论文标题
在存在未知均匀噪声的情况下，用于DOA估计的EM和SAGE算法
EM and SAGE algorithms for DOA Estimation in the Presence of Unknown Uniform Noise
论文作者
论文摘要
预期最大化（EM）和空间偏置的广义EM（SAGE）算法已应用于已知噪声中的到达方向（DOA）估计。在这项工作中，提出了两种算法以在未知均匀噪声中进行DOA估计。确定性和随机信号模型均被考虑。此外，还提出了适用于噪声假设的修改后的EM（MEM）算法。这些提出的算法得到改进，以确保当源的能力不平等时稳定。改进后，数值结果表明，EM算法与MEM算法具有相似的收敛性，而SAGE算法的表现优于确定性信号模型的EM和MEM算法。此外，数值结果表明，从随机信号模型中处理相同的样品，确定性信号模型的鼠尾草算法需要最少的迭代。
The expectation-maximization (EM) and space-alternating generalized EM (SAGE) algorithms have been applied to direction of arrival (DOA) estimation in known noise. In this work, the two algorithms are proposed for DOA estimation in unknown uniform noise. Both the deterministic and stochastic signal models are considered. Moreover, a modified EM (MEM) algorithm applicable to the noise assumption is also proposed. These proposed algorithms are improved to ensure the stability when the powers of sources are unequal. After being improved, numerical results illustrate that the EM algorithm has similar convergence with the MEM algorithm and the SAGE algorithm outperforms the EM and MEM algorithms for the deterministic signal model. Furthermore, numerical results show that processing the same samples from the stochastic signal model, the SAGE algorithm for the deterministic signal model requires the fewest iterations.
