Signal subspace techniques for DOA estimation using higher order statistics

Author

Leyman, A.R. ; Durrani, T.S.

Author_Institution

Dept. of Electron. & Electr. Eng., Strathclyde Univ., Glasgow, UK

Volume

3

fYear

1995

fDate

9-12 May 1995

Firstpage

1956

Abstract

Eigendecomposition based techniques such as MUSIC and its variants constitute effective methods for determining the direction of arrival (DOA) estimates of narrowband sources. A new strategy which extends the MUSIC algorithm to higher order statistics (HOS) is proposed for estimation of the DOA. Also, we present a new method for the estimation of the number of multiple narrowband incoherent and coherent non-Gaussian source signals arriving on the array which we consider as a significant contribution. The performance of the technique is compared with other suggested HOS-based methods

Keywords

direction-of-arrival estimation; eigenvalues and eigenfunctions; higher order statistics; DOA estimates; DOA estimation; HOS; MUSIC algorithm; coherent nonGaussian source signals; direction of arrival; eigendecomposition; higher order statistics; multiple source signals; narrowband incoherent nonGaussian source signals; performance; signal subspace techniques; Array signal processing; Direction of arrival estimation; Gaussian noise; Higher order statistics; Multiple signal classification; Narrowband; Sensor arrays; Signal processing; Signal resolution; Spatial resolution;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on

Conference_Location

Detroit, MI

ISSN

1520-6149

Print_ISBN

0-7803-2431-5

Type

conf

DOI

10.1109/ICASSP.1995.480599

Filename

480599