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
Link To Document :
بازگشت