A MAXIMUM A-POSTERIORI ALGORITHM FOR RECONSTRUCTION OF TARGETS IN INCOMPLETELY DEFINED CORRELATED NOISE

Authors
WILLIS AJ KOCH RD SPEAR B KLOPPER A
Citation
Aj. Willis et al., A MAXIMUM A-POSTERIORI ALGORITHM FOR RECONSTRUCTION OF TARGETS IN INCOMPLETELY DEFINED CORRELATED NOISE, IEEE transactions on signal processing, 46(5), 1998, pp. 1439-1443
Citations number
15
Categorie Soggetti
Engineering, Eletrical & Electronic
Journal title
IEEE transactions on signal processing → ACNP
ISSN journal
1053587X
Volume
46
Issue
5
Year of publication
1998
Pages
1439 - 1443
Database
ISI
SICI code
1053-587X(1998)46:5<1439:AMAAFR>2.0.ZU;2-U
Abstract
The maximum a posteriori (MAP) line spectral estimator used to charact erize sinusoids in data corrupted by Gaussian noise of unknown correla tion is generalized to the case where an experimental estimate of nois e covariance is available. The estimator is robust to noise with mean square error and standard deviation falling below that of the classica l MAP for increasing number of samples, while approaching classical MA P for the case of no prior knowledge.