Maximum-Likelihood Direction Finding Under Elliptical Noise Using the EM Algorithm
Unlike subspace-based solutions of direction-of-arrival (DOA) estimation under non-Gaussian noise, where the only optional difference with the Gaussian case is the scatter/covariance matrix estimation method, maximum-likelihood (ML)-based DOA solutions need a different treatment under the non-Gaussi...
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| Published in | IEEE communications letters Vol. 23; no. 6; pp. 1041 - 1044 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
IEEE
01.06.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN | 1089-7798 1558-2558 |
| DOI | 10.1109/LCOMM.2019.2911518 |
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| Abstract | Unlike subspace-based solutions of direction-of-arrival (DOA) estimation under non-Gaussian noise, where the only optional difference with the Gaussian case is the scatter/covariance matrix estimation method, maximum-likelihood (ML)-based DOA solutions need a different treatment under the non-Gaussianity assumption. In this letter, we derive a particular ML-based DOA solution, called the expectation-maximization (EM) estimator, under the wide class of complex elliptically symmetric (CES) distributions. |
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| AbstractList | Unlike subspace-based solutions of direction-of-arrival (DOA) estimation under non-Gaussian noise, where the only optional difference with the Gaussian case is the scatter/covariance matrix estimation method, maximum-likelihood (ML)-based DOA solutions need a different treatment under the non-Gaussianity assumption. In this letter, we derive a particular ML-based DOA solution, called the expectation–maximization (EM) estimator, under the wide class of complex elliptically symmetric (CES) distributions. |
| Author | Wang, Xiaodong Karimi, Mahmood Baktash, Ebrahim |
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| Cites_doi | 10.1109/TVT.2018.2794322 10.1111/j.2517-6161.1977.tb01600.x 10.1109/TSP.2012.2212433 |
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| SubjectTerms | Algorithms Arrays CES noise Covariance matrix Direction finding Direction of arrival Direction-of-arrival estimation DOA estimation Economic models EM method Generators Maximum likelihood estimation Normal distribution Probability density function Random noise Symmetric matrices |
| Title | Maximum-Likelihood Direction Finding Under Elliptical Noise Using the EM Algorithm |
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