Detection and parameter estimation of multiple nonGaussian sources via higher order statistics

Author

Shamsunder, Sanyogita ; Giannakis, Georgios B.

Author_Institution

Dept. of Electr. Eng., Virginia Univ., Charlottesville, VA, USA

Volume

42

Issue

5

fYear

1994

fDate

5/1/1994 12:00:00 AM

Firstpage

1145

Lastpage

1155

Abstract

Simultaneous detection of signal arriving at a sensor array and estimation of their parameters is carried out using higher than second-order statistics. Information theoretic criteria which are (at least theoretically) insensitive to additive Gaussian noise are developed to estimate consistently the parameters as well as the number of non-Gaussian but unknown sources. The novel cumulant based algorithms can estimate parameters of more sources with fewer sensors. Simulations confirm superior resolution capability of the proposed methods for both narrow-band and wideband sources in the presence of low SNR additive correlated Gaussian noise

Keywords

array signal processing; parameter estimation; random noise; signal detection; statistical analysis; additive correlated Gaussian noise; higher order statistics; information theory; low SNR; multiple nonGaussian sources; narrow-band sources; parameter estimation; resolution; sensor array; signal detection; wideband sources; Additive noise; Array signal processing; Colored noise; Direction of arrival estimation; Gaussian noise; Higher order statistics; Parameter estimation; Sensor arrays; Signal processing; Signal processing algorithms;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.295204

Filename

295204