张量框架下双基地FDA-MIMO雷达参数估计算法

国月皓; 王咸鹏; 兰翔; 苏婷

doi:10.12263/DZXB.20230172

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张量框架下双基地FDA-MIMO雷达参数估计算法

学术论文 | 更新时间：2025-12-11

- 张量框架下双基地FDA-MIMO雷达参数估计算法
- Parameter Estimation Algorithm for Bistatic FDA-MIMO Radar Based on Tensor Framework
- 电子学报 2024年52卷第6期页码：2103-2111
- 作者机构：
  
  1.海南大学信息与通信工程学院，海南海口 570228
  2.海南大学南海海洋资源利用国家重点实验室，海南海口 570228
- 作者简介：
  
  国月皓男，1996年1月出生，山东日照人.现为博士研究生.主要研究方向为阵列信号处理、MIMO雷达.
  王咸鹏男，1986年出生.主要研究方向为通信系统、阵列信号处理、雷达信号处理、压缩传感及其应用.中国电子学会会员编号：E190014644M. Email: wxpeng2016@hainanu.edu.cn
  兰翔男，博士、副教授.主要研究方向为基于矢量传感器阵列的信号处理（极化信号的波束形成和DOA估计）和稀疏阵列处理.
  苏婷女，博士、副教授.主要研究方向为计算电磁、无线通信和信号处理.
- 基金信息：
  
  海南省重大科技计划(ZDKJ2020010);国家自然科学基金(61961013;62101088;62101165);海南省自然科学基金(620RC555)
- DOI：10.12263/DZXB.20230172
  中图分类号： TN958;
- 收稿：2023-02-28，
  
  修回：2023-11-10，
  
  纸质出版：2024-06-25
- 稿件说明：
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国月皓,王咸鹏,兰翔,等.张量框架下双基地FDA-MIMO雷达参数估计算法[J].电子学报,2024,52(06):2103-2111.

GUO Yue-hao, WANG Xian-peng, LAN Xiang, et al.Parameter Estimation Algorithm for Bistatic FDA-MIMO Radar Based on Tensor Framework[J].Acta Electronica Sinica, 2024, 52(06): 2103-2111.
国月皓,王咸鹏,兰翔,等.张量框架下双基地FDA-MIMO雷达参数估计算法[J].电子学报,2024,52(06):2103-2111. DOI：10.12263/DZXB.20230172

GUO Yue-hao, WANG Xian-peng, LAN Xiang, et al.Parameter Estimation Algorithm for Bistatic FDA-MIMO Radar Based on Tensor Framework[J].Acta Electronica Sinica, 2024, 52(06): 2103-2111. DOI：10.12263/DZXB.20230172

摘要

频控阵（Frequency Diversity Array，FDA）雷达于2006年由Antonik和Wicks提出.由于FDA雷达每个相邻的天线之间存在一个频率偏移，因此在发射阵列存在距离角度二维依赖性.而对于双基地频控阵多输入多输出（FDA-Multiple Input Multiple Output，FDA-MIMO）雷达而言，在导向矢量中耦合了波离方向、到达方向、距离（Direction Of Departure-Direction Of Arrival-range，DOD-DOA-range）三个信息，如何对三者信息进行解耦便成为研究的重点.本文针对双基地FDA-MIMO雷达的目标参数估计问题，提出了一个张量框架下的降维多重信号分类（Reduced-Dimension MUltiple SIgnal Classification，RD-MUSIC）的参数估计算法.首先，为了将发射阵列中的DOD和距离信息进行解耦，需要对发射阵列进行子阵的划分.紧接着利用高阶奇异值分解（High-Order-Singular Value Decomposition，HOSVD）算法获得信号子空间，并构建二维空间谱函数.其次，通过拉格朗日算法对空间谱进行降维，使其仅与DOA有关，从而得到DOA估计.然后利用子阵之间的频率增量来对DOD和距离信息进行解耦，同时消除相位模糊，最终得到与DOA估计自动匹配的DOD和距离估计.所提算法利用高维数据的多维结构提高了估计精度，同时能够有效地降低运算复杂度.数值实验证明了所提算法性能的优越性.

Abstract

Frequency diversity array (FDA) radar was proposed by Antonik and Wicks in 2006. Since there is a frequency offset between each adjacent antenna of FDA radar

there exists two-dimensional dependence on range and angle in the transmitting array. For bistatic FDA-multiple input multiple output (MIMO) radar

direction of departure (DOD)- direction of arrival (DOA)-range information is coupled in the transmitting steering vector. How to decouple the three information has become the focus of research. In this paper

aiming at the problem of target parameter estimation of bistatic FDA-MIMO radar

a reduced-dimension multiple signal classification (RD-MUSIC) parameter estimation algorithm based on tensor framework is proposed. Firstly

in order to decouple the DOD and range information in the transmitting array

it is necessary to divide the transmitting array into subarrays. Then the signal subspace is obtained by high-order-singular value decomposition

and the two-dimensional spatial spectral function is constructed. Secondly

the dimension of spatial spectrum is reduced by Lagrange algorithm

so that it is only related to DOA

and the DOA estimation is obtained. Then the frequency increment between subarrays is used to decouple the DOD and range information

and eliminate the phase ambiguity at the same time. Finally

the DOD and range estimation automatically matched with DOA estimation are obtained. The proposed algorithm uses the multidimensional structure of high-dimensional data to improve the estimation accuracy. Meanwhile

the proposed RD-MUSIC algorithm can effectively reduce the computational complexity. Numerical experiments show the superiority of the proposed algorithm.

关键词

Keywords

references

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