% Update K = P*H' / (H*P*H' + R); x = x + K*(meas(k) - H*x); P = (eye(2) - K*H)*P;
est_pos(k) = x(1); end
Tuning Q and R is everything. Too low Q → filter ignores new data; too high → noisy output.
Happy filtering! 🔍
Estimate position and velocity from noisy measurements.
% Plot plot(true_pos, 'g-', meas, 'ro', est_pos, 'b--') legend('True', 'Noisy', 'Kalman estimate')