% --- Update --- x_est = x_pred + K * (z - H * x_pred); P_est = (eye(2) - K * H) * P_pred;
% Simulation parameters dt = 1; % time step (seconds) T = 50; % total time steps kalman filter for beginners with matlab examples download
x_history(k) = x_est; end
% 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; % --- Update --- x_est = x_pred +
% Noise parameters process_noise_std = 0.5; % uncertainty in model (e.g., window opens) measurement_noise_std = 2; % sensor noise % Simulation parameters dt = 1