Title :
Robust Multidimensional Matched Subspace Classifiers Based on Weighted Least-Squares
Author :
Salberg, Arnt-Børre ; Hanssen, Alfred ; Scharf, Louis L.
Author_Institution :
DolphiScan AS, Moelv
fDate :
3/1/2007 12:00:00 AM
Abstract :
We propose and design two classes of robust subspace classifiers for classification of multidimensional signals. Our classifiers are based on robust M-estimators and the least-median-of-squares principle, and we show that they may be unified as iterated reweighted oblique subspace classifiers. The performance of the proposed classifiers are demonstrated by two examples: noncoherent detection of space-time frequency-shift keying signals, and shape classification of partially occluded two-dimensional (2-D)_ objects. In both cases, the proposed robust subspace classifiers outperform the conventional subspace classifiers
Keywords :
least squares approximations; multidimensional signal processing; signal classification; signal detection; least-median-of-squares principle; multidimensional signals classification; robust multidimensional matched subspace classifiers; signals noncoherent detection; space-time frequency-shift keying signals; weighted least-squares; Detectors; Frequency shift keying; Gaussian noise; Interference; Multidimensional systems; Noise robustness; Object detection; Pattern recognition; Shape; Signal design; Noncoherent receivers; robust estimation; shape recognition; subspace classification;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2006.887560