How to set initial values of the elements in the covariance matrices in the Kalman filter?

1. How do you initialize a Kalman filter?
2. Why covariance matrix is used in Kalman filter?
3. How to fine tune Kalman filter?

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.

Why covariance matrix is used in 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.

How to fine tune Kalman filter?

A simple approach to tune a Kalman filter is to use measurements with a known ground truth and adjusting the measurement and process noise of the filter.