Kalman filter initial covariance matrix

1. How do you initialize a covariance matrix Kalman filter?
2. What is covariance matrix in Kalman filter?
3. How do you initialize a Kalman filter?
4. How do you choose Kalman filter parameters?

How do you initialize a covariance matrix Kalman filter?

Since the model of the Kalman filter does not start with any old measure, the initial state vector x0 - is chosen to be zero. The initial covariance matrix Po is chosen equal to a diagonal matrix with a value equal to 10. The value of the variance of the noise R is chosen to be equal to a constant = 0.05.

What is covariance matrix in Kalman filter?

This uncertainty can be represented by a matrix known as the state covariance matrix, P. The state covariance matrix consists of the variances associated with each of the state estimates as well as the correlation between the errors in the state estimates.

How do you initialize a Kalman filter?

In absence of covariance data, Kalman filters are usually initialized by guessing the initial state. Making the variance of the initial state estimate large makes sure that the estimate converges quickly and that the influence of the initial guess soon will be negligible.

How do you choose Kalman filter parameters?

Kalman filter needs the F, H, Q (the covariance matrix of v) and R (the covariance matrix of w) as well as ξ1 as the initial state and the corresponding P1 (the mean squared error of ξ1) to start the recursion. However, these parameters generally have to be estimated by numerical methods.