系统工程与电子技术 ›› 2026, Vol. 48 ›› Issue (1): 342-349.doi: 10.12305/j.issn.1001-506X.2026.01.30

• 通信与网络 • 上一篇    下一篇

非均匀噪声下近场太赫兹大规模MIMO目标定位

孙梦瑶1,*(), 王超轶1, 李赛2, 林云航1   

  1. 1. 南京航空航天大学电子信息工程学院,江苏 南京 211106
    2. 杭州电子科技大学空间信息研究院,浙江 杭州 310018
  • 收稿日期:2024-08-30 出版日期:2026-01-25 发布日期:2026-02-11
  • 通讯作者: 孙梦瑶 E-mail:sunmengyao@nuaa.edu.cn
  • 作者简介:王超轶(2000—),女,硕士研究生,主要研究方向为通信信号处理
    李 赛(1993—),男,博士后,主要研究方向为无人机通信、多址接入
    林云航(1996—),男,博士研究生,主要研究方向为无人机信道估计、定位
  • 基金资助:
    浙江省重点研发项目基金(2023C01003)资助课题

Target localization in non-uniform noise for near-field terahertz massive MIMO

Mengyao SUN1,*(), Chaoyi WANG1, Sai LI2, Yunhang LIN1   

  1. 1. College of Electronic and Information Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China
    2. Space Information Research Institute,Hangzhou Dianzi University,Hangzhou 310018,China
  • Received:2024-08-30 Online:2026-01-25 Published:2026-02-11
  • Contact: Mengyao SUN E-mail:sunmengyao@nuaa.edu.cn

摘要:

针对非均匀噪声环境下太赫兹信号在近场区域的定位性能下降问题,基于子阵列结构的混合波束成形太赫兹大规模多输入多输出系统架构,提出一种基于接收信号数据协方差矩阵重构的定位算法。首先,通过增加时隙从少数射频链中获得全阵列信息;其次,分解全阵列信息的数据协方差矩阵,得到一个包含噪声功率的对角矩阵;然后,选取对角元素中的最小值来替换其余对角元素,得到重构后的数据协方差矩阵;最后,结合子空间算法得到信源参数。此外,还推导了克拉美罗下界验证所提算法的性能。理论分析和仿真结果表明,相比于现有算法,所提算法能以较低的计算复杂度实现对非均匀噪声干扰的有效抑制,提高了定位精度,并且验证了可以通过增加时隙减小硬件成本。

关键词: 太赫兹, 近场, 非均匀噪声, 定位

Abstract:

To address the issue of degraded positioning performance in non-uniform noise environments for terahertz signals in the near-field region, a localization algorithm based on the reconstruction of the received signal data covariance matrix is proposed, utilizing a array-of-subarrays structured hybrid beamforming architecture for a terahertz massive multiple input multiple output system. Firstly, by increasing the number of time slots, full-array information is obtained from a limited number of radio frequency chains. Secondly, the data covariance matrix of the full-array information is decomposed to obtain a diagonal matrix containing the noise power. Then, the minimum value among the diagonal elements is selected and used to replace the remaining diagonal elements, resulting in a reconstructed data covariance matrix. Finally, the source parameters are estimated using a subspace algorithm. In addition, the Cramer-Rao lower bound is derived to validate the performance of the proposed algorithm. Theoretical analysis and simulation results demonstrate that, compared to existing algorithms, the proposed algorithm can achieve effective suppression of non-uniform noise interference with lower computational complexity, improving the localization accuracy. It also validates that hardware costs can be reduced by increasing the number of time slots.

Key words: terahertz, near-field, non-uniform noise, localization

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