This paper deals with the problem of covariance matrix estimation for radar signal processing applications. We propose and analyze a class of estimators which do not require any knowledge about the probability distribution of the sample support and exploit the characteristics of the positive definite matrix space. Any estimator of the class is associated with a suitable distance in the considered space and is defined as the geometric barycenter of some basic covariance matrix estimates obtained from the available secondary data set. © 2012 IEEE.
Pallotta, L., Aubry, A., De Maio, A., Farina, A. (2012). Geometric barycenters and their application to radar training data selection/target detection. In Proceedings International Radar Symposium (pp.85-90) [10.1109/IRS.2012.6233294].
Geometric barycenters and their application to radar training data selection/target detection
Pallotta L.;
2012-01-01
Abstract
This paper deals with the problem of covariance matrix estimation for radar signal processing applications. We propose and analyze a class of estimators which do not require any knowledge about the probability distribution of the sample support and exploit the characteristics of the positive definite matrix space. Any estimator of the class is associated with a suitable distance in the considered space and is defined as the geometric barycenter of some basic covariance matrix estimates obtained from the available secondary data set. © 2012 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
