A signal subspace beamformer

Author

Farrier, D. ; Prosper, L.

Author_Institution

Dept. of Electr. Eng., Southampton Univ., UK

fYear

1990

fDate

3-6 Apr 1990

Firstpage

2815

Abstract

It is shown that it is possible to approximate a maximum-likelihood method, leading to a very high performance subspace algorithm. This has all the advantages of subspace methods (i.e. inexpensive), but with much better threshold performance than existing methods such as MUSIC. The method is applicable to arbitrary array geometry, and is demonstrated on both linear and curved arrays with limited snapshots, multipath, and with correlated (but unknown) noise. The results demonstrate the robustness of the algorithm and its superiority over MUSIC, with no additional cost

Keywords

computerised signal processing; digital simulation; probability; signal detection; MUSIC; arbitrary array geometry; computerised signal processing; correlated noise; cost; curved arrays; limited snapshots; linear arrays; maximum-likelihood method; signal detection; signal subspace beamformer; simulation; subspace algorithm; Array signal processing; Computational complexity; Costs; Covariance matrix; Eigenvalues and eigenfunctions; Geometry; Iterative algorithms; Iterative methods; Multiple signal classification; Noise robustness; Working environment noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on

Conference_Location

Albuquerque, NM

ISSN

1520-6149

Type

conf

DOI

10.1109/ICASSP.1990.116211

Filename

116211