Title :
Detection and localization of multiple sources in noise with unknown covariance
Author_Institution :
RAFAEL, Haifa, Israel
fDate :
1/1/1992 12:00:00 AM
Abstract :
The authors present a novel technique for the detection and localization of multiple sources in the presence of noise with unknown and arbitrary covariance. The technique is applicable to coherent and noncoherent signals and to arbitrary array geometry and is based on Rissanen´s minimum description length (MDL) principle (1989) for model selection. Its computational load is comparable to that of analogous techniques for white noise. Simulation results demonstrating the performance of this technique are included
Keywords :
noise; signal detection; Rissanen´s minimum description length; arbitrary array geometry; arbitrary covariance; coherent signals; model selection; multiple source detection; multiple source localisation; noise; noncoherent signals; unknown covariance; Computational modeling; Covariance matrix; Geometry; Narrowband; Parametric statistics; Sensor arrays; Sensor phenomena and characterization; Signal resolution; Solid modeling; White noise;
Journal_Title :
Signal Processing, IEEE Transactions on