改进的阵列幅相差和阵元位置误差自校正算法

基于信号子空间拟合算法的代价函数,提出了一种改进的阵列幅相差和阵元位置误差自校正算法,该算法采用分步迭代的方式,可在阵列存在幅相差和阵元位置误差的情况下,估计出信源的波达方向(DOA)、阵列幅相差和阵元位置误差.文中还给出了参数估计惟一性的必要条件.计算机仿真结果验证了该算法的有效性.     

基于均匀十字阵的幅相误差自校正算法

针对实际应用中普遍存在的幅相误差扰动问题,结合子空间类波达方向估计算法,基于均匀十字阵列,提出了一种幅相误差的自校正算法。均匀十字阵列可分解为两个相互垂直的均匀线性阵列,利用均匀线阵接收数据协方差矩阵的结构特点对幅相误差进行初步估计,计算出波达方向的初始估计值,通过迭代方法得到更精确的估计值,自校正方法不需要任何参数初始值,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信源的波达方向角和阵元的幅相误差值。     

基于辅助阵元的二维波达方向估计算法

;针对任意平面阵列,提出了一种基于辅助阵元的二维波这方向估计算法.首先利用附加的一个辅助阵元及信号的空、时域信息,构造时空旋转矩阵实现对仰角的分离估计,再利用得到的仰角信息通过一维搜索获取方位角.与传统基于子空间的二维波达方向估计算法相比,该方法不需要进行二维谱峰搜索与参数配对,对阵元的幅相误差具有较强的鲁棒性,并具有...     

基于辅助阵元的阵元位置误差和信源方位联合估计算法

鉴于阵元位置误差会严重影响MUSIC算法的测向性能,基于W-F方法的思想给出了一种基于辅助阵元的阵元位王误差和信源方位联合估计算法.该算法可看作是W-F方法的一种变形,因为它仍以交替迭代的方式给出,其目标函数建立在信号子空间性质的基础上,并且可推广应用于任意阵列流型.同时本文推导了各个参数估计的克拉美罗下界(CRLB),仿真结果验证了本文算法的有效性.     

L型阵列通道不一致及阵元位置误差的联合校正方法

针对L型阵列中通道不一致和阵元位置误差同时存在的情况,利用辅助阵列和校正源,提出一种L型阵列通道不一致和阵元位置误差的解耦合估计方法.该方法计算量小,不需要误差参数的任何先验知识,且校正源的位置可以未知.理论分析和仿真结果表明,提出的方法能很好地解决L型阵列中通道不一致和阵元位置误差的联合校正问题,且两种误差的估计精度高.     

矢量天线阵元方向不一致的误差校正

基于特征值分解的子空间类算法对误差非常敏感,有必要对方向误差进行有效的校正.分析了方向误差形成的原因,建立了误差阵元的数据模型,研究同一入射信号玻印廷(Poynting)矢量与阵元排列方向的关系,使用3个参量未知的校正源,通过比较校正源玻印廷矢量在参考阵元与误差阵元处的响应,获得阵列采样数据方向误差校正矩阵.比较玻印延矢量的误差校正方法不涉及参量搜索,计算量小且易于在工程上实现,计算机仿真验证了算法的正确性和有效性.     

一种经典阵元幅相误差、阵元间互耦自校正方法的仿真分析

阵元幅相误差以及阵元间互耦的存在会使大多数高分辨DOA估计算法的性能恶化或失效。因此,阵列误差的校正技术在实际工程应用中具有重要的意义。本文基于一种经典自校正算法进行仿真分析,针对较多文章在理论上分析说明此方法对于均匀线阵的局限性,本文主要考查在实际应用中,在一定条件下此方法同样适用于均匀线阵。     

阵列信号幅相一致性校正及FPGA实现

文章针对阵列信号处理中的由于阵元接收机和阵元位置扰动造成幅相不一致问题提出了一种基于比较法的解决方案,并利用FPGA加以实现.通过计算的位扩展保证校正精度,同时兼顾处理的实时性,同时将位置扰动带来的相位误差归一化到单阵元进行相位校正.并且利用了LVDS端口提高传输速率,提高了可实现性,通过仿真和试验证明了其可行性.     

