In order to apply for any of the following theses or internships, the candidate must have no more than 3 exams left.
MAVEN (Mars Atmosphere and Volatile Evolution) is a NASA spacecraft orbiting Mars to study the loss of the planet's atmospheric gases to space, providing insight into the history of the planet's climate. This thesis aims to analyze data from radio occultation experiments conducted by the spacecraft, with the objective of reconstructing the structure of Mars' atmosphere.
A radio occultation experiment is a technique used to study the atmosphere of a planet or moon. During such experiments, a spacecraft transmits radio waves toward a receiver, typically located on Earth, while it moves behind the celestial body relative to the observer. By analyzing the changes in the radio signal as it passes through the atmosphere, we can derive vertical profiles of atmospheric properties.
The data analysis will employ the ray-tracing technique, which allows for modeling the propagation of radio waves transmitted by the spacecraft as they pass through the Martian atmosphere, accounting for the phenomenon of refraction. The goal is to determine key parameters such as density, temperature, and pressure profiles, offering new insights into the atmospheric dynamics under the specific conditions of each experiment.
This project is part of the broader context of space missions dedicated to planetary exploration, contributing to the improvement of existing atmospheric models and enhancing our understanding of Mars' environmental conditions.
Topic: Radio Occultations / Data Analysis
Tutor: Andrea Caruso
Uploaded: 2025/02/25
The precise tracking of spacecraft via Doppler radio measurements is fundamental to a wide range of scientific and navigation objectives in planetary missions. One of the principal limitations on the accuracy of Doppler tracking data is the presence of tropospheric noise, namely propagation delays and fluctuations introduced as radio signals traverse Earth’s troposphere. Variations in temperature, pressure, and particularly water vapor content induce path length fluctuations that directly translate into errors in the measured Doppler shift. Characterizing this noise is therefore crucial for constructing reliable Doppler noise budgets and achieving high-precision orbit determination for interplanetary spacecraft.
The NASA Jet Propulsion Laboratory (JPL) operates Advanced Water Vapor Radiometers (AWVRs) in support of deep-space missions. These radiometers are highly sensitive instruments capable of measuring the brightness temperatures associated with water vapor emission at several microwave frequencies. These measurements can be converted into estimates of the Integrated Water Vapor (IWV) along the line of sight to a spacecraft’s signal path. Such data provide an invaluable resource for monitoring and modelling the tropospheric conditions that introduce noise into Doppler tracking.
The aim of this thesis is to quantify and model the impact of tropospheric noise based on the analysis of NASA JPL’s Advanced Water Vapor Radiometer (AWVR) data. To achieve this, the research will first comprehend the processing of AWVR brightness temperature measurements collected during past deep-space missions, focusing on the extraction of principal measurements and the computation of the tropospheric path delay. This path delay will subsequently be analyzed in terms of its Allan deviation, providing insight into the stability and noise characteristics of the tropospheric signal over various integration times. The final model developed in this thesis will be directly related to the Allan deviation, enabling a quantitative representation of tropospheric noise that can be incorporated into Doppler noise budgets for high-precision spacecraft tracking applications.
Topic: Data Analysis
Tutor: David Bernacchia
Uploaded: 29/07/2025