Title :
An invariance property of some subspace-based detection algorithms
Author :
Basseville, Michèle
Author_Institution :
CNRS, IRISA, Rennes, France
fDate :
12/1/1999 12:00:00 AM
Abstract :
Subspace fitting estimates involve multidimensional parameter estimating functions having a particular product form. Based on estimating functions, the statistical local approach builds detection algorithms that enjoy a simple invariance property. This article investigates that invariance property for the detectors built on those two concepts
Keywords :
array signal processing; direction-of-arrival estimation; signal detection; statistical analysis; vibrations; DOA; array processing; directions of arrival; invariance property; multidimensional parameter estimating functions; product form; statistical local approach; subspace fitting estimates; subspace-based detection algorithms; vibration monitoring; Additive noise; Detection algorithms; Information filtering; Information filters; Parameter estimation; Sampling methods; Signal processing algorithms; Signal sampling; Signal to noise ratio; Testing;
Journal_Title :
Signal Processing, IEEE Transactions on
