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Direction of Arrival Estimation for Complex Sources Through $\ell _1$ Norm Sparse Bayesian Learning

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In this letter, Laplace distribution is used to model the prior for the direction of arrival (DoA) of sources. In order to incorporate the real and imaginary part of the… Click to show full abstract

In this letter, Laplace distribution is used to model the prior for the direction of arrival (DoA) of sources. In order to incorporate the real and imaginary part of the received signal, we propose a method that pairwise estimates the hyperparameters for parts of the signal coefficients. In addition, we propose a multitask algorithm to extend the application of our method to the situation where multiple measurements are available. Nonuniform linear arrays are used to demonstrate the validity and advantages of the proposed method including its improved efficiency and accuracy compared with the state-of-art DoA estimation methods.

Keywords: estimation complex; direction; arrival estimation; direction arrival; complex sources

Journal Title: IEEE Signal Processing Letters
Year Published: 2019

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