多载频MIMO雷达的幅相误差校正  

Gain and phase error calibration for multi-carrier-frequency MIMO radar

作　　者：杨明磊[1] 张守宏[1] 陈伯孝[1] 朱守平[1] 

机构地区：[1]西安电子科技大学雷达信号处理国家重点实验室,陕西西安710071

出　　处：《系统工程与电子技术》2010年第2期279-283,307,共6页Systems Engineering and Electronics

基　　金：教育部新世纪优秀人才支持计划(NCET-06-0856);国家部委基金(51307050102)资助课题

摘　　要：建立了多载频(multi-carrier-frequency,MCF)MIMO雷达的幅相误差模型,并针对其发射和接收阵列的幅相误差耦合到一起的特点,提出了对信号预处理后等效阵列的联合幅相误差进行整体估计来实现误差校正的思想。针对单辅助信源的情况完成了两种误差估计方法:子空间拟合(subspace fitting,SF)法和最大似然(maximum likelihood,ML)法,子空间拟合法利用信号子空间与阵列流型张成空间的对应系列方程求解,而最大似然法利用似然函数最大来得到幅相误差。推导了幅相误差估计的Cramer-Rao界(CRB),并仿真分析了两种方法的估计性能与信噪比、快拍数的关系以及辅助信源的定位误差对估计性能的影响。A gain and phase error model of the multi-carrier-frequency（MCF） MIMO radar is constructed and a method to calibrate the array error by estimating the combined gain and phase error of the equivalent array after the signal preprocessing is proposed based on the coupling characteristics of gain and phase error of the transmit and receive array.Two estimation methods,subspace fitting（SF） method and maximum likelihood（ML） method,are proposed to estimate the gain and phase error when there is a single auxiliary source at a certain position.The SF method estimates the error by the corresponding equation of the signal subspace and the subspace expanded by array manifold while the ML method obtains it by maximizing the likelihood function.The Cramer-Rao bound（CRB） of gain and phase error estimation is derived,and the relationship between the estimation performance of these two methods and both signal to noise ratio（SNR） and snap number as well as the influence of the angle error of assistant source on the estimation performance are studied and simulated.

关 键 词：多载频多输入多输出雷达 幅相误差校正 子空间拟合法 最大似然法 CRAMER-RAO界 

分 类 号：TN958.5[电子电信—信号与信息处理]