User`s guide

Kalman Filtering
9-59
you can implement the time-varying filter with the following for loop.
P = B*Q*B'; % Initial error covariance
x = zeros(3,1); % Initial condition on the state
ye = zeros(length(t),1);
ycov = zeros(length(t),1);
for i=1:length(t)
% Measurement update
Mn = P*C'/(C*P*C'+R);
x = x + Mn*(yv(i)–C*x); % x[n|n]
P = (eye(3)–Mn*C)*P; % P[n|n]
ye(i) = C*x;
errcov(i) = C*P*C';
% Time update
x = A*x + B*u(i); % x[n+1|n]
P = A*P*A' + B*Q*B'; % P[n+1|n]
end