DocumentCode
1606437
Title
Resampling based techniques for source detection in array processing
Author
Brcich, Ramon F. ; Zoubir, Abdelhak M.
Author_Institution
Sch. of Electr. & Comput. Eng., Curtin Univ. of Technol., Perth, WA, Australia
fYear
2001
fDate
6/23/1905 12:00:00 AM
Firstpage
26
Lastpage
29
Abstract
The source detection problem in array processing can be considered as a test for the equality of eigenvalues. This approach is implemented through a multiple hypothesis procedure which compares all pairwise differences between eigenvalues. A resampling procedure is used to estimate the null distributions of the test statistics, an advantage for small sample sizes or non-Gaussian signals since traditional techniques such as the minimum description length (MDL) assume Gaussianity. Simulations show the increased performance of the test compared to the MDL for small samples or non-Gaussian signals, with a noticeable improvement over the more accurate sphericity test
Keywords
array signal processing; eigenvalues and eigenfunctions; signal detection; signal sampling; statistical analysis; MDL; array processing; bias estimation; eigenvalues; minimum description length; multiple hypothesis procedure; nonGaussian signals; null distribution estimation; pairwise differences; resampling; simulations; small sample sizes; source detection; sphericity test; test statistics; Array signal processing; Australia; Computational efficiency; Eigenvalues and eigenfunctions; Gaussian distribution; Gunshot detection systems; Statistical analysis; Statistical distributions; Telecommunication computing; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Statistical Signal Processing, 2001. Proceedings of the 11th IEEE Signal Processing Workshop on
Print_ISBN
0-7803-7011-2
Type
conf
DOI
10.1109/SSP.2001.955213
Filename
955213
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