Position Estimation

Position estimation aims to accurately determine the location of an object or entity, a crucial task across diverse fields. Current research focuses on improving accuracy and robustness using various sensor modalities (e.g., GNSS, radar, IMU, cameras, UWB) and advanced algorithms like particle filters, Kalman filters, and neural networks (including CNNs and GANs), often incorporating physics-informed models or data-driven approaches to mitigate noise and environmental challenges. These advancements are driving progress in applications ranging from autonomous navigation and robotics to smart city infrastructure and medical imaging, where precise localization is essential for functionality and safety.