Stochastic Wind Gust Model for Aerobot in Venus Atmosphere

Venus, the closest planet to Earth, is often referred to as Earth's sister planet due to its similar size, mass, and composition. Past robotic missions have revealed a hot, dry climate with a dense carbon dioxide atmosphere, characterized by strong winds and clouds. The clouds of Venus are of particular interest because, with mild temperatures and Earth-like pressures between 51 to 62 km of altitude, it is one of the few potentially habitable regions in our solar system. Various mission concepts have been proposed, but what would be optimal to study this atmospheric region in the next decade is a balloon with a suspended science gondola, together referred to as an aerobot. Given the extreme conditions of the planet and the dynamics of a balloon navigating the atmosphere, detailed models of wind gusts are particularly significant. Unfortunately, previous missions have only collected surface wind data and vertical gusts, leaving horizontal gusts data missing. The goal of this thesis is to develop a robust gust model capable of capturing the highly non-stationary and random characteristics of wind gusts. In addition, it aims to develop a method to generate real-time predictions during a mission using live data. The proposed model relies on a set of stochastic differential equations, specifically the Ornstein-Uhlenbeck process, able to accurately reproduce the autocorrelation function and probability density function of an authentic wind signal. This approach results in synthetic random data that faithfully reflects the probability characteristics of real wind signals. Over the past few months, JPL conducted flight tests in the desert and collected wind data. The data underwent a cleaning process using an Extended Kalman Filter, and was then used to validate the gust model. Finally, after successfully validating the model with Earth-based data and demonstrating its reliability, the thesis concludes with a discussion of potential gust conditions in the Venusian atmosphere.