DocumentCode :
1749411
Title :
Wavelets in the frequency domain for narrowband process detection
Author :
Willett, Peter ; Wang, Zhen ; Streit, Roy
Author_Institution :
Connecticut Univ., Storrs, CT, USA
Volume :
5
fYear :
2001
fDate :
2001
Firstpage :
3193
Abstract :
Detecting signals that are long, weak, and narrowband is a well known and important problem in acoustic signal processing. In this paper an ad hoc scheme is developed: its stages include the DFT, a multiresolution decomposition in the frequency domain, and a GLRT. The computational load is light, and the performance is remarkably good. This is so not just in the original narrowband situation, but also, due to an inherent adaptivity to the data, in the detection of signals that are relatively broadband in nature. Generalizations are given to CFAR operation in both prewhitened and unwhitened cases, and to the detection of multi-band signals. As regards the last, it is discovered that there is little loss from over-estimating the number of bands
Keywords :
acoustic signal processing; adaptive signal detection; discrete Fourier transforms; frequency-domain analysis; signal resolution; wavelet transforms; DFT; GLRT; acoustic signal processing; adaptive signal detection; computational load; frequency domain; multi-band signal detection; multiresolution decomposition; narrowband process detection; wavelets; Acoustic signal detection; Bandwidth; Detectors; Frequency domain analysis; Maximum likelihood detection; Narrowband; Signal detection; Signal processing; Testing; Wavelet domain;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on
Conference_Location :
Salt Lake City, UT
ISSN :
1520-6149
Print_ISBN :
0-7803-7041-4
Type :
conf
DOI :
10.1109/ICASSP.2001.940337
Filename :
940337
Link To Document :
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