Kalman filter class

The class implements a standard Kalman filter, [Welch95]. However, you can modify transitionMatrix, controlMatrix, and measurementMatrix to get an extended Kalman filter functionality.

Example

% initialization
kf = cv.KalmanFilter(4,2);
kf.statePre = [10;20;0;0]; % initial state prediction
kf.transitionMatrix = [1,0,1,0; 0,1,0,1; 0,0,1,0; 0,0,0,1];
kf.measurementMatrix([1,4]) = 1;
kf.processNoiseCov = eye(4) * 1e-4;
kf.measurementNoiseCov = eye(2) * 1e-1;
kf.errorCovPost = eye(4) * 0.1;

% dynamics
p_pred = kf.predict();       % update internal state
measure = [11;21];           % measurement
p_est = kf.correct(measure); % correct

References

[Welch95]:

Greg Welch and Gary Bishop. An introduction to the kalman filter, 1995. PDF