基于L型阵列的幅相误差自校正算法研究

针对实际应用中普遍存在的阵列幅相误差扰动问题,结合子空间类波达方向估计算法,基于L型阵列,提出了一种幅相误差的自校正算法。先利用均匀阵列协方差矩阵的结构特点对幅相误差进行初步校正,再通过迭代方法得到更精确的估计值,自校正方法无需任何参数初始值,实现比较简单。仿真实验验证了算法具有良好的误差校正效果,能够比较准确地估计出波达方向角和幅相误差值。     

基于均匀圆阵的幅相误差自校正算法

针对实际应用中普遍存在的阵列幅相误差扰动问题,结合子空间类波达方向估计算法,以均匀圆阵为基础,提出了一种幅相误差的自校正算法。先利用均匀圆阵协方差矩阵的结构特点对幅相误差进行初步估计,再通过迭代方法得到更精确的估计值,自校正方法无需任何参数初始值,实现比较简单。仿真实验验证了算法具有良好的误差校正效果,能够比较准确的估计出波达方向角和幅相误差值。     

基于子空间的幅相误差自校正算法

针对实际应用中普遍存在的阵列幅相误差扰动问题,结合子空间类波达方向估计算法,提出了一种幅相误差的自校正算法。先利用均匀线阵协方差矩阵的结构特点对幅相误差进行初步校正,再通过迭代方法得到更精确的估计值,自校正方法无需任何参数初始值,实现比较简单。仿真实验验证了算法具有良好的误差校正效果,能够比较准确的估计出方位角和幅相误差值。     

一种利用互耦矩阵稀疏性的阵列误差有源校正改进算法

重点研究了波达方向估计中由阵元互耦、幅相误差以及阵元位置误差的综合影响引起的阵列误差校正问题,其主要方法是通过矩阵特征分解得到一组校正源的方向矢量来估计阵列误差.文中给出了一种改进的参数估计算法,该算法充分利用了互耦矩阵的稀疏性,并通过交替迭代的方法实现了阵列误差矩阵和阵元位置误差的优化校正.计算机仿真结果表明文中的改进算法提高了参数估计精度.     

阵列天线在近场条件下的幅相校正和阵元位置估计

在运动阵列存在幅相误差和阵元位置未知的条件下,提出了一种基于子空间方法的阵列幅相误差校正和阵元位置估计方法。该方法要求一个方位已知的近场校正源。计算机仿真结果表明,该校正方法可有效地估计出阵列参数。     

基于辅助阵元的近场源幅相误差校正算法

针对近场源的定位及阵列幅相误差校正问题,该文提出一种基于均匀对称阵列利用辅助阵元矢量重构解耦合的幅相误差校正方法。通过重构虚拟阵列实现距离参数的分离,再通过对虚拟阵列导向矢量的变换实现方位和幅相误差之间的解耦合;最后通过对实阵列导向矢量的变换,实现距离与幅相误差的解耦合,从而实现对近场源的方位角、距离以及阵列的幅相误差系数的级联估计。仿真结果表明所提算法相比现有算法运算量小,方位及距离参数估计精确,幅相误差校正精度高。     

阵列误差下的波达方向估计

由于阵列误差的存在会降低波达角的估计精度,重点研究了迭代求解混合范数约束下的稀疏谱以提高估计精度。考虑一维线性阵列,首先建立了统一的优化函数,高精度地估计信号子空间;然后推导了误差矩阵向量化的方法,简化求解耦合误差和幅相误差的过程;最后推导了Khatri-Rao积下的扩展正交导向矢量,根据优化函数迭代求解空间谱估计。对比不同方法估计参数的均方根误差表明,通过设计优化函数迭代求解阵列误差、波达角等参数的精度较之现有方法有一定的提高。     

导航系统的通道自均衡空时抗干扰技术

针对导航系统由于通道之间幅相特性的不一致导致抗干扰性能下降的问题,本文提出了一种通道自均衡的空时抗干扰技术。该方法首先在无干扰的情况下,利用本地参考信号与接收数据的相关特性求出实际导向矢量,再采用波达方向估计方法估计出信号的理想波达方向,进而求出理想导向矢量,并由此实际导向矢量和理想导向矢量求得幅相误差矩阵,然后在有干扰的情况下,利用求得的幅相误差矩阵对接收数据进行阵列误差校正,再对校正后的数据进行波束形成,此方法可以改善通道失配导致干扰抑制性能下降的问题,仿真验证了其有效性和优越性。     

