文献类型：期刊文献

英文题名：An Unambiguous Doa Estimation Algorithm by a Large-Space Separated Nested Array for Reducing Mutual Coupling

作者：Liu, Sheng Zhao, Jing Wu, Decheng Zeng, Cheng Jiang, Qingping

第一作者：Liu, Sheng

机构：[1] School of Data Science, Tongren University, Tongren, 554300, China; [2] School of Automation, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China; [3] School of Science, Guizhou Institute of Technology, Guiyang, 550003, China; [4] College of Microelectronics and Communication Engineering, Chongqing University, Chongqing, 400044, China

第一机构：School of Data Science, Tongren University, Tongren, 554300, China

年份：2022

外文期刊名：SSRN

收录：EI(收录号：20220411346)

语种：英文

摘要：In this paper, a large-space separated nested array construction is introduced, by which an unambiguous direction of arrival (DOA) estimation algorithm is proposed. The proposed array consists of two large-space nested arrays, and the minimum element-spacing is larger than half-wavelength of the incident signal. By using the signal parameter via rotational invariance techniques (ESPRIT), an ambiguous angle matrix can be got. This ambiguous angle matrix is used to obtain an unambiguous angle matrix by which an extended signal subspace is constructed. Then high-precision and unambiguous DOA estimation can be got by virtue of the extended signal subspace. The proposed array shows strong robustness to mutual coupling because of the modified array construction. The proposed method has higher accuracy than the ESPRIT algorithms based on many existing sparse arrays and can distinguish more signals than some other large-space arrays, which can be proved in complexity analysis and simulation results. ? 2022, The Authors. All rights reserved.