Robust auto-focusing wideband DOA estimation
Robust auto-focusing wideband DOA estimation
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DOI：
10.1016/j.sigpro.2005.04.009
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发表时间：
2006
期刊：
影响因子：
--
通讯作者：
F. Sellone
中科院分区：
文献类型：
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作者：
F. Sellone
在过去的十年中，人们越来越关注开发用于估计携带宽带信号的波前的到达方向（DOA）以定位发射源的技术。相干信号子空间方法（CSM）是基于信号子空间概念的最常用的迭代方法之一，由于其处理相干源的能力，同时显示出非常好的检测和分辨率阈值，低偏差和高精度。CSM的核心是使用所谓的聚焦矩阵，其特性强烈影响其整体性能。在文献中，已经提出了几个聚焦矩阵，其中最有效的往往需要初始估计的DOA，这可能是一个缺点的整体估计过程。此外，经典的聚焦设计技术没有考虑这样的事实，即在算法的每次迭代中，估计的DOA可能不同于流形应聚焦的实际DOA。在本文中，我们提出了一种新的聚焦矩阵的设计技术，旨在抵消其他经典聚焦矩阵的一些主要缺点。结果表明，类的旋转信号子空间和信号子空间变换聚焦矩阵留下空间，进一步优化可用的自由度，利用这里创建一个CSM对DOA估计误差鲁棒。为此，该方法被称为鲁棒相干信号子空间方法（R-CSM）。由于这些新的聚焦矩阵的特点，不再需要经典CSM的初始预处理阶段。此外，由于在每次迭代中使用自由度来使聚焦越来越靠近估计的DOA，因此提高了收敛速度。
Within the last decade there has been a growing interest in developing techniques for the estimation of the direction of arrival (DOA) of wavefronts carrying wideband signals in order to locate the emitting sources. The coherent signal-subspace method (CSM) is one of the most largely adopted iterative technique based upon the concept of signal-subspace, due to its ability in handling coherent sources, while showing very good detection and resolution thresholds, low bias and high accuracy. Central to CSM is the use of the so-called focusing matrices, whose characteristics strongly influence its overall performance. In the literature, several focusing matrices have been proposed and the most effective of them often require initial estimation of the DOAs, which could be a drawback for the overall estimation procedure. Furthermore classical focusing design techniques do not take into account the fact that at each iteration of the algorithm estimated DOAs may differ from the actual ones on which the manifold should be focused. In this paper we propose a novel focusing matrices design technique aimed at counteracting some of the main disadvantages of other classical focusing matrices. It is shown that the classes of Rotational Signal Subspace and Signal Subspace Transformation focusing matrices leave room for further optimization of the available degrees of freedom, that are exploited here to create a CSM robust against DOA estimation errors. For this reason, the proposed method is referred to as robust coherent signal-subspace method (R-CSM). Thanks to the peculiarities of these novel focusing matrices, the initial preprocessing stage of the classical CSM is no longer required. Furthermore, the convergence speed is improved, because at each iteration the degrees of freedom are used to concentrate the focusing closer and closer about the estimated DOAs.