论文标题
在极化敏感的单用户环境中，强大的2-D DOA估计
Robust 2-D DOA Estimation in a Polarization Sensitive Single User Environment
论文作者
论文摘要
除了常规参数（例如信噪比，阵列几何和大小，样本量）外，其他几个因素（例如，天线元素的比对，极化参数）会影响到达方向（DOA）估计算法的性能。当所有天线元件都相同对准时，极化参数不会影响转向向量，这是所有常规DOA算法的基本假设。不幸的是，在这种情况下，对于给定的DOA角度，存在一系列极化参数，这些偏振参数可能会导致阵列中所有天线元件的信噪比（SNR）非常低。为了避免这种类型的灾难性事件，需要以不同的方式对齐不同的天线元件。但是，由于转向向量被极化参数污染，因此这一事实将使几乎所有常用的DOA估计算法无法操作。据我们所知，文献中的工作也没有解决这个问题，即使对于单个用户环境。在本文中，进行了询问。我们考虑具有最小天线元件数量的圆形阵列，并提出了一种天线对准方案，以确保由于极化的贡献，在任何给定点，在任何给定点，不超过一个元素将遭受显着较低的SNR。开发了以封闭形式估算DOA角度的低复杂算法。我们将音乐视为基线算法，并演示了它如何在所有可能的DOA和极化环境中可靠地运行。最后，对上述两种算法进行了彻底的性能和复杂性分析。
Apart from the conventional parameters (such as signal-to-noise ratio, array geometry and size, sample size), several other factors (e.g. alignment of the antenna elements, polarization parameters) influence the performance of direction of arrival (DOA) estimating algorithms. When all the antenna elements are identically aligned, the polarization parameters do not affect the steering vectors, which is the underlying assumption of all the conventional DOA algorithms. Unfortunately, in this case, for a given set of DOA angles there exists a range of polarization parameters which could result in a very low signal-to-noise ratio (SNR) across all the antenna elements in the array. To avoid this type of catastrophic event, different antenna element needs to be aligned differently. However, this fact will make almost all commonly used DOA estimation algorithms non-operable, since the steering vectors are contaminated by the polarization parameters. To the best of our knowledge, no work in the literature addresses this issue even for a single user environment. In this paper, that line of inquiry is pursued. We consider a circular array with the minimum number of antenna elements and propose an antenna alignment scheme to ensure that at any given point no more than one element will suffer from significantly low SNR due to the contribution of polarization. A low complexity algorithm that estimates the DOA angles in a closed-form manner is developed. We treat MUSIC as the baseline algorithm and demonstrate how it can reliably operate in all possible DOA and polarization environments. Finally, a thorough performance and complexity analysis are illustrated for the above two algorithms.
