脉冲噪声环境中鲁棒的自适应波束形成方法

本文提出一种脉冲噪声环境中的自适应波束形成方法.方法假定噪声服从对称 α 稳定(S α S:Symmetric α -stable)分布,首先定义分数低阶阵列响应,然后根据最小方差无畸变响应波束形成器(MVDR)提出分数低阶最小方差无畸变响应波束形成器(FrMVDR).理论上证明了当阶数小于噪声特征指数的一半时,分数低阶阵列输出功率有界.计算机仿真实验证明了本文提出的FrMVDR波束形成器在高斯噪声和非高斯脉冲噪声环境中性能都优于MVDR和其他有关的基于分数低阶矩的波束形成器,是一种鲁棒的自适应波束形成器.     

一种稳健的低旁瓣波束形成技术

为了更好地抑制来自非期望方向的信号,波束形成器形成较低的旁瓣以抑制干扰。针对传统的最小方差无畸变响应(MVDR)波束形成器抑制干扰性能不稳健的缺点,提出了一种自适应MVDR波束形成方法。该算法通过对已形成波束图搜索极值点,排序取次大值即最高旁瓣,将其对应方向增加到"零陷"方向组,不断迭代以降低旁瓣级。结合均匀半圆阵所作的计算机仿真验证了该方法的正确性和有效性。     

一种近场环境下的麦克风阵列语音增强方法

针对语音源位于阵列近场而干扰噪声源位于阵列远场的声学环境,本文提出了一种基于近场双自适应波束形成的麦克风阵列语音增强方法。该方法利用近场声波波前的特点,主通道采用最小方差无失真响应准则的近场优化波束形成器,辅助通道采用双自适应波束形成技术,从而有效地抑制了混响和噪声对语音信号的影响。仿真实验结果表明,在房间混响条件下,本文方法具有良好的噪声抑制性能。     

Quadratically Constrained Beamforming Robust Against Direction-of-Arrival Mismatch

It is well known that the performance of the minimum variance distortionless response (MVDR) beamformer is very sensitive to steering vector mismatch. Such mismatches can occur as a result of direction-of-arrival (DOA) errors, local scattering, near-far spatial signature mismatch, waveform distortion, source spreading, imperfectly calibrated arrays and distorted antenna shape. In this paper, an adaptive beamformer that is robust against the DOA mismatch is proposed. This method imposes two quadratic constraints such that the magnitude responses of two steering vectors exceed unity. Then, a diagonal loading method is used to force the magnitude responses at the arrival angles between these two steering vectors to exceed unity. Therefore, this method can always force the gains at a desired range of angles to exceed a constant level while suppressing the interferences and noise. A closed-form solution to the proposed minimization problem is introduced, and the diagonal loading factor can be computed systematically by a proposed algorithm. Numerical examples show that this method has excellent signal-to-interference-plus-noise ratio performance and a complexity comparable to the standard MVDR beamformer.     

Efficient implementation of robust adaptive beamforming based on worst-case performance optimisation

Traditional adaptive beamforming methods undergo serious performance degradation when a mismatch between the presumed and the actual array responses to the desired source occurs. Such a mismatch can be caused by desired look direction errors, distortion of antenna shape, scattering due to multipath, signal fading as well as other errors. This mismatch entails robust design of the adaptive beamforming methods. Here, the robust minimum variance distortionless response (MVDR) beamforming based on worst-case (WC) performance optimisation is efficiently implemented using a novel ad hoc adaptive technique. A new efficient implementation of the robust MVDR beamformer with a single WC constraint is developed. Additionally, the WC optimisation formulation is generalised to include multiple WC constraints which engender a robust linearly constrained minimum variance (LCMV) beamformer with multiple-beam WC (MBWC) constraints. Moreover, the developed LCMV beamformer with MBWC constraints is converted to a system of nonlinear equations and is efficiently solved using a Newton-like method. The first proposed implementation requires low computational complexity compared with the existing techniques. Furthermore, the weight vectors of the two developed adaptive beamformers are iteratively updated using iterative gradient minimisation algorithms which eliminate the estimation of the sample matrix inversion. Several scenarios including angle-of-incidence mismatch and multipath scattering with small and large angular spreads are simulated to study the robustness of the developed algorithms.     

