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Maximum likelihood 3-D near-field source localization using the EM algorithm

机译:使用EM算法的最大似然3-D近场源定位

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In this paper, maximum likelihood estimator is proposed for passive localization of narrowband sources in the spherical coordinates (azimuth, elevation, range). We adapt expectation/maximization iterative method to solve the complicated multi-parameter optimization problem appearing on the 3-D localization problem. The proposed algorithm is based on maximum likelihood criterion, which employs the source signals recorded by 2-D array under near-field assumption. Expectation/maximization algorithm decomposes the observed data into its components and then estimates the parameters of each signal component separately providing computationally efficient solution to the resulting optimization problem. Finally, some numerical simulations illustrate the applicability and effectiveness of the proposed algorithm.
机译:在本文中,提出了一种最大似然估计器,用于在球坐标(方位角,仰角,范围)中对窄带源进行被动定位。我们采用期望/最大化迭代方法来解决3D定位问题中出现的复杂的多参数优化问题。该算法基于最大似然准则,该准则采用了二维阵列在近场假设下记录的源信号。期望/最大化算法将观察到的数据分解为其分量,然后分别估计每个信号分量的参数,从而为最终的优化问题提供计算上有效的解决方案。最后,一些数值模拟说明了该算法的适用性和有效性。

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