基于PAST的毫米波雷达MIMO阵列幅相误差校正算法  

Amplitude and Phase Error Calibration Algorithm for a MIMO Array of Millimeter Wave Radar Based on PAST

作　　者：王纪平 刘衍琦 邓钱钰 郭淑婷 毛新华 WANG Jiping;LIU Yanqi;DENG Qianyu;GUO Shuting;MAO Xinhua(Key Laboratory of Radar Imaging and Microwave Photonics,Ministry of Education,College of Electronic and Information Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing,Jiangsu 211106,China)

机构地区：[1]南京航空航天大学电子信息工程学院雷达成像与微波光子技术教育部重点实验室,江苏南京211106

出　　处：《信号处理》2024年第9期1633-1647,共15页Journal of Signal Processing

基　　金：国家自然科学基金(62071225);江苏省自然科学基金(BK20211181);上海航天科技创新基金(SAST2022-066)。

摘　　要：随着毫米波雷达探测场景的复杂多元化,仅仅利用合成孔径雷达(Synthetic Aperture Radar,SAR)成像技术获得探测场景二维信息很难满足实际工程需要。因此,基于车载毫米波雷达二维SAR成像结果,利用高度向多输入多输出(Multiple Input Multiple Output,MIMO)阵列来进行到达角(Direction Of Arrival,DOA)估计,获得目标高度信息,实现高分辨率三维点云成像就显得十分重要。然而在实际MIMO阵列中存在的幅度和相位误差会导致DOA估计性能下降,影响目标聚焦效果,难以满足目标分类识别的要求。由于SAR成像后的阵列幅相误差具有时变性,现有的阵列幅相误差校正算法难以兼顾补偿精度和计算效率。针对上述问题,本文首先构建了车载毫米波雷达三维回波模型,提出了一种基于后向投影算法的高分辨三维重构成像方法。相较于传统的毫米波点云成像,该方法可以获得更高的方位向和高度向分辨率。然后,建立了高度向一维阵列信号模型,利用最大似然估计方法,推导了阵列幅相误差最大似然估计值与阵列协方差矩阵的最大特征值对应的特征向量之间的等效关系。最后,提出了一种基于投影近似子空间跟踪(Projection Approximation Subspace Tracking,PAST)的MIMO阵列幅相误差校正算法,该算法利用PAST技术迭代求解所需的特征向量,有效避免了复杂的估计协方差矩阵和特征分解过程。相较于已有算法,该算法拥有较高的估计精度的同时可以满足工程实时处理的需要。理论分析、数值仿真以及实测实验验证了该算法可以有效排除阵列幅相误差干扰,获得高分辨DOA估计结果。Benefiting from the widespread applications of synthetic aperture radar(SAR)imaging technology and multiple input multiple output(MIMO)arrays in millimeter wave radar,high-resolution three-dimensional point clouds im‐ages can be obtained using MIMO arrays for direction of arrival(DOA)estimation based on the two-dimensional SAR imaging results of automotive millimeter wave radar.However,in actual millimeter wave radar echo data,the ampli‐tude and phase errors between array elements may cause multiple inaccurate peaks in the angle spectrum,a decrease in the main lobe peak,and an increase in the side peaks,all of which can lead to a degradation in DOA estimation perfor‐mance.This affects the target focusing effect,and makes it difficult to meet the requirements of target classification and recognition.Due to the time variant of amplitude and phase errors after SAR imaging,correctly compensating amplitude and phase errors using existing amplitude and phase error calibration algorithms is difficult.Moreover,most current al‐gorithms require estimating the covariance matrix to seek amplitude and phase errors,which results in high complexity and cannot achieve the effect of engineering.Therefore,the amplitude and phase error calibration of the MIMO arrays will become a hot topic for automotive millimeter wave radars,which is of great importance for achieving real-time high-resolution imaging and assisting driving.This paper first describes the construction of a three-dimensional echo model of the automotive millimeter wave radar and proposes a high-resolution three-dimensional point clouds imaging method based on the back projection algorithm.Compared to the traditional point clouds imaging method,this method can achieve a higher azimuth and height resolution.To ensure DOA estimation performance,we demonstrate the equiva‐lence between the amplitude and phase error vectors of the array and the eigenvectors corresponding to the maximum ei‐genvalues of the covariance matrix by utilizing a one-dimensional array s

关 键 词：毫米波雷达 MIMO阵列 合成孔径雷达 幅相误差 投影近似子空间跟踪 

分 类 号：TN958.94[电子电信—信号与信息处理]