The quaternion coherence problem exists in the data model of the conventional dimensional reduced quaternion estimation of signal parameters via rotational invariance techniques(DRQ-ESPRIT), and DRQ-ESPRIT would lose degrees of freedom(DOFs)when it is used to implement the spatial smooth operation. An improved DRQ-ESPRIT algorithm based on 2-level nested vector-sensor array is proposed in this paper. The quaternion coherence problem is solved by switching the multiplication sequence of spatial direction vector and electric field. Meanwhile, nested array and Khatri-Rao subspace approach are used to increase the number of DOFs, thus the proposed algorithm can estimate more incident sources than DRQ-ESPRIT, and the estimations of direction of arrival(DOA)and polarization parameters are more accurate. Simulation results demonstrate the effectiveness of the proposed algorithm.
同点正交配置磁环和电偶极子(Co-centered Orthogonal Loop and Dipole,COLD)是常用的二分量电磁矢量传感器之一,但是COLD传感器没有充分利用磁环和电偶极子分量的空间信息.针对由COLD传感器组成的均匀线阵,磁环分量保持不变,将电偶极子分量沿正交方向稀疏拉伸,形成L形阵,扩展阵列的空间孔径,提出了基于广义旋转不变的降维多重信号分类算法.该算法利用L形阵的几何构形,将导向矢量分隔成三部分,利用广义旋转不变矩阵分别估计各个部分,使得波达角和极化参数仅需一维谱峰搜索就可以估计得到.同时,在参考点处新增一个电偶极子天线,利用四元数模型解决了由于稀疏拉伸引起的相位周期模糊问题.仿真实验验证了所提算法的有效性.
同点正交配置磁环和电偶极子(Co-centered orthogonal loop and dipole,COLD)是一种最常用的二分量电磁矢量传感器,但是COLD传感器没有充分利用磁环和电偶极子分量的空间信息。本文针对由COLD传感器组成的均匀线阵(Uniform linear array,ULA),将所有磁环和电偶极子分量分别沿两个正交方向均匀拉伸,形成L形阵,扩展阵列的空间孔径,并提出了基于广义旋转不变的降维多重信号分类算法(Dimension reduction multiple signal classification method based on generalized rotational invariance,GRIDR-MUSIC)。所提算法利用L形阵的几何构形,将导向矢量分隔成三部分,通过两个正交ULA的广义旋转不变结构,分别估计各个部分,使得波达角(Direction of arrival)和极化参数仅需一维谱峰搜索就可以估计得到,且无需参数匹配。最后,仿真实验验证了所提算法的有效性。
