Abstract
In this paper we address target detection in correlated non-Gaussian noise. We introduce a powerful class of multivariate complex valued distribution that allows us to specify flexible non-Gaussian marginals, as well as correlation between the variables, while preserving circular symmetry. For noise belonging to this class, we study the fundamental problem of signal detection under different settings, and develop the needed (generalized) likelihood ratio tests. We also consider the problem of estimation of the noise parameters, and derive the maximum likelihood formulations. We compare the performance of the proposed methods using numerical simulations on synthetic data, and demonstrate the importance of using both correlations and non-Gaussiantiy.
Original language | English |
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Title of host publication | 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 4274-4278 |
Number of pages | 5 |
ISBN (Electronic) | 9781479999880 |
DOIs | |
State | Published - 18 May 2016 |
Event | 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Shanghai, China Duration: 20 Mar 2016 → 25 Mar 2016 |
Publication series
Name | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
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Volume | 2016-May |
ISSN (Print) | 1520-6149 |
Conference
Conference | 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 |
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Country/Territory | China |
City | Shanghai |
Period | 20/03/16 → 25/03/16 |
Bibliographical note
Publisher Copyright:© 2016 IEEE.
Keywords
- Circular symmetry
- copula
- detection
- non-Gaussian