite-based signals; however, the inherently low sampling frequency of LEO data severely constrains their usable bandwidth. As a consequence, satellite-derived gust spectra are of limited relevance for detailed assessments of aircraft structural response and fatigue, although they may remain valuable for large-scale atmospheric characterization.