Detection of sources using bootstrap techniques

Author

Brcich, Ramon F. ; Zoubir, Abdelhak M. ; Pelin, Per

Author_Institution

Sch. of Electr. & Comput. Eng., Curtin Univ. of Technol., Bentley, WA, Australia

Volume

50

Issue

2

fYear

2002

fDate

2/1/2002 12:00:00 AM

Firstpage

206

Lastpage

215

Abstract

Source detection in array processing can be viewed as a test for equality of eigenvalues. Such a test is proposed, based on a multiple test procedure that considers all pairwise comparisons between eigenvalues. Using the bootstrap to estimate the null distributions of the test statistics results in a procedure with minimal assumptions on the nature of the signal. Simulations show that the proposed test is superior to information theoretic criteria such as the MDL, which are based on Gaussian signals and large sample sizes. Performance in most cases exceeds the more powerful sphericity test

Keywords

array signal processing; eigenvalues and eigenfunctions; signal detection; statistical analysis; array processing; bootstrap techniques; eigenvalues; multiple test procedure; null distributions; pairwise comparisons; source detection; test statistics; Array signal processing; Australia; Degradation; Eigenvalues and eigenfunctions; Gaussian noise; Sequential analysis; Statistical analysis; Statistical distributions; Telecommunication computing; Testing;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.978376

Filename

978376