In this paper we proposed deterministic maximum likelihood approach for estimating the direction of arrival and range parameters of the near-field sources. Direct maximum likelihood estimation of near-field source parameters results in complicated multi-parameter optimization problems, we therefore reformulated the estimation problem in terms of actual-dam sample, called the incomplete data, and a hypothetical data set, called the complete data, and then devised the Expectation/Maximization (EM) iterative method for obtaining maximum likelihood estimates. The EM 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. The applicability and effectiveness of the proposed algorithm is illustrated by some numerical simulations.%本文介绍了一种对近场声源的距离和方位参数的确定性最大似然估计方法.直接的对近场声源参数的最大似然估计产生了复杂的多参数优化问题,我们在实际采样数据(非完全数据)和假设数据(完全数据)等方面重新构建这个问题,最后提出运用期望最大化迭代方法获得最大似然估计.期望最大化算法将观测数据分解,然后对于最优化问题,运用有效的计算措施单独估计每个信号成分的参数.这种算法的应用性和有效性通过一定的仿真得到了验证.
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