Wang Kun, He Jin, Shu Ting, Liu Zhong
Department of Electronic Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.
Shanghai Key Laboratory of Intelligent Sensing and Recognition, Department of Electronic Engineering, Shanghai Jiaotong University, Shanghai 200240, China.
Sensors (Basel). 2016 Feb 19;16(2):248. doi: 10.3390/s16020248.
We propose a parallel factor (PARAFAC) analysis-based angle and polarization estimation algorithm for multiple coherent sources using a uniformly-spaced linear tripole sensor array. By forming a PARAFAC model using the spatial signature of the tripole array, the new algorithm requires neither spatial smoothing nor vector-field smoothing to decorrelate the signal coherency. We also establish that the angle-polarization parameters of K coherent signals can be uniquely determined by PARAFAC analysis, as long as the number of tripoles L ≥ 2K - 1 . In addition, the proposed algorithm can offer enhanced angle and polarization estimation accuracy by extending the interspacing of the tripoles beyond a half wavelength.
我们提出了一种基于平行因子（PARAFAC）分析的角度和极化估计算法，该算法用于使用均匀间隔线性三极子传感器阵列来估计多个相干源。通过利用三极子阵列的空间特征形成PARAFAC模型，新算法既不需要空间平滑也不需要矢量场平滑来消除信号相干性。我们还证明，只要三极子的数量(L≥2K - 1)，PARAFAC分析就可以唯一确定(K)个相干信号的角度-极化参数。此外，通过将三极子的间距扩展到超过半波长，所提出的算法可以提高角度和极化估计精度。
