Kalman Filter For Beginners With Matlab Examples Download _top_ -

% Plot results time = (0:N-1)*dt; figure; subplot(2,1,1); plot(time, X_true(1,:), 'g-', time, X_est(1,:), 'b--', time, Z, 'rx'); legend('True position','Estimated position','Measurements'); xlabel('Time (s)'); ylabel('Position'); title('Kalman Filter: Position');

This is where the magic happens. The Kalman Filter looks at your and your Measurement . It calculates the Kalman Gain —a weight that decides which one to trust more. If the sensor is great, it trusts the measurement. If the sensor is jumpy, it trusts the math model. kalman filter for beginners with matlab examples download