提出了一种估计均匀圆阵互耦系数的算法。
A new mutual coupling calibration algorithm is presented to estimate the mutual coupling (coefficients) of uniform circular array.
提出了极化敏感均匀圆阵中平行因子信号检测算法。
The blind parallel factor (PARAFAC) signal detection algorithm for the polarization sensitive array is proposed.
提出了一种利用一个辅助源估计均匀圆阵互耦系数的算法。
This paper presented a mutual coupling calibration algorithm that needs one assistant source for uniform circular array.
分析了极化敏感均匀圆阵接收到的信号，该信号具有三线性模型特征。
The received signal of the polarization sensitive array is proved to have trilinear model characteristics.
该方法只适用于均匀圆阵系统，因而针对性强，具有很好的应用前景。
This method is only suitable for UCA system and has large pertinence, so it has good application foreground.
这两种算法对阵列的形式没有限制，可以应用于水声系统中常见的均匀圆阵波束输出。
These two algorithms have no constraints on the array shape and they can easily be applied to beam outputs of uniform circular arrays which are often used in underwater systems.
基于互耦矩阵的特殊结构，给出了一种更具一般性的非均匀圆阵模型，提出了一种在未知互耦条件下的非均匀圆阵波达方向估计算法。
Based on the special structure of coupling matrix, a direction of arrival (DOA) estimation algorithm in the presence of unknown mutual coupling for the nonuniform circular array (NUCA) is presented.
基于互耦矩阵的特殊结构，给出了一种更具一般性的非均匀圆阵模型，提出了一种在未知互耦条件下的非均匀圆阵波达方向估计算法。
Based on the special structure of coupling matrix, a direction of arrival (DOA) estimation algorithm in the presence of unknown mutual coupling for the nonuniform circular array (NUCA) is presented.
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