通信工程文献翻译——摘要

一种基于改进的Toeplitz矩阵重构的被称为第四阶累积量的有效解相干的方法（FOC-ITMR），目的是解决二维相干信号波达方向的估计。为了避免阵列的物理孔径的损失，FOC-ITMR算法充分利用了从所有双平行线性均匀矩阵接收到的信息和基于FOC的变化的参考元素。相比于之前的研究，FOC-ITMR算法在白噪声和有色噪声环境中可以提供出色的消噪性能。此外，该算法可以无需额外计算就实现自动配对。理论分析和仿真结果证实了该算法的有效性。

关键词：波达方向（DOA），二维（2D），相干源，第四阶累积量（FOC）

1.简介

波达方向（DOA）估计在雷达，无线通信和声纳等阵列信号处理应用的问题中是一个重要的研究方向。在不同的DOA估计方法中，对相干信号源的二维DOA估计引起了越来越多的关注。传统的高精度算法，例如MUSIC算法和ESPRIT算法，取得了令人满意的表现。不足的是，这些算法很容易受到噪声的影响并需要它的先验知识。此外，信号源的个数必须要少于传感器的数目。优秀之处是对于高阶累积量，如四阶累积量（FOC），已经被证明是一种很有行之有效的方法。由于噪声的协方差服从高斯分布，所以可以被忽视。此外，另外的一个关键因素是使用FOC可以解决超出传感器数组数目的信号源的问题。

在实际中，在多路径传播环境中，由于信号源的反射和折射，高度相关或相干信号无处不在。基于这样的情况,相干源的协方差矩阵的秩会损失，这可能导致传统高分辨率的算法的失败。为了实现信号解相关,，空间平滑和前后向空间平滑要特别注意相干信号源的位置。陈老师等人已经提出了一种二维的ESPRIT-like算法来实现。基于三个相关矩阵，王教授等人提出了二维的DOA估计算法。近些年来，聂教授等人引入了一个提高计算效率的子空间方法和L形阵列。在参考文献【24】中，提到了一种有效的稀疏的L型阵列的二维DOA估计算法，可以获得良好的估计性能和较少的计算复杂度。在文献【25】中，FOC-FSS算法已经被提出解决秩亏损问题。在文献【26】中，FOC-TMR算法提出通过两个Toeplitz矩阵的重构以获得了信号源的位置。

在这篇文章中，一种新的Toeplitz矩阵重构算法，被称为FOC-ITMR，提出了二维相干......

Abstract

An effective decoherence method called the fourth-order cumulants-based improved Toeplitz matrices reconstruction (FOC-ITMR) is addressed for two-dimensional (2-D) direction-of-arrival (DOA) estimation of coherent signals. To avoid the loss of the array’s physical aperture, the FOC-ITMR method fully utilizes the information of received data from the whole two parallel uniform linear arrays (ULAs) and the changing reference element based on FOC. Compared with previous works, the proposed method can offer excellent decoherence performance in both white noise and color noise environments. In addition, the proposed algorithm can achieve automatic pair-matching without additional computation. The theoretical analysis and simulation results confirm the effectiveness of the proposed algorithm. Keywords: Direction-of-arrival (DOA), Two-dimensional (2-D), Coherent sources, Fourth-order cumulants (FOC)

1 Introduction

Direction-of-arrival (DOA) estimation is a major research issue in array signal-processing applications such as radar,wireless communication, and sonar [1–5]. Among different DOA estimation methods, 2-D DOA estimation of coherent source signals [6–10] has drawn increasing attentions. Conventional high-precision methods, such as MUSIC [11] and ESPRIT [12], have achieved exciting performance. Unfortunately, these algorithms are easy to affect by noise as well as require its prior knowledge. Besides, the total number of incident signals must be less than that of the sensors [13]. Fortunately, the high-order cumulants, such as the fourth-order cumulants (FOC), have been shown to be a promising method since the noise covariance, which is Gaussian distributed, can be ignored [14–16]. Furthermore, another key motivation of using the FOC is the ability to resolve more number of......