Kalman Filter For Beginners With Matlab Examples Download Top -

% --- CORRECTION STEP (Using the measurement) --- z = measurements(k); % Current measurement y = z - H * x_pred; % Innovation (measurement residual) S = H * P_pred * H' + R; % Innovation covariance K = P_pred * H' / S; % Kalman Gain

% True state: [Position; Velocity] true_pos = zeros(1, N); true_vel = 1.0; % Constant velocity = 1 m/s % --- CORRECTION STEP (Using the measurement) ---

Invented by Rudolf E. Kálmán in 1960, the Kalman Filter is a mathematical algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, to produce estimates of unknown variables that are more accurate than those based on a single measurement alone. Velocity] true_pos = zeros(1