摘要
现有的波达方向(Direction of Arrival,DOA)估计方法大多依赖于阵列导向矩阵的精确无偏条件,而实际工程中由于时钟偏移、阵元位置偏差的存在导致该条件往往难以满足.为匹配阵列实际接收条件,本文基于部分校准嵌套阵列,提出了一种增益相位误差下的DOA估计新方法.该方法首先利用连乘子函数和简单的代数运算完成初始增益相位误差估计,然后通过协方差矩阵向量化和稀疏表示理论构建具有连续自由度的稀疏表示向量模型,最后考虑有效样本的影响,在初始增益相位误差估计的基础上应用稀疏总体最小均方(Sparse total least squares,STLS)算法完成波达方向估计.本文所提方法不仅对阵列增益相位误差不敏感,而且可依靠嵌套阵列高自由度特性和STLS算法的抗扰动特性获得改进的分辨率和估计精度,计算机仿真结果验证了所提算法的有效性.
Most of the current direction of arrival estimation(DOA) methods are proposed based on the unbiased knowledge of the array manifold,which may not be guaranteed in some practical applications,since the clock drifting and sensor position uncertainties always exist.To match the actual array reception condition,a DOA estimation method that uses partly calibrated nested array is presented.The proposed method completes the array gain-phase errors estimation by exploiting the continuous multiplication operator and simple algebraic operation,and then constructs a sparse vector model via vectorization operation on array covariance matrix in sparse representation framework,which owes consecutive degrees of freedom.Finally,the influence of the finite number of samples is considered,and the DOAs are successively estimated by applying sparse total squares(STLS) algorithm based on the estimated result of gain-phase errors.The proposed method not only performs independent of gain-phase errors,but also can provide improved resolution and estimation accuracy,by depending on the high DOFs provided by nested array and anti-disturbance characteristics of STLS algorithm.Simulation results validate the effectiveness of the proposed method.
作者
田野
史佳欣
王彦茹
TIAN Ye;SHI Jia-xin;WANG Yan-ru(School of Information Science and Engineering,Yanshan University,Qinhuangdao,Hebei 066004,China)
出处
《电子学报》
EI
CAS
CSCD
北大核心
2019年第12期2465-2471,共7页
Acta Electronica Sinica
基金
国家自然科学基金(No.61601398,No.61571388)
河北省自然科学基金(No.F2016203100)
关键词
DOA估计
增益相位误差
部分校准嵌套阵列
连乘子函数
STLS算法
direction of arrival(DOA) estimation
gain-phase errors
partly calibrated nested array
continuous multiplication operator
STLS algorithm