基于差分阵列的双基地EMVS-MIMO雷达高分辨多维参数估计

潘小义; 谢前朋; 孟晓明; 陈吉源; 艾夏; 刘佳琪

doi:10.11999/JEIT221259

基于差分阵列的双基地EMVS-MIMO雷达高分辨多维参数估计

doi: 10.11999/JEIT221259

1.
国防科技大学电子信息系统复杂电磁环境效应国家重点实验室长沙 410073
2.
解放军 95913部队沈阳 110041
3.
陆军装备部驻南京地区军事代表局驻上海地区第二军事代表室上海 200031
4.
试验物理与计算数学国家重点实验室北京 100076

基金项目: 国家自然科学基金(61890545,61890542,61890540)，长沙市科技计划项目经费(Kq2209002)

详细信息

作者简介:
潘小义：男，副教授，主要研究方向为先进体制雷达对抗

谢前朋：男，工程师，主要研究方向为阵列信号处理、雷达信号处理

孟晓明：男，工程师，主要研究方向为雷达对抗工程

陈吉源：男，博士生，主要研究方向为雷达成像与对抗、阵列设计与处理

艾夏：男，高级工程师，主要研究方向为空天信息获取与处理

刘佳琪：男，研究员，主要研究方向为电子对抗、空天信息获取与处理

通讯作者:
谢前朋　13721038905@163.com

中图分类号: TN958
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出版历程
- 收稿日期: 2022-09-29
- 修回日期: 2023-02-01
- 网络出版日期: 2023-02-04
- 刊出日期: 2023-11-28

High Resolution Multidimensional Parameters Estimation for Bistatic EMVS-MIMO Radar: From the Difference Coarray Perspective

1.
State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, National University of Defense Technology, Changsha 410073, China
2.
95913 Troops of the Chinese People’s Liberation Army, Shenyang 110041, China
3.
Shanghai Second Military Representative Office, Nanjing Military Representative Office of the Ministry of Army Equipment, Shanghai 200031, China
4.
National Key Laboratory of Science and Technology on Test physics & Numerical Mathematics, Beijing 100076, China

Funds: The National Natural Science Foundation of China (61890545, 61890542, 61890540), Changsha Science and Technology Project Funding Program(Kq2209002)

摘要

摘要: 为提升双基地EMVS-MIMO雷达的多维参数估计性能，该文提出利用发射/接收EMVS的差分阵列结构来实现多维参数的高分辨估计。对于阵列接收数据，可以利用高阶张量来实现对发射/接收EMVS的差分阵列的构建。首先，利用高阶张量的交换和缩并规则来构建一个包含原始发射/接收EMVS差分阵列结构的5阶张量模型；通过利用两个选择矩阵，可以剔除该张量模型中差分阵列的重复元素，且获得的差分阵列的自由度为原始阵列自由度的两倍。然后，对新构建的5阶张量模型再次进行张量的缩并处理可以获得一个第3个维度为36的3阶张量模型。最后，通过利用平行因子分解算法可以实现对发射4维参数和接收4维参数进行有效的求解。仿真实验表明，该文对差分阵列的构建有效地实现了双基地EMVS-MIMO雷达中多维参数估计性能的提升。
- 双基地EMVS-MIMO雷达 /
- 高阶张量模型 /
- 差分阵列 /
- 多维参数估计 /
- 平行因子分解算法
Abstract: This paper employs the difference coarray structures of transmit/receive EMVS to enhance the multidimensional parameter estimation performance in bistatic EMVS-MIMO radar. The difference coarrays of transmit/receive EMVS are built through the high-order tensor operation for receiving data. First, a fifth-order tensor model with the difference coarray of the original transmits/receive EMVS can be obtained by applying the tensor permutation rule and generalized tensorization. Additionally, the repeated elements in the difference coarray can be removed by using two selection matrices, where the obtained degree of freedom of the difference coarray is twice that of the original array. Then, a third-order tensor model with the third way fixed at 36 can be developed by using the generalized tensorization again. Finally, the PARAFAC algorithm is adopted to effectively estimate the transmit/receive four-dimensional parameter. Simulation demonstrate that the difference coarray can efficiently enhance the multi-dimensional parameter estimation performance in bistatic EMVS-MIMO radar.
- Bistatic EMVS-MIMO Radar /
- Higher-order tensor model /
- Difference coarray /
- Multidimensional parameters estimation /
- PARAFAC algorithm

HTML全文

图 1 双基地 EMVS-MIMO 雷达系统

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图 2 不同算法的计算复杂度随快拍数的变化

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图 3 基于差分阵列的空间谱估计性能

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图 4 均方误差随信噪比的变化

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图 5 均方误差随快拍数的变化

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