Detection of non-Gaussian signals in non-Gaussian noise using the bispectrum

The problem of detecting a non-Gaussian time series in the presence of additive Gaussian or non-Gaussian noise is cast into a classical hypothesis testing framework, using the sample bispectrum as the test statistic. The power of the test is demonstrated as a function of signal-to-noise ratio, the d...

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Bibliographic Details
Published in:IEEE transactions on acoustics, speech, and signal processing speech, and signal processing, 1990-07, Vol.38 (7), p.1126-1131
Main Authors: Hinich, M.J., Wilson, G.R.
Format: Article
Language:English
Subjects:
Additive noise
Biomedical measurements
Gaussian noise
Geophysical measurements
Noise measurement
Plasma measurements
Sea measurements
Signal detection
Signal processing
Testing
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Summary:The problem of detecting a non-Gaussian time series in the presence of additive Gaussian or non-Gaussian noise is cast into a classical hypothesis testing framework, using the sample bispectrum as the test statistic. The power of the test is demonstrated as a function of signal-to-noise ratio, the degree of skewness of the signal, and processing parameters. The results are compared to the power of a classical energy detection test. It is concluded that the bispectrum can be used effectively to detect non-Gaussian signals in the presence of interfering noise and that it may perform better, depending on the degree of non-Gaussianity, than energy detection.< >
ISSN:0096-3518
DOI:10.1109/29.57541