A recursive linear MMSE filter for dynamic systems with unknown state vector means
| dc.contributor.author | Khodabandeh, A. | |
| dc.contributor.author | Teunissen, Peter | |
| dc.date.accessioned | 2017-01-30T13:51:42Z | |
| dc.date.available | 2017-01-30T13:51:42Z | |
| dc.date.created | 2014-09-18T20:00:20Z | |
| dc.date.issued | 2014 | |
| dc.identifier.citation | Khodabandeh, A. and Teunissen, P. 2014. A recursive linear MMSE filter for dynamic systems with unknown state vector means. International Journal on Geomathematics. 5 (1): pp. 17-31. | |
| dc.identifier.uri | http://hdl.handle.net/20.500.11937/35782 | |
| dc.identifier.doi | 10.1007/s13137-014-0058-0 | |
| dc.description.abstract |
In this contribution we extend Kalman-filter theory by introducing a new recursive linear minimum mean squared error (MMSE) filter for dynamic systems with unknown state-vector means. The recursive filter enables the joint MMSE prediction and estimation of the random state vectors and their unknown means, respectively. We show how the new filter reduces to the Kalman-filter in case the state-vector means are known and we discuss the fundamentally different roles played by the initialization of the two filters. | |
| dc.publisher | Springer | |
| dc.subject | Best linear unbiased estimation (BLUE) | |
| dc.subject | BLUE-BLUP recursion | |
| dc.subject | Minimummean squared error (MMSE) | |
| dc.subject | Kalman filter | |
| dc.subject | Best linear unbiased prediction (BLUP) | |
| dc.title | A recursive linear MMSE filter for dynamic systems with unknown state vector means | |
| dc.type | Journal Article | |
| dcterms.source.volume | 5 | |
| dcterms.source.startPage | 17 | |
| dcterms.source.endPage | 31 | |
| dcterms.source.issn | 1869-2672 | |
| dcterms.source.title | International Journal on Geomathematics | |
| curtin.note |
The final publication is available at Springer via | |
| curtin.department | Department of Spatial Sciences | |
| curtin.accessStatus | Open access |