阵列方向矩阵Moore-Penrose逆的波达方向估计

针对弱信号且源数未知情况下的波达方向估计问题,传统方法是先估计源数目再进行波达方向估计,但源数目估计的误差会造成波达方向估计精度下降。本文提出一种阵列方向矩阵的Moore-Penrose逆和MUSIC（MUltiple SIgnal Classification）算法的联合波达方向估计方法,充分利用Moore-Penrose逆的盲源数波达方向估计和MUSIC算法的高精度的优势。该方法无需预先估计源数目就可进行波达方向估计。通过仿真实验并与传统方法比较,表明本文提出的方法具有更高的精度,特别是在低信噪比情况下,具有更强的鲁棒性。      

未知阵列流形条件下波达方向一多普勒频率盲估计方法

本文研究阵列信号高分辨波达方向-多普勒频率二维估计问题,在未精确已知阵列流形条件下,利用到达波信号的多普勒频率,提出了一种波达方向-多普勒频率盲估计的新方法。理论分析和计算机仿真结果表明此方法在实际阵列存在增益和相位误差时亦有效,而且与现有二维估计算法相比,其运算量较小。     

增益相位误差下基于部分校准嵌套阵列的DOA估计

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.     

Joint Angle and Array Gain-Phase Errors Estimation Using PM-like Algorithm for Bistatic MIMO Radar

This paper discusses the problem of the direction of departure (DOD) and the direction of arrival (DOA) estimation for multi-input multi-output (MIMO) radar with array gain-phase errors. In this paper, we propose a propagator method (PM)-like algorithm for joint angle and array gain-phase errors estimation in MIMO radar. The proposed method not only yields automatically paired estimates of the angles and gain-phase errors but also has much better gain-phase errors estimation performance than the estimation of signal parameters via rotational invariance techniques (ESPRIT)-like algorithm; this has higher computational cost than the proposed algorithm. Furthermore, the proposed algorithm has angle estimation performance very close to ESPRIT-like algorithm. We also derive the Cramér–Rao bound (CRB) for MIMO radar with array gain-phase errors. Simulation results present the usefulness of our approach.     

Covariance matrix based fast smoothed sparse DOA estimation with partly calibrated array

To solve the problem of direction-of-arrival (DOA) estimation for partly calibrated array, a new gain-phase error matrix estimation scheme and a smoothed sparse signal reconstruction method tailored for the complex-valued covariance matrix are proposed. In the proposed method, DOA estimation is achieved by employing the structure of the covariance matrix for the error matrix estimation and the complex-valued gradient matrix based fast non-convexity data reconstruction. The proposed method has much faster computational speed than other sparse DOA estimation methods with partly calibrated array. In addition, simulation results show that it performs well and is independent of the errors.     

DOA estimation with double L-shaped array based on Hadamard product and joint diagonalization in the presence of sensor gain-phase errors

A method with double L-shaped array for direction-of-arrival (DOA) estimation in the presence of sensor gain-phase errors is presented. The reason for choosing double L-shaped array is that the shared elements between sub-arrays are the most and rotation invariant property can be applied for this array. The proposed method is introduced as follows. (1) If the number of signal is one, first the gain errors are estimated and removed with the diagonal of the covariance matrix of the array output. Then the array is rotated by an unknown angle and DOA can be estimated with the relationship between signal subspace and steering vector of signal. (2) If signals are more than one, the method for eliminating gain errors is the same with the previous case, and then the phase errors are removed by the Hadamard product of the (cross) covariance matrix and its conjugate. After the errors are eliminated, the DOAs can be estimated by rotation invariant property and orthogonal joint diagonalization for the Hadamard product. This method requires neither calibrated sources nor multidimensional parameter search, and its performance is independent of the phase errors. Simulation results demonstrate the effectiveness of the proposed method.

