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- Title
Adaptive Bayesian detection for multiple-input multiple-output radar in compound-Gaussian clutter with random texture.
- Authors
Lingjiang Kong; Na Li; Guolong Cui; Haining Yang; Qing Huo Liu
- Abstract
In this study, the authors consider the adaptive detection with multiple-input multiple-output radar in compound-Gaussian clutter. The covariance matrices of the primary and the secondary data share a common structure, but different power levels (textures). A Bayesian framework is exploited where both the textures and the structure are assumed to be random. Precisely, the textures follow Gamma distribution or inverse Gamma distribution and the structure is drawn from an inverse complex Wishart distribution. In this framework, two generalised likelihood ratio tests are derived. Finally, they evaluate the capabilities of the proposed detectors against compound-Gaussian clutter as well as their superiority with respect to some existing techniques.
- Subjects
MIMO systems; RADAR research; ANALYSIS of covariance; MATRICES (Mathematics); GAMMA distributions
- Publication
IET Radar, Sonar & Navigation (Wiley-Blackwell), 2016, Vol 10, Issue 4, p689
- ISSN
1751-8784
- Publication type
Article
- DOI
10.1049/iet-rsn.2015.0241