An optimal robust adaptive beamforming in the presence of unknown mutual coupling

Multidimensional Systems and Signal Processing - An optimal robust adaptive beamformer in the presence of unknown mutual coupling is proposed. In this proposed beamformer, envelopes of the received...     

互耦效应对波束赋形天线的影响分析

波束赋形天线技术可以通过基带调零等手段降低干扰信号影响,提升系统抗干扰性能,通过数字信号处理还可以在空间上形成多个波束,从而形成空分多址,大幅度提升系统的容量。但是波束赋形天线技术要求天线间隔尽可能小,一般约为工作频率的半波长,而较小的天线间隔在实际工程实现时会引起严重互相耦合。由于对互耦效应进行有效的数学描述非常困难,一般通过计算量极大的专业天线仿真软件进行仿真验证,严重制约了互耦效应解决方案的提出和论证。文中针对上述问题,提出了互耦效应的数学模型,并利用MATLAB和ANSYS-HFSS工具对相关模型进行了交叉验证。不同平台的对比仿真结果显示了相关模型的正确性和有效性。     

考虑互耦的相控阵面天线波束形成

本文从实现相控阵面天线低副瓣性能的角度出发,针对在实际的相控阵天线设计中由于阵列天线单元间的互耦效应,用理想的电流分布作为激励往往达不到所期望的副瓣电平要求这一缺陷,首先用矩量法精确分析了考虑互耦影响时相控阵面天线阵元的电流分布,作出归一化电流幅度分布图,仿真实现了阵元互耦对相控阵面天线波束形成的影响效果,接下来用软件的方式补偿互耦所造成的影响,给出补偿的具体步骤,从而完成了相控阵天线波束形成的综合.     

考虑互耦的切比雪夫线阵天线波束形成

低副瓣是当今电子对抗时代中对雷达天线的必然要求,但由于阵列天线单元间有互耦的影响,实际的天线单元电流分布往往达不到我们设计的要求。本文在介绍切比雪夫线阵的设计公式和互耦的矩量法分析方法的基础上,首先用矩量法精确分析了考虑互耦影响时切比雪夫线阵天线阵元的电流分布,仿真实现了阵元互耦对切比雪夫线阵各阵元电流幅度及相位的影响效果以及互耦对切比雪夫线阵天线波束形成的影响效果,接下来用软件的方式补偿互耦所造成的影响,从而完成了切比雪夫线阵天线波束形成的综合。     

基于改进互耦系数估计算法的自适应波束形成

阵列信号在实际应用中,常常会面临噪声的干扰,低信噪比(signal noise ratio, SNR)时波束形成器性能会急剧下降.针对该问题,提出一种基于改进互耦系数估计的抗互耦算法的自适应波束形成,即研究信号在不同输入SNR以及不同干扰波达方向(direction of arrival,DOA)估计误差下的互耦系数估计误差;并通过误差分析修正原算法不同SNR下参与估计信号的数目.改进算法改进了导向矢量和期望信号,提高了低SNR下互耦系数估计的准确度,对比分析验证了其在低SNR情况下有更强的抗干扰能力,对互耦现象有着更好的稳健性.     

Reducing the mutual coupling effect in adaptive nulling using are-defined mutual impedance

The effect of mutual coupling in an adaptive antenna array for the nulling of interferences is investigated. The concept of mutual impedance is re-defined to take into account of the scattering effect due to the other antenna elements in the array. The re-defined mutual impedances are used to reduce the mutual coupling effect by calculating the open-circuit voltages from the measured voltages on the antenna terminals. Results show that by using the re-defined mutual impedances, substantial improvements in term of the depths and the accuracy of the nulls can be obtained over a previous method     

On uplink CDMA cell capacity: mutual coupling and scattering effects on beamforming

It has been shown that code-division multiple-access (CDMA) systems that employ digital beamforming and base station antenna arrays have the potential to increase capacity significantly. Therefore, accurate performance prediction of such systems is important. We propose to take the electromagnetic behavior of the base station antenna array into account, as well as its impact on wireless channel propagation. Specifically, the wideband channel introduces scattering, while the mobile environment causes Doppler fading, which in turn degrades power controllability. We develop a more accurate performance analysis of antenna arrays, where the performance degradation in digital beamforming, due to the combination of mutual coupling, scatter and imperfect power control, and its impact on uplink CDMA system capacity is quantified. A Rayleigh fading amplitude with varying angle-of-arrival spread is assumed, and maximum signal-to-noise ratio beamforming weights are used. These weights are further correlated with mutual coupling at the base station array. Despite the degradation due to the combination of mutual coupling, scattering, and imperfect power control, significant capacity increases are possible.     

Effect of mutual coupling on the performance of adaptive arrays

The effect of mutual coupling between array elements on the performance of adaptive arrays is examined. The study includes both steady state and transient performance. An expression for the steady state output signal-to-interference-plus-noise ratio (SINR) of adaptive arrays, taking into account the mutual coupling between the array elements, is derived. The expression is used to assess the steady state performance of adaptive arrays. The transient response is studied by computing the eigenvalues associated with the signal covariance matrix. The steering vector required to maximize the output SINR of Applebaum-type adaptive arrays in the presence of mutual coupling is also given.     

Source-oriented adaptive beamforming

A system concept expected to improve sonar multiple target detection and classification performance in severe directional interference environments is presented. Adaptive nulling of undesired strong interference sources and detection of desired weak sources are achieved by utilizing constrained adaptive processing techniquestogether with conventional processing techniques. The adaptive processing functions are incorporated in the overall system architecture in a manner which maintains the computational complexity and storage requirementslinearly proportional to the product of the number of interference sources and the number of adaptive weights per interference source. In addition, a detailed discussion is provided concerning the importance of certaina priori assumptions on constrained adaptive algorithm performance.This research was supported by NSERC Grant A0912 and Raytheon Company Independent Research and Development Programs.     

Knowledge-aided adaptive beamforming

In array processing, when the available snapshot number is comparable with or even smaller than the sensor number, the sample covariance matrix ^R is a poor estimate of the true covariance matrix R. To estimate R more accurately, prior environmental knowledge can be used, which is manifested as knowing an a priori covariance matrix R/sub 0/. In practice, R0 usually represents prior knowledge on dominant sources or interferences. Since the noise power level is unknown, and thus cannot be included into the a priori covariance matrix, R/sub 0/is often rank deficient. Both modified general linear combinations (MGLC) and modified convex combinations (MCC) of the a priori covariance matrix R/sub 0/, the sample covariance matrix ^R and an identity matrix I to obtain an enhanced estimate of R, denoted as ~R are considered. Both MGLC and MCC can choose the combination weights fully automatically. Moreover, both the MGLC and MCC methods can be extended to deal with linear combinations of an arbitrary number of positive semi-definite matrices. Both approaches can be formulated as convex optimisation problems that can be solved efficiently to obtain globally optimal solutions. Numerical examples are provided to demonstrate the type of achievable performance by using ~R instead of ^R in the standard Capon beamformer.     

Signal bandwidth consideration of mutual coupling effects on adaptive array performance

The effect of mutual coupling on the performance of a least mean square (LMS) adaptive array using dipole elements is analyzed in consideration of the signal bandwidth. The purpose here is to illustrate quantitatively the significance of the effect of mutual coupling. The results show that the effect in the broad-band signal cases is much greater than that in the narrow-band cases, particularly when few antenna elements are used.     

Super-exponential blind adaptive beamforming

The objective of the beamforming with the exploitation of a sensor array is to enhance the signals of the sources from desired directions, suppress the noises and the interfering signals from other directions, and/or simultaneously provide the localization of the associated sources. In this paper, we present a higher order cumulant-based beamforming algorithm, namely, the super-exponential blind adaptive beamforming algorithm, which is extended from the super-exponential algorithm (SEA) and the inverse filter criteria (IFC). While both SEA and IFC assume noise-free conditions, this requirement is no longer needed, and all the noise components are taken into account in the proposed algorithm. Two special conditions are derived under which the proposed blind beamforming algorithm achieves the performance of the corresponding optimal nonblind beamformer in the sense of minimum mean square error (MMSE). Simulation results show that the proposed algorithm is effective and robust to diverse initial weight vectors; its performance with the use of the fourth-order cumulants is close to that of the nonblind optimal MMSE beamformer.     

顽健自适应波束形成算法

针对方向向量偏差会导致最小均方(LMS)算法的性能急剧下降这一问题,提出了一种基于可变对角载入的顽健自适应波束形成算法.采用最陡下降法对信号方向向量进行优化求解,并在每次迭代过程中更新对角载入值,进而求出最优的权重向量,避免了矩阵求逆运算和特征值分解运算,大大降低了计算复杂度.通过建立步长与输入信号的关系得到可变的步长因子,克服了收敛速度和稳态误差之间的矛盾.该算法收敛速度快,抗扰动性强,对信号方向向量偏差具有很强的顽健性,从而改善了阵列输出的信干噪比,使其更接近最优值.理论分析和仿真结果表明与传统自适应波束形成算法相比,所提顽健算法具有更好的性能.     

Comparison of mutual coupling compensation to dummy columns in adaptive antenna systems

Compensation for mutual coupling in antenna arrays by matrix multiplication is compared to the use of dummy elements. A least squares estimation of the coupling matrix is made, including co- and cross-polar coupling. We show that compensation for measurements off the phase center is important as well as a proper assumption of the ideal element pattern. We study the performance of a dual polarized patch array with respect to far-field phase error, signal-to-interference reduction, and cross-polarization level. In all aspects, the performance of the compensation method exceeds or equals the use of dummy elements.     

Compensation for the effects of mutual coupling on direct datadomain adaptive algorithms

This paper investigates the effects of mutual coupling between the elements of an array on direct data domain algorithms. Mutual coupling severely undermines the interference suppression capabilities of direct data domain algorithms. The method of moments (MoM) is used to evaluate the mutual coupling between the elements of a given array. The MoM admittance matrix is then used to eliminate the effects of mutual coupling     

自适应波束形成算法的研究

自适应波束形成是智能天线的关键技术,其核心是通过一些自适应波束形成算法获得天线阵列的最佳权重,并最终最后调整主瓣专注于所需信号的到达方向,以及抑制干扰信号,通过这些方式,天线可以有效接收所需信号。在实际应用中,收敛性,复杂性和鲁棒性的速度是在选择自适应波束形成算法时要考虑的主要因素。本文聚焦于最小均方(LMS)算法和样本矩阵求逆(SMI)的算法,分析了它们的性能,并在Matlab的帮助下将这两个算法应用于自适应波束形成。     

The mutual coupling and diffraction effects on the performance of aCMA adaptive array

The performance of the constant modulus algorithm (CMA) with the steepest descent method used in an adaptive array of monopole antennas mounted on a rectangular conducting plate was investigated. The mutual coupling (MC) effect among the array elements and the diffraction effect caused by the conducting plate were taken into account in the calculation by a hybrid method of moment method (MM) and geometrical theory of diffraction (GTD). Simulations showed that the CMA adaptive array performs differently when the MC and the diffraction effects are taken into account. In some cases, the speed of convergence is slower with MC, and in other cases it is faster. Also, in multipath scenarios the array sometimes converges on a weaker delayed ray rather than the direct ray when MC is included. The capture property is explained by the fact that the CMA algorithm is sensitive to initial conditions and the initial array pattern is directional due to MC-not omnidirectional as in the ideal case. The performance of the array on a finite ground plane is different from that on an infinite ground plane due to diffraction effects     

COMPENSATION FOR THE EFFECTS OF MUTUAL COUPLING ON THE PERFORMANCE OF ADAPTIVE ARRAYS

Using the Method of Moments(MoM) and the spectral method, the effect of mutual coupling on the performance of adaptive arrays is compensated.First, the MoM is used to compute the behavior of the array,where the accurate analytical model and odd numbers of piecewise sinusoids are applied.Then the covariance matrix with mutual coupling being taken into account is analyzed, and the expression for the weight of the Least Mean Square(LMS) algorithm with mutual coupling being compensated is given.Finally, the method given in this letter is tested on an example.     

均匀先验分布Bayesian自适应波束形成方法

针对UUV舷侧阵存在观测信号方向有误差的情况，提出了基于均匀先验分布的Bayesian自适应波束形成方法（UB）。该方法假设期望信号的到达方向是区间内服从均匀先验分布的一个变量，利用含有均匀先验分布信息的阵列接收数据和Bayesian后验分布来估计期望信号的到达方向，最后计算权矢量。仿真结果表明，该方法对观测信号方向误差具有较好的稳健性，其阵列方向图的主波束不受观测方向误差的影响，始终对准信号的到达方向，其输出信干噪比随着输入信噪比、快拍数的增加而稳定增加，随着观测方向误差的增大而保持稳定的恒定值。      

The PDF of adaptive beamforming weights

The author derives a closed-form expression for the marginal probability density function (PDF) for the weight vector coefficients in a minimum-variance distortionless response (MVDR) adaptive beamformer, when the snapshots are independently identically distributed (IID) normal and the weights are computed via sample matrix inversion. The marginal PDF allows one to determine the dynamic range required to avoid saturation (with a specified degree of probability) in digital and/or analog implementation of beamforming weights