Kalman Filter For Beginners With Matlab Examples Download -

% Noise parameters process_noise_std = 0.5; % uncertainty in model (e.g., window opens) measurement_noise_std = 2; % sensor noise

for k = 1:T % True motion true_pos = true_pos + true_vel * dt; true_traj(k) = true_pos;

% Matrices F = [1 dt; 0 1]; % state transition H = [1 0]; % we measure only position Q = [process_noise_pos^2 0; 0 process_noise_vel^2]; R = meas_noise_pos^2; kalman filter for beginners with matlab examples download

% --- Update step --- x_est = x_pred + K * (z - x_pred); P_est = (1 - K) * P_pred;

% Storage true_traj = zeros(1,T); meas_traj = zeros(1,T); est_traj = zeros(1,T); % Noise parameters process_noise_std = 0

% Noisy measurement z = true_pos + meas_noise_pos * randn; meas_traj(k) = z;

est_traj(k) = x_est(1); end

% Simulation parameters dt = 1; % time step (seconds) T = 50; % total time steps