GNSS干扰测向中的自适应阵元标校算法研究

在卫星导航系统优化设计的研究中,由于存在空间干扰,信息源方向测试误差较大。针对阵列通道之间存在幅相误差,导致子空间类高分辨测向算法测向性能下降的问题,提出一种快速自校正算法应用到GNSS接收机阵列通道幅相误差校正中。算法无需知道干扰方向,在准确估计出干扰个数的基础之上,采用分步迭代的方式,估计出存在幅相误差情况下的干扰波达方向,能够实现对多个干扰的同时校正。仿真结果表明,改进算法能够有效提高MUSIC算法的稳健性,提高对多干扰的分辨能力和估计精度,在GNSS接收机阵元标校中有良好的应用前景。     

基于稀疏分解的阵列幅相误差自校正

针对现实条件下普遍存在的阵元通道幅相误差对波达方向DOA(Directions of Arrival)估计的影响,提出一种新的阵列误差自校正方法.该方法对接收信号进行稀疏分解,结合遗传算法寻优,可以精确估得信号源的波达方向,同时估计出各阵元的幅相误差值.该方法适用于任意阵列形式,在小于0 dB信噪比的情况下也能保持较好的估计准确性.计算机仿真验证了方法的有效性.     

Array errors active calibration algorithm based on instrumental sensors

The array mutual coupling,gain-phase errors and sensor position errors would significantly degrade the performance of high-resolution direction of arrival (DOA) estimation algorithms.Aiming at the combined influences of the above three array errors,a kind of active calibration algorithm is presented with the help of instrumental sensors in this paper.Firstly,the integrated effects of the three array errors are shown to be equivalent to angularly dependent gain-phase errors.Then,a non-linear least square (LS...     

A sparse direction-of-arrival estimation algorithm for MIMO radar in the presence of gain-phase errors

In this paper, the problem of direction-of-arrival (DOA) estimation for monostatic multiple-input multiple-output (MIMO) radar with gain-phase errors is addressed, by using a sparse DOA estimation algorithm with fourth-order cumulants (FOC) based error matrix estimation. Useful cumulants are designed and extracted to estimate the gain and the phase errors in the transmit array and the receive array, thus a reliable error matrix is obtained. Then the proposed algorithm reduces the gain-phase error matrix to a low dimensional one. Finally, with the updated gain-phase error matrix, the FOC-based reweighted sparse representation framework is introduced to achieve accurate DOA estimation. Thanks to the fourth-order cumulants based gain-phase error matrix estimation, and the reweighted sparse representation framework, the proposed algorithm performs well for both white and colored Gaussian noises, and provides higher angular resolution and better angle estimation performance than reduced-dimension MUSIC (RD-MUSIC), adaptive sparse representation (adaptive-SR) and ESPRIT-based algorithms. Simulation results verify the effectiveness and advantages of the proposed method.     

Joint direction of arrival estimation and array calibration for coprime MIMO radar

Compared to large-scale MIMO radar, coprime MIMO radar can achieve approximate estimation performance with reduced antenna number. In this paper, joint direction of arrival (DOA) estimation and array calibration for coprime multiple-input multiple-output (MIMO) radar is considered, and an iterative method for the estimations of DOA and array gain-phase errors is proposed. Based on the received data structure of coprime MIMO radar, trilinear decomposition is firstly adopted to obtain the estimations of transmit and receive direction matrices, which are perturbated by the gain-phase errors. Through equation transformation, the un-perturbated direction matrices and gain-phase errors can be iteratively updated based on Least squares (LS). Finally, the unique DOA estimation is determined from the intersection of transmit and receive direction matrices. The proposed algorithm achieves better DOA estimation and array calibration performance than other methods including estimation of signal parameters via rotational invariance techniques (ESPRIT)-like algorithm, multiple signal classification (MUSIC)-like algorithm and joint angle and array gain-phase error estimation (JAAGE) method, and it performs close to the method with ideal arrays. Multiple simulation results verify the algorithmic effectiveness of the proposed method.     

