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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。
Co-centered orthogonal loop and dipole (COLD) is one of the most commonly used two-component electromagnetic vector sensors, but the COLD sensor does not take full advantage of the magnetic ring and electric dipole components of the space information. In this paper, aiming at the uniform linear array (ULA) composed of COLD sensors, all the magnetic rings and electric dipole components are uniformly stretched in two orthogonal directions to form an L-shaped array, which expands the spatial aperture of the array, And a dimension reduction multiple signal classification method based on generalized rotational invariance (GRIDR-MUSIC) is proposed. The proposed algorithm utilizes the geometry of the L-shaped array and divides the steering vector into three parts. The generalized rotationally invariant structures of two orthogonal ULAs are used to estimate the parts separately such that the Direction of Arrival and the polarization Parameters can be estimated with only one-dimensional peak search without parameter matching. Finally, simulation results verify the effectiveness of the proposed algorithm.