SUBSPACE FITTING WITH DIVERSELY POLARIZED ANTENNA-ARRAYS
SUBSPACE FITTING WITH DIVERSELY POLARIZED ANTENNA-ARRAYS
复制标题
DOI：
10.1109/8.273313
复制
发表时间：
1993-12-01
影响因子：
5.7
通讯作者：
VIBERG, M
中科院分区：
文献类型：
--
作者：
SWINDLEHURST, A;VIBERG, M
双极化天线阵列广泛应用于射频领域。这种阵列所提供的响应的多样性可以大大改善对仅一个偏振分量敏感的阵列的测向性能。对于d个发射器，直接实现多维估计算法（例如，最大似然）将需要搜索3D参数：D到达方向（DOA）和2D极化参数。在本文中，我们提出了一个更有效的解决方案的基础上，所谓的噪声子空间拟合（NSF）算法。特别是，我们展示了如何解耦的NSF搜索到一个两步的过程中，DOA的估计分开。然后通过求解线性方程组获得偏振参数。这种方法的优点是搜索维度减少了三分之一，并且不需要初始极化估计。此外，该算法可以被证明，以产生渐近最小方差估计提供没有完美的相干信号。仿真例子包括比较NSF的方法与类似的概括的MUSIC算法。
Diversely polarized antenna arrays are widely used in RF applications. The diversity of response provided by such arrays can greatly improve direction finding performance over arrays sensitive to only one polarization component. For d emitters, directly implementing a multidimensional estimation algorithm (e.g., maximum likelihood) would require a search for 3d parameters: d directions of arrival (DOA's), and 2d polarization parameters. In this paper, we present a more efficient solution based on the so-called noise subspace fitting (NSF) algorithm. In particular, we show how to decouple the NSF search into a two-step procedure, where the DOA's are estimated separately. The polarization parameters are then obtained by solving a linear system of equations. The advantage of this approach is that the search dimension is reduced by a factor of three, and no initial polarization estimate is required. In addition, the algorithm can be shown to yield asymptotically minimum variance estimates provided no perfectly coherent signals are present. Simulation examples are included to compare the NSF approach with a similar generalization of the MUSIC algorithm.