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[1]阮新志,吴云韬*,黄龙庭.一种基于子空间方法的近场目标定位算法[J].武汉工程大学学报,2021,43(03):313-317.[doi:10.19843/j.cnki.CN42-1779/TQ.202010030]
 RUAN Xinzhi,WU Yuntao*,HUANG Longting.Near-Field Target Localization Algorithm Based on Subspace Method[J].Journal of Wuhan Institute of Technology,2021,43(03):313-317.[doi:10.19843/j.cnki.CN42-1779/TQ.202010030]
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一种基于子空间方法的近场目标定位算法(/HTML)
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《武汉工程大学学报》[ISSN:1674-2869/CN:42-1779/TQ]

卷:
43
期数:
2021年03期
页码:
313-317
栏目:
机电与信息工程
出版日期:
2021-06-30

文章信息/Info

Title:
Near-Field Target Localization Algorithm Based on Subspace Method
文章编号:
1674 - 2869(2021)03 - 0313 - 05
作者:
阮新志12吴云韬*12黄龙庭3
1. 智能机器人湖北重点实验室(武汉工程大学),湖北 武汉 430205;2. 武汉工程大学计算机科学与工程学院,湖北 武汉 430205;3. 武汉理工大学信息工程学院,湖北 武汉 430070
Author(s):
RUAN Xinzhi12 WU Yuntao*12 HUANG Longting3
1. Hubei Key Laboratory of Intelligent Robot (Wuhan Institute of Technology), Wuhan 430205, China;2. School of Computer Science & Engineering,Wuhan Institute of Technology, Wuhan 430205, China;3. School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China
关键词:
近场目标主奇异向量模态分析MUSIC角度估计距离估计 定位算法
Keywords:
near-field target principal singular vector utilization for modal analysis (PUMA) MUSIC angle estimation range estimationlocalization algorithm
分类号:
TN911.72
DOI:
10.19843/j.cnki.CN42-1779/TQ.202010030
文献标志码:
A
摘要:
针对近场目标参数估计中计算量大的问题,提出了一种结合主奇异向量模态分析(PUMA)技术以及一维多重信号分类(MUSIC)方法的近场目标定位算法。该算法首先利用PUMA技术估计近场目标角度参数,然后通过估计出的角度参数并结合一维MUSIC方法,估计出近场目标距离参数。通过计算机仿真实验表明,该方法能明显减少近场目标参数估计的计算量,并且具有较好的参数估计性能。
Abstract:
To reduce the computational overhead of near-field target parameter estimation, a near-field target localization algorithm based on the principal singular vector utilization for modal analysis (PUMA) and one-dimensional multiple signal classification method(MUSIC) was proposed. Firstly, the PUAM technique was used to estimate the angle parameters of near-field targets. Then, the one-dimensional MUSIC spectrum was constructed from the estimated angle parameters to estimate the range parameters of near-field targets. Simulation results show that the proposed method can significantly reduce the computational overhead of the near-field target parameter estimation. Above all, better performance can be achieved.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2020-10-28基金项目:国家自然科学基金(61771353)作者简介:阮新志,硕士研究生。E-mail:1582247719@qq.com*通讯作者:吴云韬,博士,教授。E-mail:ytwu@uit.edu.cn引文格式:阮新志,吴云韬,黄龙庭. 一种基于子空间方法的近场目标定位算法[J]. 武汉工程大学学报,2021,43(3):313-317.
更新日期/Last Update: 2021-06-28