基于频域波束降维的车载雷达多参数联合超分辨方法

doi:10.12305/j.issn.1001-506X.2024.10.10

系统工程与电子技术 ›› 2024, Vol. 46 ›› Issue (10): 3325-3333.doi: 10.12305/j.issn.1001-506X.2024.10.10

• 传感器与信号处理 • 上一篇

基于频域波束降维的车载雷达多参数联合超分辨方法

刘润虎¹^,², 曹丙霞¹^,*, 李迎春¹, 闫锋刚¹, 金铭¹

1. 哈尔滨工业大学(威海)信息工程研究所, 山东威海 264209
2. 哈尔滨工业大学电子与信息工程学院, 黑龙江哈尔滨 150001

收稿日期:2023-06-16 出版日期:2024-09-25 发布日期:2024-10-22
通讯作者: 曹丙霞
作者简介:刘润虎 (1998—), 男, 博士研究生, 主要研究方向为阵列信号处理、毫米波雷达信号处理
曹丙霞 (1988—), 女, 副教授, 博士, 主要研究方向为阵列信号处理、雷达电子对抗
李迎春 (1987—), 男, 副教授, 博士, 主要研究方向为雷达系统、多源融合感知技术
闫锋刚 (1982—), 男, 教授, 博士, 主要研究方向为自适应信号处理、电子对抗
金铭 (1968—), 男, 教授, 博士, 主要研究方向为阵列信号处理、雷达系统设计
基金资助:
国家自然科学基金(61971158);国家自然科学基金(62171150);国家自然科学基金(62001143);泰山学者工程专项经费(TSQN202211087);山东省自然科学基金(ZR2023MF091)

Frequency-domain beam dimension reduction based multi-parameter joint super-resolution algorithm for vehicle radar

Runhu LIU¹^,², Bingxia CAO¹^,*, Yingchun LI¹, Fenggang YAN¹, Ming JIN¹

1. Institute of Information Engineering, Harbin Institute of Technology (Weihai), Weihai 264209, China
2. School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China

Received:2023-06-16 Online:2024-09-25 Published:2024-10-22
Contact: Bingxia CAO

摘要/Abstract

摘要：

针对车载雷达多参数联合超分辨计算复杂度高、无法快速实现参数估计的问题, 提出了基于频域波束降维的多参数联合超分辨算法。所提算法通过快速傅里叶变换(fast Fourier transform, FFT)将空时多参数域联合数据变换到频域, 处理感兴趣区域的多维频域数据, 完成空时波束空间降维和基于频域数据的多参数联合超分辨, 实现目标信息的快速联合估计。推导了频域子空间正交性及频域波束降维超分辨算法理论。仿真研究了算法的分辨率和估计性能与信噪比的关系。仿真结果表明, 所提算法的精度和分辨率远超传统FFT算法, 相对于传统多重信号分类(multiple signal classification, MUSIC)算法, 所提算法计算量大幅降低。

关键词: 频域, 波束空间, 联合超分辨, 多重信号分类

Abstract:

Aiming at the problem that the multi-parameter joint super-resolution of vehicle radar has high computational complexity and cannot achieve parameter estimation quickly, a multi-parameter joint super-resolution algorithm based on frequency-domain beam dimension reduction is proposed. The proposed algorithm transforms the joint data of space-time multi-parameter domain to frequency domain by fast Fourier transform (FFT), to process multi-dimensional frequency-domain data of the region of interest and complete the dimension reduction of the beam-space in space-time and the multi-parameter joint super-resolution based on the frequency-domain data, which achieve fast joint estimation of target information. The theory of frequency-domain subspace orthogonality and frequency-domain beam dimension reduction super-resolution is deduced. The relationship between the resolution, estimation performance of the algorithm and the signal to noise ratio (SNR) is investigated in simulation, and the simulation results show that compared with the traditional FFT, the accuracy and resolution of the proposed algorithm have been greatly improved, and the computational quantity is greatly reduced compared with that of the multiple signal classification (MUSIC) algorithm.

Key words: frequency domain, beam-space, joint super-resolution, multiple signal classification (MUSIC)

中图分类号:

刘润虎, 曹丙霞, 李迎春, 闫锋刚, 金铭. 基于频域波束降维的车载雷达多参数联合超分辨方法[J]. 系统工程与电子技术, 2024, 46(10): 3325-3333.

Runhu LIU, Bingxia CAO, Yingchun LI, Fenggang YAN, Ming JIN. Frequency-domain beam dimension reduction based multi-parameter joint super-resolution algorithm for vehicle radar[J]. Systems Engineering and Electronics, 2024, 46(10): 3325-3333.

图/表 10

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算法名称	计算复杂度
ACM	O((MNL)²)
EVD	O((MNL)³)
SPS	O((MNL)m_sn_sl_s)
总体	O((MNL)²+(MNL)³+(MNL)m_sn_sl_s)

算法名称	计算复杂度
ACM	O((M_bN_bL_b)²)
EVD	O((M_bN_bL_b)³)
SPS	O((M_bN_bL_b)mnl)
总体	O((M_bN_bL_b)²+(M_bN_bL_b)³+(M_bN_bL_b)mnl)

参数	数值
中心频率/GHz	24
带宽/MHz	150
一个Chirp周期/μs	16
快拍数	200
Chirp个数	2×128
发射/接收阵元数	2/15
扩展虚拟阵元数	30
目标1的距离、角度、速度参数	(150 m, 5°, 3.0 m/s)
目标2的距离、角度、速度参数	(150.5 m, 8°, 4.0 m/s)

算法	CPU运行时间
二维MUSIC	128.621 735
本文所提算法	1.007 684

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基于频域波束降维的车载雷达多参数联合超分辨方法

Frequency-domain beam dimension reduction based multi-parameter joint super-resolution algorithm for vehicle radar

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