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- W2945889962 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." @default.
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- W2945889962 date "2019-06-01" @default.
- W2945889962 modified "2023-10-16" @default.
- W2945889962 title "Maximum-Likelihood Direction Finding Under Elliptical Noise Using the EM Algorithm" @default.
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- W2945889962 doi "https://doi.org/10.1109/lcomm.2019.2911518" @default.
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