Kalman filter error covariance

1. What is error covariance Kalman filter?
2. What is error covariance?
3. What is background error covariance?
4. What is error state Kalman filter?

What is error covariance Kalman filter?

The Kalman Filter (KF) is a recursive scheme that propagates a current estimate of a state and the error covariance matrix of that state forward in time. The filter optimally blends the new information introduced by the measurements with old information embodied in the prior state with a Kalman gain matrix.

What is error covariance?

The error covariance matrix (ECM) is a dataset that specifies the correlations in the observation errors between all possible pairs of vertical levels. It is given as a two-dimensional array, of size NxN , where N is the number of vertical levels in the sounding data products.

What is background error covariance?

Background error covariance matrices (B): Describes errors in the background state (forecast from previous analysis). Depends on the analysis errors of the previous assimilation, and on forecast model error.

What is error state Kalman filter?

The indirect (error state) form of the Kalman filter is developed for attitude estimation when apply- ing gyro modeling. The main benefit of this choice is that complex dynamic modeling of the mobile robot and its interaction with the environment is avoided.