Detection in incompletely characterized colored non-Gaussian noise via parametric modeling

The problem of detecting a signal known except for amplitude in incompletely characterized colored non-Gaussian noise is addressed. The problem is formulated as a testing of composite hypotheses using parametric models for the statistical behavior of the noise. A generalized likelihood ratio test is employed. It is shown that for a symmetric noise probability density function the detection performance is asymptotically equivalent to that obtained for a detector designed with a priori knowledge of the noise parameters. Non-Gaussian distributions of the noise are found to be more favorable for the purpose of detection as compared to the Gaussian distribution. Acceiw fcr NTIS CRA&A DTIC TAB l U,,ain~Ou, ,' 1 LI