基于稀疏拉伸式COLD传感器的波达角和极化参数估计

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.

Joint DOA and polarization parameters estimation based on sparsely stretched COLD sensors

The co-centered orthogonal loop and dipole (COLD) sensor is one of the most widely used two-component electromagnetic vector sensors. However, the COLD sensor does not make full use of the two component spatial aperture. The uniform linear array, which consists of COLD sensors, is considered. In order to extend the spatial aperture, all loop-components maintain the same, and all dipole-components are sparsely uniformly stretched along the orthogonal direction, thus an L-shaped array is formed. A generalized rotational invariance based dimension reduction multiple signal classification method (GRIDR-MUSIC) is proposed. The proposed algorithm uses the L-shaped array geometry to separate the steering vector into three parts, and uses the generalized rotational invariance matrix to estimate each part separately, thus direction of arrival (DOA) and polarization parameters can be estimated by only one-dimensional spectral peak search. In addition, a dipole is added in the conference point, and the quaternion model is used to resolve the phase cyclic ambiguity caused by sparsely stretching operation. Finally, the numerical simula-tions show the effectiveness of the proposed algorithm.