Kalman Filter For Beginners With - Matlab Examples Pdf

% Run Kalman filter x_hat_log = zeros(2, num_steps); for k = 1:num_steps % Predict x_pred = A * x_hat; P_pred = A * P * A' + Q;

x_k = A * x_k-1 + B * u_k + w_k Measurement equation: z_k = H * x_k + v_k kalman filter for beginners with matlab examples pdf

% Generate noisy measurements num_steps = 50; measurements = zeros(1, num_steps); for k = 1:num_steps x_true = A * x_true; % true motion measurements(k) = H * x_true + sqrt(R)*randn; % noisy measurement end % Run Kalman filter x_hat_log = zeros(2, num_steps);

% Update K = P_pred * H' / (H * P_pred * H' + R); x_hat = x_pred + K * (measurements(k) - H * x_pred); P = (eye(2) - K * H) * P_pred; measurements = zeros(1