 a posteriori states</span>
z = zeros(LG, r);       <span class="comment">% INS/vor_dme measurements</span>
v = zeros(LG, r);       <span class="comment">% Kalman filter innovations</span>

A  = zeros(LG, n^2);    <span class="comment">% Transition-state matrices</span>
Pi = zeros(LG, n^2);    <span class="comment">% A priori covariance matrices</span>
Pp = zeros(LG, n^2);    <span class="comment">% A posteriori covariance matrices</span>
K  = zeros(LG, n*r);    <span class="comment">% Kalman gain matrices<