MUSIC algorithm is an effective method in solving the direction-finding problems. Due to the good performance of this algorithm, many variations of it including tesnor-MUSIC for verctor-sensor arrays, have been developed. However, these MUSIC-based methods have some limitations with respect to the number of sources, modeling errors and the noise power. It has been shown that using 2 q th-order $$(q>1)$$ ( q > 1 ) statistics in MUSIC algorithm is very effective to overcome these drawbacks. However, the existing 2 q -order MUSIC-like methods are appropriate for scalar-sensor arrays, which only measure one parameter, and have a matrix of measurements. In vector-sensor arrays, each sensor measures multiple parameters, and to keep this multidimensional structure, we should use a tensor of measurements. The contribution of this paper is to develop a new tensor-based 2 q -order MUSIC-like method for vector-sensor arrays. In this regard, we define a tensor of the cumulants which will be used in the proposed algorithm. The new method is called tensor-2 q -MUSIC. Computer simulations have been used to compare the performance of the proposed method with a higher-order extension of the conventional MUSIC method for the vector-sensor arrays which is called matrix-2 q -MUSIC. Moreover, we compare the performance of tensor-2 q -MUSIC method with the existing second-order methods for the vector-sensor arrays. The simulation results show the better performance of the proposed method.

中文翻译：

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使用高阶统计量估计矢量传感器阵列中的到达方向

MUSIC算法是解决测向问题的有效方法。由于该算法的良好性能，已经开发了它的许多变体，包括用于垂直传感器阵列的 tesnor-MUSIC。然而，这些基于 MUSIC 的方法在源数量、建模误差和噪声功率方面存在一些局限性。已经表明，在 MUSIC 算法中使用 2 q 阶 $$(q>1)$$ ( q > 1 ) 统计量可以非常有效地克服这些缺点。然而，现有的 2 q 阶 MUSIC 类方法适用于仅测量一个参数并具有测量矩阵的标量传感器阵列。在矢量传感器阵列中，每个传感器测量多个参数，为了保持这种多维结构，我们应该使用测量张量。本文的贡献是为矢量传感器阵列开发了一种新的基于张量的 2 q 阶类 MUSIC 方法。在这方面，我们定义了将在所提出的算法中使用的累积量的张量。新方法称为 tensor-2 q -MUSIC。计算机模拟已被用来比较所提出方法的性能与用于矢量传感器阵列的传统 MUSIC 方法的高阶扩展，称为矩阵 2 q -MUSIC。此外，我们将 tensor-2 q-MUSIC 方法与现有的矢量传感器阵列二阶方法的性能进行了比较。仿真结果表明所提出的方法具有更好的性能。新方法称为 tensor-2 q -MUSIC。计算机模拟已被用来比较所提出方法的性能与用于矢量传感器阵列的传统 MUSIC 方法的高阶扩展，称为矩阵 2 q -MUSIC。此外，我们将 tensor-2 q-MUSIC 方法与现有的矢量传感器阵列二阶方法的性能进行了比较。仿真结果表明所提出的方法具有更好的性能。新方法称为 tensor-2 q -MUSIC。计算机模拟已被用来比较所提出方法的性能与用于矢量传感器阵列的传统 MUSIC 方法的高阶扩展，称为矩阵 2 q -MUSIC。此外，我们将 tensor-2 q-MUSIC 方法与现有的矢量传感器阵列二阶方法的性能进行了比较。仿真结果表明所提出的方法具有更好的性能。