Regularised parallel factor analysis for the estimation of direction-of-arrival and polarisation with a single electromagnetic vector-sensor
Regularised parallel factor analysis for the estimation of direction-of-arrival and polarisation with a single electromagnetic vector-sensor
复制标题
使用单个电磁矢量传感器估计到达方向和偏振的正则并行因子分析
DOI：
10.1049/iet-spr.2009.0221
复制
发表时间：
2011-07-01
影响因子：
1.7
通讯作者：
Xu, Y. -G.
中科院分区：
文献类型：
--
作者：
Gong, X. -F.;Liu, Z. -W.;Xu, Y. -G.
本研究考虑基于单个六分量电磁矢量传感器的到达方向 (DOA) 和偏振估计问题。在正则化框架内建立了融合传感器信号二阶和四阶统计量的正则化并行因子分析（PARAFAC）模型。通过利用该三线性模型和 PARAFAC 之间的联系，可以唯一地识别转向矢量，从中可以进一步获得二维 DOA 和偏振态的明确估计。该方法以张量方式结合了二阶统计量良好的方差特性和四阶累积量（FOC）固有的多不变性结构，在存在噪声和有限数据长度的情况下，比通过旋转不变性技术和基于 FOC 的 PARAFAC 的信号参数正则化估计提供更好的性能。提供仿真来说明所提出方法的性能。
This study considers the problem of direction-of-arrival (DOA) and polarisation estimation based on a single six-component electromagnetic vector-sensor. A regularised parallel factor analysis (PARAFAC) model that fuses both second- and fourth-order statistics of the sensor signal is established within the regularised framework. The steering vectors can be uniquely identified by exploiting the link between this trilinear model and PARAFAC, from which unambiguous estimation of 2-D DOAs and polarisation states can be further obtained. The proposed method combines the nice variance property of second-order statistics and the intrinsic multi-invariance structure of fourth-order cumulant (FOC) in a tensorial manner, and offers better performance than regularised estimation of signal parameters via rotational invariance techniques and FOC-based PARAFAC in the presence of noise and finite data length. Simulations are provided to illustrate the performance of the proposed method.