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Numerical Computation of Wishart Eigenvalue Distributions for Multistatic Radar Detection


Abstract Eigenvalues of the Gram matrix formed from received data frequently appear in sufficient detection statistics for multi-channel detection with Generalized Likelihood Ratio (GLRT) and Bayesian tests. In a frequently presented model for passive radar, in which the null hypothesis is that the channels are independent and contain only complex white Gaussian noise and the alternative hypothesis is that the channels contain a common rank-one signal in the mean, the GLRT statistic is the largest eigenvalue $\lambda_1$ of the Gram matrix formed from data. This Gram matrix has a Wishart distribution. Although exact expressions for the distribution of $\lambda_1$ are known under both hypotheses, numerically calculating values of these distribution fu... (more)
Created Date 2019
Contributor Jones, Scott (Author) / Cochran, Douglas (Advisor) / Berisha, Visar (Committee member) / Bliss, Daniel (Committee member) / Kosut, Oliver (Committee member) / Richmond, Christ (Committee member) / Arizona State University (Publisher)
Subject Electrical engineering / Statistics / Applied mathematics / Multi-channel detection / Passive Radar / Wishart
Type Doctoral Dissertation
Extent 114 pages
Language English
Copyright
Note Doctoral Dissertation Electrical Engineering 2019
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis