一种低复杂度的鲁棒自适应波束形成算法

传统基于干扰噪声协方差矩阵（interference-plus-noise covariance matrix,INCM）重构的鲁棒自适应波束形成（robust adaptive beamformer,RAB）算法在多种样本数据协方差矩阵误差和信号导向向量误差的失配环境中具有较强的鲁棒性,但目前主流的INCM重构法都是对信号和干扰的导向向量通过建立凸优化模型来估计,这带来了很高的计算复杂度。为了解决这个问题,提出了一种低复杂度的基于INCM重构的RAB算法。该算法首先将干扰信号的导向向量分解为对应标称项和误差项的和,然后通过一种子空间方法估计得到误差项的单位向量。接下来对一个Capon空间谱功率最大问题进行求解,得到误差项的模值,以此得到重构的INCM。同时利用Capon空间谱中残差噪声的存在,使用交替投影法估计得到期望信号的导向向量,最后得到所提算法的权重向量。仿真实验表明所提算法在多种误差环境下具有较强鲁棒性的同时,还具有较低的计算复杂度。     

稳健的全阵波束形成方法

由于相干干扰和角度估计误差影响波束形成性能,对此提出一种稳健的波束形成方法。采用加权空间平滑算法去除相干性;对期望信号施加约束,保证一定角度估计误差范围内算法的稳健性;进行全阵波束形成变换,避免阵列孔径损失。仿真结果表明,在相干干扰环境中,该算法的方向图在期望信号方向有明显主瓣,有利于接收期望信号;在一定的角度估计误差范围内,该算法可保持比较高的且比较平坦的输出信干噪比;随着输入信噪比的增加,输出信干噪比几乎线性增大。     

基于干扰噪声矩阵重构的自适应波束形成算法

针对在自适应波束形成中,当采样次数较少或期望信号导向矢量存在误差以及训练数据中含有期望信号成分时导致波束输出信干噪比(SINR)下降的问题,提出了一种重构干扰噪声协方差矩阵并且估计期望信号导向矢量的稳健自适应波束形成方法。在期望信号波达方向的角度范围已知的条件下,首先利用多重信号分类（MUSIC）空间谱在不含期望信号的区域重构出干扰噪声协方差矩阵;然后推导了避免期望信号的导向矢量的估计值收敛到任一干扰的导向矢量或它们的线性组合的约束条件;进而以此约束条件和阵列输出功率最大化条件建立了期望信号导向矢量估计的优化问题,并使用凸优化软件估计出最优的期望信号导向矢量。讨论了该方法的计算复杂度并通过仿真实验验证了其有效性和优越性。仿真结果表明,当期望信号和干扰源存在随机指向误差和局部散射的情况下,所提方法在很大的输入信噪比范围内的输出信干噪比仍接近理论值,优于其他自适应波束形成方法。     

一种稳健的波束域自适应波束形成算法

在波束域算法中,针对波束域期望信号的指向误差落在波束主瓣边缘时波束性能严重恶化,采用波束域旋转矢量法的线性约束来改善波束域自适应算法的性能,同时为提高工程的实施性,减少算法的计算量,利用信号的特征值大于噪声的特征值这一理论,采用空间协方差矩阵逆的高阶次幂来逼近信号子空间,将求得的权矢量投影于改进的波束域的特征信号子空间,该算法在波束域中不但减少了计算量,而且使波束具有更好的信号比和稳健性。实验仿真验证了提出的改进波束域特征空间的稳健自适应算法的正确性和有效性,具有一定的工程实用价值。     

Performance evaluation of uniform linear array for adaptive beamforming using a novel Fibonacci branch algorithm

A new metaheuristic algorithm Fibonacci branch search (FBS) based on two innovative criteria rules, tree's branches fundamental structure and interactive searching rules, was introduced in this paper and applied to adaptive beamforming (ABF) field for uniform linear array. The global optima in search space can be reached by FBS during the searching process by the fitness evaluation of optimization rules. In this mode, two types of multidimensional points are to construct the branch structure of FBS based on shortening fraction selected by Fibonacci series. Then, the interactive local optimization and global searching rules are implemented alternately to obtain the optimal solutions, avoiding the search points trapping and stagnating in the local optimum. The performance of global searching ability of FBS has been evaluated by standard benchmark functions. It is also used here to construct an ABF technique as a practical issue to improve the nulling level. The simulation results of implemetation of FBS are compared with the five well‐known heuristic optimization algorithms and verfied the superior of the proposed FBS approach in both locating the global optimal solution and higher precision of nulling improvement in the ABF.     

