Design and optimisation of Walker satellite constellations

Satellite constellations play an increasingly vital role in modern space applications, enabling essential services such as global communications, precise navigation, and Earth observation. The design and optimization of these constellations are crucial to maximizing performance while minimizing costs and complexity. Among the various constellation configurations, Walker-Delta and Street of Coverage are the ones analyzed in this work. This thesis focuses on the in-depth analysis of these two constellation architectures, examining their underlying principles and the algorithms governing their deployment and operation. A key contribution of this work is the development of two novel algorithms: the first for computing the geometric parameters of a satellite constellation based on mission requirements, and the second for simulating satellite orbits within the constellation framework. These algorithms provide a systematic approach to defining and evaluating constellation configurations, ensuring optimal coverage and performance tailored to specific mission needs. The proposed methodology is first applied to well-established constellations, including GPS and Galileo, which employ the Walker-Delta configuration, and Iridium, which follows the Street of Coverage approach. By validating the algorithms against these existing systems, their accuracy and effectiveness are demonstrated. Subsequently, the same algorithms are extended to analyze potential future case studies, showcasing their adaptability to the design of next-generation satellite constellations. Through this study, a structured and automated approach to constellation design is presented, offering valuable insights for the development of future space missions. The results highlight the importance of algorithm-driven optimization in satellite constellation planning, contributing to enhanced mission efficiency and performance in an increasingly demanding space environment.