Array errors active calibration algorithm and its improvement

The combined effects of mutual coupling, gain and phase errors, and sensor position errors have great negative impact on the direction-finding performance of the MUSIC algorithm. This paper investigates the calibration of the array errors induced by the three errors. Based on the array errors calibration algorithm (algorithm 1) presented by See, two improved array error-calibrating algorithms are presented. One (algorithm 2) uses the sparseness of mutual coupling matrix, and the other (algorithm 3) utilizes...     

Array calibration of angularly dependent gain and phase uncertainties with carry-on instrumental sensors

Array calibration with angularly dependent gain and phase uncertainties has long been a difficult problem. Although many array calibration methods have been reported extensively in the literature, they almost all assumed an angularly independent model for array uncertainties. Few calibration methods have been developed for the angularly dependent array uncertainties. A novel and efficient auto-calibration method for angularly dependent gain and phase uncertainties is proposed in this paper, which is called ISM (Instrumental Sensors Method). With the help of a few well-calibrated instrumental sensors, the ISM is able to achieve favorable and unambiguous direction-of-arrivals (DOAs) estimate and the corresponding angularly dependent gain and phase estimate simultaneously, even in the case of multiple non-disjoint sources. Since the mutual coupling and sensor position errors can all be described as angularly dependent gain/phase uncertainties, the ISM proposed still works in the presence of a combination of     

基于任务的故障检测机制的研究

磁盘阵列故障检测机制是保证磁盘阵列可靠性的核心技术;为了能够及时检测系统故障,提出一种基于任务的故障检测机制;该机制根据磁盘阵列任务特征,将任务分为三类,并描述任务间的依赖关系;当故障发生时,该机制能够及时主动地检测出错任务,并根据任务间依赖关系划分恢复组,将故障影响控制在恢复组内;计算机仿真结果显示,采用该故障检测机制的故障处理系统不仅故障检出率高,而且对磁盘阵列控制器系统读写速率影响小,能够显著地提高磁盘阵列系统可靠性。     

均匀线阵中幅相及位置误差的快速校正方法

着重研究了针对均匀线阵中由各阵元幅度相位不一致性及位置误差的综合影响引起的阵列流形误差的校正问题。该方法利用单信号源(可以为事先设置的校正源或某目标源)，无须准确知道信号源的波迭方向，只须在校正过程中将阵列天线以已知角度旋转两次．即可对各阵元的幅度、相位及位置因子作较精确的估计，从而估计出综合误差存在情况下的阵列流形，并可同时估计信号源的波达方向。该方法无需迭代．计算简单快速．且具有较高的估计精度。计算机模拟实验结果表明了本文方法的有效性。     

Robustness analysis of nearfield subband beamformers in the presence of microphone gain and phase errors

Subband beamforming has found many applications in microphone array processing field, due to its advantages over the fullband counterpart. In this paper, the performance of nearfield subband beamformers for arbitrary arrays in the presence of microphone gain and phase errors is studied from the perspective of statistical analysis. Through the bias and variance analysis of array response, some insightful properties on the robustness of nearfield subband beamformers have been derived. It is shown that the robustness of nearfield subband beamformers is dependent on the source-to-array distance, i.e., the robustness will deteriorate when the source is close to microphone arrays. Moreover, the variation in sound speed, i.e., the temperature in homogeneous environments, has little effect on the robustness performance of subband beamformers. The theoretical results are further verified by several numerical examples on nearfield subband beamformers.