一种简化特征空间稳健自适应波束形成算法*

在基于特征空间(ESB)的自适应波束形成算法中,针对当指向误差落在波束主瓣的边缘特定角度时,输出信干噪比下降,且信号子空间需要进行费时的特征值分解的问题,提出了改进线性约束最小方差(LCMV)算法。在假定的期望信号方向附近减少一个方向性约束条件,并基于信号特征值大于噪声特征值的这一特性, 利用空间协方差矩阵逆的高阶次幂来逼近信号子空间,无须特征分解,将求得的权矢量向改进的信号子空间投影。该方法能够大大减少计算量,同时还显著提高了自适应波束形成稳健性。通过仿真分析及结果比较验证了算法的正确性和有效性,因此从     

Analysis of uniform circular arrays for adaptive beamforming applications using particle swarm optimization algorithm

In this article, the particle swarm optimization algorithm is used to calculate the complex excitations, amplitudes and phases, of the adaptive circular array elements. To illustrate the performance of this method for steering a signal in the desired direction and imposing nulls in the direction of interfering signals by controlling the complex excitation of each array element, two types of arrays are considered. A uniform circular array (UCA) and a planar uniform circular array (PUCA) with 16 elements of half‐wave dipoles are examined. Also, the performance of an adaptive array using 3‐bit amplitude and 4‐bit phase shifters are studied. In our analysis, the method of moments is used to estimate the response of the dipole UCAs in a mutual coupling environment. © 2007 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2008.     

基于协方差矩阵重构的稳健自适应波束形成算法综述

Capon波束形成器作为理论上最优的波束形成器具有良好的干扰抑制能力。然而Capon波束形成器对于模型失配误差非常敏感,尤其是针对协方差矩阵和期望信号导向矢量误差,波束形成器的性能会严重下降,这大大降低了波束形成器的稳健性。目前,一系列基于协方差矩阵重构的稳健自适应波束形成算法被提出,这些算法核心思想都是利用Capon功率谱一定的角度范围内积分来重构出协方差矩阵。本文首先介绍了波束形成的信号模型,然后在Capon波束形成器的基础上,介绍了4种基于协方差矩阵重构的稳健自适应波束形成技术,最后对未来波束形成技术的研究热点进行了展望。     

一种基于协方差矩阵重构和EMP的宽带波束形成算法

在宽带波束形成中,若干扰信号从主瓣方向进入,会引起主瓣畸变、旁瓣电平抬高,从而使波束性能严重恶化。为了解决波束形成中的这些问题,研究了一种基于协方差矩阵重构和特征投影预处理（EMP）的宽带波束形成算法。该算法首先通过EMP算法求取阻塞矩阵,对接收信号进行干扰相消预处理阻塞掉主瓣干扰;然后通过相干信号子空间（CSM）方法、协方差矩阵重构求取合理的协方差矩阵;最后进行波束形成。在主瓣干扰、旁瓣干扰同时存在的情况下,该算法能够自适应地阻塞主瓣干扰、抑制旁瓣干扰,解决了存在主瓣干扰情况下宽带波束形成的波形畸变问题。计算机仿真验证了该算法有效性。     

同参数估计对偶的自适应控制算法

本文把线性和非线性系统统一处理。从自适应控制算法与参数估计算法的对偶性出发,提出了自适应控制算法的一种统一格式。这种格式算法简单,并在一定的条件下,能使控制误差一致的足够小。     

空间谱估计和数字波束形成的RFID信号辨识

针对超高频和微波段射频识别系统(RFID)信号在噪声干扰和多标签环境下难以辨识的问题,提出一种新的RFID信号辨识方法。以均匀直线阵为基础,采用空间谱估计算法正确估计出波达方向(DOA),再根据信号波达方向通过数字波束形成技术产生自适应定向波束来辨识信号。仿真分析表明,该方法具有较低的信噪比门限和较高的信号辨识和防碰撞性能。     

车用锂离子动力电池自适应状态联合估计研究

为确定动力电池的剩余电量和峰值功率这两个关键指标, 提出一种基于数据驱动的在线参数辨识方法, 通 过递归最小二乘法精确计算电池的实时参数; 然后设计了一种基于自适应扩展卡尔曼滤波的多状态联合估计算法, 准确估计电池的实时荷电状态; 并在电压、剩余电量和单体峰值电流的多约束条件下, 建立多采样间隔持续峰值功 率估算的数学模型. 最后在MATLAB/Simulink环境下搭建基于纯电动汽车实际运行工况的硬件在环测试模型. 结 果表明: 在初始误差较大时, 剩余电量的估计误差在3%左右, 硬件在环测试系统的端电压误差保持在20 mV以内, 峰值功率的平均误差为4.9745 W, 为联合估计算法的准确性提供了可靠理论依据.     

