Digital twins

Harnessing the potential of quantum sensors to assist in navigation requires enabling their operation in complex, dynamic environments and integrating them within existing navigation systems. While cross-couplings from platform dynamics generally degrade quantum measurements in a complex manner, navigation filters would need to be designed to handle such complex quantum sensor data. Accurate quantum sensor models representative of the sensor true performance in real navigation conditions would therefore be critical to provide comprehensive, reliable data to train and optimise navigation filters. In a recent work, I have developed a high-fidelity model of an atom-interferometry-based gravity gradiometer and demonstrated its successful integration with a map-matching navigation filter. Relying on the ability of the model to simulate the sensor behaviour across various dynamic platform environments, this work has evidenced the benefits of aiding navigation via map matching using quantum gravity gradiometry and highlighted the importance of mitigating non-Gaussian errors arising from platform dynamics which are a key challenge to map-matching navigation. This work demonstrates the value of an end-to-end digital simulation approach that could support future optimization of the overall navigation system. 

Published in Quantum Science and Technology 10 045007 (2025)