College of Information Science and Engineering, Shandong Agricultural University, Tai'an 271018, China.
Information School, Shandong University of Political Science and Law, Jinan 250014, China.
Sensors (Basel). 2018 May 27;18(6):1725. doi: 10.3390/s18061725.
In this paper, we investigate the problem of two-dimensional (2D) direction-of-arrival (DOA) estimation for generalized co-prime planar arrays. The classic multiple signal classification (MUSIC)-based methods can provide a superior estimation performance, but suffer from a tremendous computational burden caused by the 2D spectral search. To this end, we reduce the 2D problem into a one-dimensional (1D) one and propose a reduced dimension partial spectral search estimation method, which can compress the search region into a small 1D sector. Moreover, the proposed method can utilize the full information of the entire array without degrees-of-freedom loss. Furthermore, an iterative approach is also proposed to reduce complexity and improve performance. Simulation results show that the proposed methods can provide improved performance with substantially reduced complexity, as compared to other state-of-the-art methods.
在本文中，我们研究了广义互质平面阵列的二维（2D）到达角（DOA）估计问题。基于经典的多重信号分类（MUSIC）的方法可以提供优越的估计性能，但由于二维谱搜索而遭受巨大的计算负担。为此，我们将 2D 问题简化为一维（1D）问题，并提出了一种降维部分谱搜索估计方法，该方法可以将搜索区域压缩到一个小的 1D 扇区。此外，所提出的方法可以利用整个阵列的全部信息，而不会有自由度损失。此外，还提出了一种迭代方法来降低复杂度并提高性能。仿真结果表明，与其他最先进的方法相比，所提出的方法可以在大大降低复杂度的同时提供改进的性能。
