Optimal Designs for Steady-state Kalman filters
Please always quote using this URN: urn:nbn:de:0297-zib-52808
- 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.
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| Author: | Guillaume Sagnol, Radoslav Harman |
|---|---|
| Document Type: | ZIB-Report |
| Tag: | Kalman Filter; Optimal Design; Semidefinite programming |
| MSC-Classification: | 93-XX SYSTEMS THEORY; CONTROL (For optimal control, see 49-XX) |
| Date of first Publication: | 2014/10/15 |
| Series (Serial Number): | ZIB-Report (14-39) |
| ISSN: | 1438-0064 |