Perturbation estimation based coordinated adaptive passive control for multimachine power systems

This paper proposes a perturbation estimation based coordinated adaptive passive control (PECAPC) of generators excitation system and thyristor-controlled series capacitor (TCSC) devices for complex, uncertain and interconnected multimachine power systems. Discussion begins with the PECAPC design, in which the combinatorial effect of system uncertainties, unmodelled dynamics and external disturbances is aggregated into a perturbation term, and estimated online by a perturbation observer (PO). PECAPC aims to achieve a coordinated adaptive control between the excitation controller (EC) and TCSC controller based on the nonlinearly functional estimate of the perturbation. In this control scheme an explicit control Lyapunov function (CLF) and the strict assumption of linearly parametric uncertainties made on system structures can be avoided. A decentralized stabilizing EC for each generator is firstly designed. Then a coordinated TCSC controller is developed to passivize the whole system, which improves system damping through reshaping the distributed energies in power systems. Case studies are carried out on a single machine infinite bus (SMIB) and a three-machine system, respectively. Simulation results show that the PECAPC-based EC and TCSC controller can coordinate each other to improve the power system stability, finally a hardware-in-the-loop (HIL) test is carried out to verify its implementation feasibility.     

基于自适应参数估计的鲁棒语音增强算法

基于鲁棒H_∞滤波器理论和共轭梯度自适应参数估计方法提出了一种对复杂噪声有抑制效果的语音增强算法。应用这种方法自适应地从带噪信号中提取语音参数时不必预先知道噪声源的统计特性,只要求噪声信号能量有限。因为它基于H_∞滤波器,所以可保证由外界干扰和附加噪声引起的性能指标恶化达到最小。仿真结果表明：该语音增强算法具有计算速度快、鲁棒性好、语音增强效果明显、易于实现、可抑制复杂背景噪声等特点。     

Diffusion normalized subband adaptive algorithm for distributed estimation employing signed regressor of input signal

This paper presents a novel diffusion subband adaptive filtering algorithm for distributed estimation over networks. To achieve the low computational load, the signed regressor (SR) approach is applied to normalized subband adaptive filter (NSAF) and two algorithms for diffusion networks are established. The diffusion SR-NSAF (DSR-NSAF) and modified DSR-NSAF (MDSR-NSAF) have fast convergence speed and low steady-state error similar to the conventional DNSAF. In addition, the proposed algorithms have lower computational complexity than DNSAF due to the signed regressor of the network input signals at each node. Also, based on the spatial-temporal energy conservation relation, the mean-square performance of DSR-NSAF is analyzed and the expressions for the theoretical learning curve and steady-state error are derived. The good performance of these algorithms and the validity of the theoretical results are demonstrated by presenting several simulation results.     

Robust H2 estimation and control

This paper is concerned with the H2 estimation and control problems for uncertain discretetime systems with normbounded parameter uncertainty. We first present an analysis result on H2 norm bound for a stable uncertain system in terms of linear matrix inequalities ( LMIs). A solution to the robust H2 estimation problem is then derived in terms of two LMIs. As compared tothe existing results, our result on robust H2 estimation is more general. In addition, explicit search of appropriate scaling parameters is not needed as the optimization is convex in the scaling parameters. The LMI approach is also extended to solve the robust H2 control problem which has been difficult for the traditional Riccati equation approach since no separation principle has been known for uncertain systems. The design approach is demonstrated through a simple example.     

Robust H_2 estimation and control

This paper is concerned with the H2 estimation and control problems for uncertain discretetime systems with norm-bounded parameter uncertainty. We first present an analysis result on H2 norm bound for a stable uncertain system in terms of linear matrix inequalities (LMIs). A solution to the robust H2 estimation problem is then derived in terms of two LMIs. As compared to the existing results, our result on robust H2 estimation is more general. In addition, explicit search of appropriate scaling parameters is not needed as the optimization is convex in the scaling parameters. The LMI approach is also extended to solve the robust H2 control problem which has been difficult for the traditional Riccati equation approach since no separation principle has been known for uncertain systems. The design approach is demonstrated through a simple example.     

LMS自适应信道估计算法及仿真

提出一种基于连续导频的LMS自适应信道估计算法，在一个符号内进行ⅢS自适应滤波，经多次迭代得到信道估计值，然后根据信道变化速度再对其进行多符号平均。接收系统通过Simulink实现，并通过编写S函数仿真LMS自适应信道估计算法，系统动态仿真结果显示此方法可明显提高信道估计的准确度和接收机性能。     

超声波测风系统中自适应时延估计算法的研究

在时差法超声波测风系统中,风速的测量精度受到时间延迟估计精度、两超声波传感器的距离精度等的影响。在后者一定的情况下,测风精度对时延估计精度提出了更高的要求。对此,采用了一种基于权值检测的最小均方误差(LMS)自适应时延估计算法,从而实现了高精度时延估计。计算机仿真与实际测试表明:该算法的估计精度满足了所研制的超声波测风系统的设计要求,能够用于机场区域低空风场情况的监测。