Kalman Filters

A Kalman Filter is a mathematical method used to estimate the true state of a system—like position or speed—by combining noisy measurements with a model of how the system evolves over time. It predicts the next state based on the current estimate, then updates that prediction with new data, weighing their reliability. This process helps provide more accurate and smooth estimates even when measurements are uncertain or incomplete. Kalman Filters are widely used in navigation, robotics, and tracking applications to improve accuracy and reliability over raw sensor data.