TY - GEN A1 - Sagnol, Guillaume A1 - Harman, Radoslav T1 - Optimal Designs for Steady-state Kalman filters N2 - We consider a stationary discrete-time linear process that can be observed by a finite number of sensors. The experimental design for the observations consists of an allocation of available resources to these sensors. We formalize the problem of selecting a design that maximizes the information matrix of the steady-state of the Kalman filter, with respect to a standard optimality criterion, such as $D-$ or $A-$optimality. This problem generalizes the optimal experimental design problem for a linear regression model with a finite design space and uncorrelated errors. Finally, we show that under natural assumptions, a steady-state optimal design can be computed by semidefinite programming. T3 - ZIB-Report - 14-39 KW - Optimal Design KW - Kalman Filter KW - Semidefinite programming Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-52808 SN - 1438-0064 ER -