Kalman Filter For Beginners With Matlab Examples Download < Recommended >

% --- Prediction --- x_pred = F * x_est; P_pred = F * P_est * F' + Q;

est_traj(k) = x_est(1); 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; 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 % --- Prediction --- x_pred = F *

% --- Kalman gain --- K = P_pred / (P_pred + measurement_noise_std^2); est_traj(k) = x_est(1)