最小方差无失真响应波束形成解卷积后处理算法

为提高最小方差无失真响应(Minimum Variance Distortionless Response,MVDR)波束形成算法的方位分辨能力,本文将MVDR算法的输出功率谱重新建模为卷积的形式,并运用两种解卷积技术对MVDR的方位谱进行后处理.该算法将角度空间中心位置的单个声源的MVDR方位谱当作点扩散函数(Poi...     

基于稀疏约束和SRV约束的宽带自适应波束形成

针对传统的宽带MVDR自适应波束形成中,抑制干扰的同时会抬高旁瓣电平,且过多的线性约束会导致波束输出的SINR性能下降的问题,提出了一种基于SRV约束和稀疏约束的低旁瓣、高增益宽带自适应波束形成方法.该方法在窄带MVDR自适应波束形成基础上,通过增加波束图稀疏约束来降低波束的旁瓣电平,同时利用空间响应偏差(SRV)约束将窄带算法推广到宽带MVDR 自适应波束形成中,极大地降低了算法的复杂度,改善了波束输出的SINR 性能.与传统方法相比,该方法在降低宽带波束的旁瓣电平的同时,还具有良好的干扰抑制效果.数值仿真实验验证了该方法的有效性.     

基于双迭代MVDR波束形成的MIMO-OTHR多模扩展多普勒杂波抑制算法

针对多模传播引起的扩展多普勒杂波影响天波超视距雷达对低可探测慢速舰船目标检测性能的问题,该文在新一代多输入多输出天波超视距雷达系统下,利用双迭代最小方差无失真响应(MVDR)波束形成器抑制多模扩展多普勒杂波。考虑到时间叉排线性调频连续波MIMO天波雷达和慢时间相位编码MIMO天波雷达在有限相干积累时间内的训练样本数有限,且训练样本中包含主选模式期望信号,该文利用阻塞矩阵进行数据预处理,减小训练样本中的主选模式期望信号影响,并将LN×1维“发射-接收”2维权矢量优化分解为L×1维发射权矢量和N×1维接收权矢量,通过双迭代计算恢复出的2维MVDR权矢量来抑制多模扩展多普勒杂波,减小了计算量和样本需求。理论分析和仿真验证了算法的有效性。     

Adaptive Beamforming Using Frequency Invariant Uniform Concentric Circular Arrays

This paper proposes new adaptive beamforming algorithms for a class of uniform concentric circular arrays (UCCAs) having near-frequency invariant characteristics. The basic principle of the UCCA frequency invariant beamformer (FIB) is to transform the received signals to the phase mode representation and remove the frequency dependence of individual phase modes through the use of a digital beamforming or compensation network. As a result, the far field pattern of the array is electronic steerable and is approximately invariant over a wider range of frequencies than the uniform circular arrays (UCAs). The beampattern is governed by a small set of variable beamformer weights. Based on the minimum variance distortionless response (MVDR) and generalized sidelobe canceller (GSC) methods, new recursive adaptive beamforming algorithms for UCCA-FIB are proposed. In addition, robust versions of these adaptive beamforming algorithms for mitigating direction-of-arrival (DOA) and sensor position errors are developed. Simulation results show that the proposed adaptive UCCA-FIBs converge much faster and reach a considerable lower steady-state error than conventional broadband UCCA beamformers without using the compensation network. Since fewer variable multipliers are required in the proposed algorithms, it also leads to lower arithmetic complexity and faster tracking performance than conventional methods.     

A multiple time scale modularized adaptive beamformer

This paper analyzes the cascaded equivalent form of the minimum variance distortionless response (MVDR) beamformer. A unique feature of the modularized MVDR (M²VDR) beamformer is the ability to distribute adaptive degrees of freedom (DOF) among beamformer stages. This property of the M²VDR beamformer allows DOF to be adapted over different time scales. As a consequence of the multiple stage decomposition adaptive beamformer weights appear in a form which suggest an apparent increase in the number of DOF. To properly analyze this ease an alternative interpretation of adaptive DOF is introduced to establish the equivalence between the MVDR beamformer and its cascaded realization. In the second part of this paper the distribution for the output power estimate of a P stage M²VDR beamformer is derived. Analysis reveals the necessity of placing constraints on the adaptation time assigned to each beamformer stage. Simulation experiments are presented that demonstrate the applicability of the M ²VDR beamformer in resolving closely spaced sources under impulsive interference conditions     

