Computationally efficient direction-of-arrival estimation of non-circular signal based on subspace rotation technique

Wei WANG; Ming ZHANG; Bobin YAO; Qinye YIN; Pengcheng MU

doi:10.11959/j.issn.1000-436x.2020208

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Computationally efficient direction-of-arrival estimation of non-circular signal based on subspace rotation technique

Correspondences | 更新时间：2024-06-05

- Computationally efficient direction-of-arrival estimation of non-circular signal based on subspace rotation technique
- Journal on Communications Vol. 41, Issue 11, Pages: 198-205(2020)
- 作者机构：
  
  1. 西京学院信息工程学院，陕西西安 710123
  2. 西安交通大学智能网络与网络安全教育部重点实验室，陕西西安 710049
  3. 西安微电子技术研究所，陕西西安710000
  4. 长安大学电子与控制工程学院，陕西西安 710064
- 作者简介：
- 基金信息：
  
  The Natural Science Special Foundation of Shaanxi Provincial Department of Education(20JK0966);The National Natural Science Foundation of China(61702424);The National Natural Science Foundation of China(61601058)
- DOI：10.11959/j.issn.1000-436x.2020208
  CLC： TN959.2
- Online First：2020-11，
  
  Published：25 November 2020
- 稿件说明：
移动端阅览
Wei WANG, Ming ZHANG, Bobin YAO, et al. Computationally efficient direction-of-arrival estimation of non-circular signal based on subspace rotation technique[J]. Journal on Communications, 2020, 41(11): 198-205.
DOI：

Wei WANG, Ming ZHANG, Bobin YAO, et al. Computationally efficient direction-of-arrival estimation of non-circular signal based on subspace rotation technique[J]. Journal on Communications, 2020, 41(11): 198-205. DOI： 10.11959/j.issn.1000-436x.2020208.

摘要

针对波达方向（DOA）估计中非圆信号多重信号分类（NC-MUSIC）算法运算复杂度过高的问题，提出了一种结合子空间旋转的非圆信号快速 DOA 估计算法。所提算法首先利用对噪声子空间矩阵分块和子空间旋转技术（SRT）构造降维噪声子空间；然后根据降维噪声子空间与扩展后阵列流型矩阵张成空间的正交性和变量分离，将 NC-MUSIC 算法中的二维谱峰搜索转化为一维谱峰搜索。所提算法通过二维谱峰搜索到一维谱峰搜索的转化和去除一维谱峰搜索中冗余计算的方式提高了算法的计算效率。理论分析和仿真结果表明，与 NC-MUSIC算法相比，所提算法可在保证DOA估计精度的前提下将算法运算复杂度降至NC-MUSIC算法运算复杂度的5%以下；尤其对于阵元数目较多的场景，所提算法的计算效率优势更明显。

Abstract

In order to solve the problem that the high computational burden of the multiple signal classification algorithm of non-circular signal (NC-MUSIC) in direction-of-arrival (DOA) estimation

a novel computationally efficient DOA estimation algorithm based on subspace rotation technique was proposed.Firstly

the partitioning of noise subspace matrix and the subspace rotation technique (SRT) were used to construct a new reduced-dimension noise subspace.Then

the two-dimensional peak searching was converted to the one-dimensional peak searching on the basis of the separation of variables and the orthogonality between the new reduced-dimension noise subspace and the space spanned by the columns of the extended manifold matrix.The proposed algorithm can enhance the computational efficiency by means of the conversion of the two-dimensional peak searching into the one-dimensional peak searching and the removal of redundant computations.Theoretical analysis and simulation results show that the proposed algorithm can reduce the computational complexity to less than 5% as compared to NC-MUSIC algorithm on the premise of ensuring the accuracy of DOA estimation.Especially

the efficiency advantage of the proposed algorithm is more obvious in scenarios where the large numbers of sensors are required.

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references

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