DocumentCode
1459948
Title
Adaptive detection for unknown noise power spectral densities
Author
Kay, Steven
Author_Institution
Dept. of Electr. & Comput. Eng., Rhode Island Univ., Kingston, RI, USA
Volume
47
Issue
1
fYear
1999
fDate
1/1/1999 12:00:00 AM
Firstpage
10
Lastpage
21
Abstract
The detection of a known broadband signal in colored noise of unknown power spectral density is addressed. Motivated by the consistency of the integrated periodogram, a new detector is proposed. Its asymptotic performance is proven to be only slightly poorer than the optimal but unrealizable Neyman-Pearson detector. It also possesses the CFAR property asymptotically and should therefore be quite valuable in practice. For finite data records, it is shown by computer simulation to significantly outperform the conventional matched filter (without prewhitening) under realistic conditions encountered in practice
Keywords
Gaussian noise; adaptive signal detection; spectral analysis; CFAR property; adaptive detection; asymptotic performance; broadband signal; colored noise; finite data records; integrated periodogram; unknown noise power spectral densities; Autocorrelation; Colored noise; Computer simulation; Detectors; Gaussian noise; Helium; Matched filters; Narrowband; Statistical analysis; Testing;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.738235
Filename
738235
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