双通道能量差后滤波语音增强算法统计分析和改进

双通道能量差后滤波语音增强算法在语音通信系统的噪声抑制技术中有较好的应用前景,然而其理论性能和局限性还未得到充分研究。为此,本文采用统计分析方法研究了双通道能量差后滤波语音增强算法的性能,分析了相干性、平滑因子及噪声估计误差对算法的影响。理论和仿真结果表明,噪声估计误差和平滑因子严重影响该算法的降噪性能。依据此分析结果,本文提出一种基于非平稳噪声估计和功率谱自适应平滑的双通道能量差后滤波算法。测试结果表明,本文提出的算法在不增加语音失真的前提下,能更有效地抑制非平稳噪声,段信噪比提高(SegSNRI)和语音质量感知评估(PESQ)等客观评价指标都表明本文的算法优于其它几种经典的后滤波算法。      

复广义高斯分布多通道最大似然联合去噪去混响波束形成器

提出了一种基于复超高斯分布的多通道联合去噪去混响波束形成器。本文采用复超高斯模型对语音信号建模,在最大似然准则下首次推导出联合去噪去混响波束形成器的解析表达式,并证明了该式是现有多种联合去噪去混响波束形成器的一般化形式。同时通过理论推导证明本文所提算法性能优于传统多通道预测误差算法级联最小功率无失真波束形成器。仿真实验与实际实验结果均表明,本文提出的算法在多个客观指标上明显优于现有联合去噪去混响算法。      

一种稳健超增益波束形成方法

最小方差无失真响应(MVDR)的基本原理是让它感兴趣方位的信号无失真通过,而使得波束输出噪声方差最小。本文提出一种圆阵稳健超增益波束形成方法,在各向同性噪声场中,当阵元间距小于半个波长时,其性能远远优于传统的波束形成器;同时,采用白噪声增益约束(white noise gain constraint,WNC)算法来提高超增益波束形成受随机误差扰动影响的鲁棒性。仿真验证算法的有效性。     

Turbo decoding of concatenated channel coding and trellis shaping for peak power controlled single-carrier systems

Trellis shaping (TS) has found its application in the peak power control of band-limited single-carrier signals. Our recent work has demonstrated that a well-designed TS can control the symbol transitions such that the output signal has almost constant envelope, which significantly alleviates the linearity requirement of power amplifiers. Compared to transmission without constellation shaping, however, the TS involves signal constellation expansion exclusively for peak power control. Therefore, unlike trellis coded modulation (TCM) that increases the minimum Euclidean distances (MED), the TS decreases the MED, thus incurring the increase in signal-to-noise power ratio (SNR) required for achieving a certain error rate. In this letter, in order to overcome this drawback, we propose a serial concatenation of coding and shaping together with an effective decoding algorithm that utilizes the memory effect (i.e., error correcting capability) of the shaped symbols. The achievable performance of the proposed system is analyzed in terms of the average mutual information. The simulation results demonstrate that the iterative decoding of the proposed concatenated system with outer convolutional codes and inner trellis shaping offers a significant performance gain.     

Robust microphone arrays using subband adaptive filters

A new adaptive beamformer which combines the idea of subband processing and the generalised sidelobe canceller structure is presented. The proposed subband beamformer has a blocking matrix that uses coefficient-constrained subband adaptive filters to limit target cancellation within an allowable range of direction of arrival. Simulations comparing the fullband and subband adaptive beamformers show that the subband beamformer has better performance than the fullband beamformer when the target and/or interfering signals are coloured. In reverberant environments, the proposed subband beamformer also performs better than its fullband counterpart     

Widely Linear MVDR Beamformers for the Reception of an Unknown Signal Corrupted by Noncircular Interferences

