The primary objective of the project was to research and develop new positioning algorithms and advanced guidance techniques to enhance the performance of the the SILEME indoor positioning system, which had been progressively developed by SKYLIFE over previous years. The initiative aimed to move beyond the existing state of the art by exploring innovative approaches capable of improving accuracy, robustness and adaptability — particularly in highly metallic and operationally demanding environments.
In parallel, the project focused on conceptualising a digital twin of the system through the development of predictive models capable of simulating the behaviour of system components and their interaction with complex environments.
This strategic approach established the foundation for future optimisation cycles beyond the scope of the project itself, where improvements could first be implemented in the digital domain, leveraging machine learning techniques, and subsequently transferred to the physical deployment of the system.
