National Digital Switching System Engineering and Technological Research Center (NDSC), Zhengzhou 86-450001, China.
Sensors (Basel). 2019 Feb 25;19(4):978. doi: 10.3390/s19040978.
In practical applications, the assumption of omnidirectional elements is not effective in general, which leads to the direction-dependent mutual coupling (MC). Under this condition, the performance of traditional calibration algorithms suffers. This paper proposes a new self-calibration method based on the time-frequency distributions (TFDs) in the presence of direction-dependent MC. Firstly, the time-frequency (TF) transformation is used to calculate the space-time-frequency distributions (STFDs) matrix of received signals. After that, the estimated steering vector and corresponding noise subspace are estimated by the steps of noise removing, single-source TF points extracting and clustering. Then according to the transformation relationship between the MC coefficients, steering vector and MC matrix, we deduce a set of linear equations. Finally, with two-step alternating iteration, the equations are solved by least square method in order to estimate DOA and MC coefficients. Simulations results show that the proposed algorithm can achieve direction-dependent MC self-calibration and outperforms the existing algorithms.
在实际应用中，全向元的假设并不总是有效，这会导致方向相关的互耦（MC）。在这种情况下，传统的校准算法的性能会受到影响。本文提出了一种新的自校准方法，该方法基于存在方向相关 MC 时的时频分布（TFD）。首先，使用时频（TF）变换来计算接收信号的空时频分布（STFD）矩阵。然后，通过噪声去除、单源 TF 点提取和聚类等步骤来估计估计的导向矢量和相应的噪声子空间。然后，根据 MC 系数、导向矢量和 MC 矩阵之间的变换关系，推导出一组线性方程。最后，通过两步交替迭代，使用最小二乘法求解方程组，以估计 DOA 和 MC 系数。仿真结果表明，所提出的算法可以实现方向相关的 MC 自校准，并且优于现有的算法。