For nonstationary observations, potentially second-order (SO) noncircular, the SO optimal complex filters are time variant (TV) and, under some conditions of noncircularity, widely linear (WL). Moreover, for applications such as spectrum monitoring or passive listening, the sources' waveforms are unknown and no training sequence or spreading code is a priori available. In this context, this paper aims at introducing the time invariant (TI) WL minimum variance distortionless response (MVDR) beamformer for the optimal reception of an unknown signal, whose waveform is unknown but whose steering vector is known, corrupted by potentially noncircular interferences. Its properties, performance, and adaptive implementation in noncircular contexts are analyzed in this paper. This optimal beamformer is shown to always improve, in the steady state, the performance of the well-known Capon's beamformer for noncircular interferences. Moreover, it should be noticed that this optimal beamformer allows the processing of up to 2 (N-1) rectilinear interferences from an array of N sensors. Finally, at the end of this paper, a TV extension of this TI WL MVDR beamformer is presented to process SO noncircular interferences having a nonnull carrier residue or frequency offset.     

基于稀疏时频分解的盲波束形成算法

针对现有盲波束形成算法通用性差,所需采样数据量大等问题,该文提出一种基于稀疏时频分解的盲波束形成算法。算法首先将传统的短时傅里叶变换转化为稀疏重构问题,利用交替分裂Bregman算法进行迭代求解。然后利用对各阵元的接收信号进行稀疏时频分解的结果,结合聚类和不确定集方法,实现导向矢量的最优估计。最后利用MVDR算法获得最优权矢量。该算法无需利用信号统计特性,实现了高效的盲波束形成。仿真实验结果表明,该算法所需数据量小,迭代步骤易于工程实现,较现有盲波束形成算法输出性能更优,适用范围更广。     

A Bayesian approach to robust adaptive beamforming

An adaptive beamformer that is robust to uncertainty in source direction-of-arrival (DOA) is derived using a Bayesian approach. The DOA is assumed to be a discrete random variable with a known a priori probability density function (PDF) that reflects the level of uncertainty in the source DOA. The resulting beamformer is a weighted sum of minimum variance distortionless response (MVDR) beamformers pointed at a set of candidate DOAs, where the relative contribution of each MVDR beamformer is determined from the a posteriori PDF of the DOA conditioned on previously observed data. A simple approximation to the a posteriori PDF results in a straightforward implementation. Performance of the approximate Bayesian beamformer is compared with linearly constrained minimum variance (LCMV) beamformers and data-driven approaches that attempt to estimate signal characteristics or the steering vector from the data     

Sidelobe suppression for adaptive beamforming with sparse constraint on beam pattern

To suppress the sidelobe level of adaptive beamforming, sparse constraint on beam pattern is added to the conventional minimum variance distortionless response (MVDR) beamformer. The sparse constraint is an Lp-norm which can be explained as a diversity measure to evaluate the sparsity of the beam pattern. The proposed beamformer can not only reduce the sidelobe level, but also increase robustness against the mismatch problem caused by imprecise knowledge of the desired source.     

Novel Transmit Beamforming Schemes for Time-Selective Fading Multiantenna Systems

Transmit beamforming has been widely adopted for wireless systems with multiple transmit antennas. For a block fading channel, the Grassmannian beamformer has been shown to provide very good performance for finite rate feedback. However, the original Grassmannian beamformer does not take the time domain correlation of the channel fading into consideration. In this paper, based on a first-order autoregressive (AR1) dynamic fading model, we develop two new classes of beamforming algorithms that exploit the interframe correlations in the channel fading. We first introduce an algorithm based on a standard predictive vector quantization (PVQ) approach, and the resulting PVQ beamformer accomplishes superior power delivery at the receiver. However, the error performance of the PVQ beamformer is not satisfactory at high signal-to-noise ratios, and it also has a high implementation complexity. To resolve these issues, we then develop a novel successive beamforming (SBF) algorithm. The new SBF scheme uses the knowledge of the previous fading blocks to aid the beamforming codebook design of the current fading block. The beamforming codebook is constructed based on the successive partition of the surface of a spherical cap. The new SBF scheme accomplishes nearly the same performance as that of the PVQ beamformer, and it has a much simpler implementation. Through numerical simulations, we demonstrate that the proposed beamformers outperform the other previously proposed beamformers at various fading scenarios