Detection in Incompletely Characterized Colored Non-Gaussian Noise via Parametric Modeling
Abstract
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.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 01, 1986
- Accession Number
- ADA175402
Entities
People
- Debasis Sengupta
- Steven Kay
Organizations
- University of Rhode Island