Howtosignalprocessing
- What is state estimation Kalman filter?
- What is steady state Kalman filter?
- What is state vector in Kalman filter?
What is state estimation Kalman filter?
The Kalman filter produces an estimate of the state of the system as an average of the system's predicted state and of the new measurement using a weighted average. The purpose of the weights is that values with better (i.e., smaller) estimated uncertainty are "trusted" more.
What is steady state Kalman filter?
For time invariant and asymptotically stable systems, there exists a steady state value of the Kalman filter gain. The steady state Kalman filter gain is usually derived via the steady state prediction error covariance by first solving the corresponding Riccati equation.
What is state vector in Kalman filter?
To help explain how a standard Kalman filter works, consider an aircraft that needs to track its position and velocity as it flies to its destination. The estimated position (p) and velocity (v) form the estimated state vector, ˆx: x=[pv]
