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020 ▼a 9781088369982
035 ▼a (MiAaPQ)AAI22588433
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 247004
0820 ▼a 519
1001 ▼a Jones, Scott.
24510 ▼a Numerical Computation of Wishart Eigenvalue Distributions for Multistatic Radar Detection.
260 ▼a [S.l.]: ▼b Arizona State University., ▼c 2019.
260 1 ▼a Ann Arbor: ▼b ProQuest Dissertations & Theses, ▼c 2019.
300 ▼a 115 p.
500 ▼a Source: Dissertations Abstracts International, Volume: 81-03, Section: B.
500 ▼a Advisor: Cochran, Douglas.
5021 ▼a Thesis (Ph.D.)--Arizona State University, 2019.
506 ▼a This item must not be sold to any third party vendors.
520 ▼a 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 貫1 of the Gram matrix formed from data. This Gram matrix has a Wishart distribution. Although exact expressions for the distribution of 貫1 are known under both hypotheses, numerically calculating values of these distribution functions presents difficulties in cases where the dimension of the data vectors is large. This dissertation presents tractable methods for computing the distribution of 貫1 under both the null and alternative hypotheses through a technique of expanding known expressions for the distribution of 貫1 as inner products of orthogonal polynomials. These newly presented expressions for the distribution allow for computation of detection thresholds and receiver operating characteristic curves to arbitrary precision in floating point arithmetic. This represents a significant advancement over the state of the art in a problem that could previously only be addressed by Monte Carlo methods.
590 ▼a School code: 0010.
650 4 ▼a Electrical engineering.
650 4 ▼a Statistics.
650 4 ▼a Applied mathematics.
690 ▼a 0544
690 ▼a 0463
690 ▼a 0364
71020 ▼a Arizona State University. ▼b Electrical Engineering.
7730 ▼t Dissertations Abstracts International ▼g 81-03B.
773 ▼t Dissertation Abstract International
790 ▼a 0010
791 ▼a Ph.D.
792 ▼a 2019
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15493086 ▼n KERIS ▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다.
980 ▼a 202002 ▼f 2020
990 ▼a ***1008102
991 ▼a E-BOOK