Mini toolsDefinition
A recursive algorithm that uses a series of measurements observed over time to estimate unknown variables more precisely than using single measurements alone.
Detailed Explanation
Kalman filters combine predictions with measurements to estimate the state of a system, taking into account both measurement and process noise. They use a prediction-correction cycle: first predicting the next state based on previous estimates, then updating this prediction using new measurements. The filter maintains estimates of uncertainty in both predictions and measurements.
Use Cases
GPS navigation systems, robotics motion planning, aerospace tracking, financial market prediction, and sensor fusion applications.
