Abstract
We consider a sensor allocation problem for the Kalman-Bucy filter within an information theoretic framework. For the signal and the observation of Kalman-Bucy filter, the mutual information between them is determined by the power of the drift-term in the innovations process and we cannot make the mutual information larger without increasing the power of the innovations process. Under a constraint on the mean square power of the drift-term in the innovations process, a set of equations is derived to compute the optimal gain matrix for the sensors which minimizes the least-squares estimation error.
