Velocity Measurement

Velocity measurement is crucial across diverse scientific and engineering fields, aiming to accurately and reliably determine the speed and direction of objects or fluids. Current research emphasizes developing robust methods for velocity estimation in challenging conditions, including using machine learning techniques like artificial neural networks and physics-informed networks to infer velocity from sparse or noisy data, and integrating data from multiple sensors (e.g., LiDAR, radar, cameras) for improved accuracy and resilience. These advancements have significant implications for various applications, ranging from autonomous vehicle navigation and sports performance analysis to the study of complex turbulent flows.