     

共形阵列幅相误差校正快速算法

基于子空间的联合迭代算法可以实现对空间信源方位和阵列幅相误差参数的联合估计。当对共形阵列进行幅相误差校正时,由于其空域导向矢量不具有Vander monde结构,导致快速高分辨空间谱估计方法无法直接应用,而利用2维谱峰搜索实现空间方位估计的运算量较大,限制了算法在共形阵列上的应用。针对此问题,该文提出一种借助虚拟阵列实现共形阵列幅相误差校正的新方法。该方法利用虚拟阵列的特殊结构快速实现对信源的DOA估计,省去了谱峰搜索过程,因而运算复杂度低,便于工程实现。理论分析和仿真结果验证了所提算法的有效性,可为共形阵列的工程应用提供参考。     

一种新的阵列误差有源校正算法

阵列互耦、幅相误差以及阵元位置误差的综合影响会严重影响阵列天线的测向性能．针对均匀圆阵,该文基于特征空间类方法给出了一种新的阵列误差有源校正算法．新算法是以交替迭代的方式给出,其目标函数建立在子空间基本原理的基础上,并且适用于多个校正源同时存在的情况．文中还给出了阵列误差参数估计唯一性的必要条件,仿真实验验证了新算法的有效性．     

一种阵列互耦矩阵与波达方向的级联估计方法

当阵列天线存在互耦效应时,传统多重信号分类(MUltiple SIgnal Classification, MUSIC)算法的测向性能急剧下降。为了有效估计阵列互耦矩阵(MCM)与入射信号的波达方向(Direction Of Arrival, DOA),该文提出一种阵列互耦矩阵与波达方向的级联估计方法。利用互耦矩阵的结构特点,变换阵列流形,实现对互耦矩阵与DOA的解耦合。求解线性约束下的二次优化问题,利用谱峰搜索,得到阵列互耦矩阵和入射信号DOA,完成互耦误差自校正。通过计算机仿真验证了该文方法估计性能的有效性和优越性。     

基于辅助阵元的方位依赖幅相误差最大似然自校正：针对确定信号模型

针对确定信号模型条件下方位依赖幅相误差的自校正问题,给出了一种基于辅助阵元的方位依赖幅相误差最大似然自校正方法;针对最大似然估计器中出现的高维非线性优化问题,推导了一种改进型交替投影迭代算法,从而实现了信号方位和方位依赖幅相误差的优化计算.此外,还推导了信号方位和方位依赖幅相误差的无偏克拉美罗界(CRB).仿真实验结果验证了新方法的有效性和优越性.     

Accurate DOA estimation using array antenna with arbitrary geometry

The so called universal steering vector (USV) whose locus is equivalent to the array element pattern is applied to the direction of arrival (DOA) estimation by multiple signal classification (MUSIC) algorithm. It is shown that if the USV which includes the effect of the mutual coupling between the array elements is used, the compensation for the received voltage to remove the effect of the mutual coupling is not required any more. The USV for array antennas with arbitrary geometry is derived and evaluated efficiently by using the method of moments (MoM) so that the DOA estimation can be performed accurately by using the array antenna with arbitrary geometry. Numerical examples of the DOA estimation by a dipole array antenna, and an antenna array composed of a monopole antenna and a planar inverted-F antenna (PIFA) mounted on a mobile handset are presented to demonstrate the effectiveness of the proposed method.     

Outage Probabilities of Wireless Systems With Imperfect Beamforming

This paper investigates the outage probability of a wireless system with conventional beamforming using a uniform linear array beamformer. The focus is to examine the impact of beamforming impairments, such as direction-of-arrival (DOA) estimation errors, signal spatial spreads, antenna array perturbation, and mutual coupling. Fading statistics of Rayleigh, Rician, and Nakagami are used to characterize the desired signal, whereas interferers are assumed to be subject to Rayleigh fading. A simplified beamforming model is used in deriving closed-form outage probability expressions. Numerical results illustrate the increase of outage probabilities in the presence of DOA estimation errors, signal spatial spreads, and antenna perturbation. However, negligible outage performance impact is observed due to mutual coupling.