Design of robust nearfield wideband beamformers with optimum subband constraints

Design of nearfield wideband beamformers robust against microphone mismatches is of great interest in practical applications. The state-of-the-art design approach is based on the fullband processing. In this paper, the over-constraint problem suffered by the fullband design approach is studied, which typically leads to the undesired signal distortion with low-pass filtered characteristics. To combat the over-constraint problem, a new design approach for robust nearfield wideband beamformers with optimum subband constraints is proposed. The performance of the proposed design approach is evaluated and compared with the fullband design counterpart via design examples.     

Design of broadband beamformers robust against gain and phase errors in the microphone array characteristics

Fixed broadband beamformers using small-size microphone arrays are known to be highly sensitive to errors in the microphone array characteristics. The paper describes two design procedures for designing broadband beamformers with an arbitrary spatial directivity pattern, which are robust against gain and phase errors in the microphone array characteristics. The first design procedure optimizes the mean performance of the broadband beamformer and requires knowledge of the gain and the phase probability density functions, whereas the second design procedure optimizes the worst-case performance by using a minimax criterion. Simulations with a small-size microphone array show the performance improvement that can be obtained by using a robust broadband beamformer design procedure.     

Robust Adaptive Microphone Array with Mainlobe and Response Ripple Control

Many existing adaptive beamformers possess robustness against arbitrary array steering vector (ASV) mismatches within presumed uncertainty set. However, when the array facing a large steering direction error, their performance degrade significantly since the uncertainty in steering direction generally gives rise to an outstanding mismatch in ASV. In the applications of microphone array, large steering direction error is often unavoidable because of the motion of target speaker. Meanwhile, in addition to conventional adaptive beamformers, microphone array also requests a controlled frequency response to target signal. In this paper, we propose a new adaptive microphone array implemented in frequency domain with controlled mainlobe and frequency response. A compact ASV uncertainty set explicitly modelling steering direction error and the other arbitrary ASV errors is exploited to derive beamformer with robust constraints on array magnitude response. Numerical results show that the proposed microphone array not only produces large controlled robust response region and robust frequency response, but also achieves high performance in SINR enhancement.     

Wideband Beamspace Processing Using Orthogonal Modal Beamformers

We introduce a novel beamspace processing structure that can be used for narrowband or wideband sources located either in nearfield or farfield of a sensor array. Main features of the new structure are: (i) a single parameter is used to steer the processor to any desired radial distance; (ii) a set of fixed frequency invariant orthogonal beamformers are used to transform array data into beamspace; and (iii) consequently, only a single set of beamspace weights are needed to process wideband beamspace data. The utility of the novel structure is illustrated by applications in interference cancellation and direction/range estimation.     

面向语音通信与交互的麦克风阵列波束形成方法

临境语音通信与智能语音交互都面临复杂声学环境中的远距离高保真拾音难题，解决这一难题的有效途径是使用由多个麦克风传感器组成的麦克风阵列或多通道拾音系统，这种系统的核心是信号处理，通过对空间采样的声场信息进行时、空、频三域的联合处理来实现声源定向/定位、信号增强、噪声抑制、混响抑制、声源分离、声场参数估计等功能。麦克风阵列信号处理的方法有很多，其中研究的最多、使用的最广的方法是波束形成。本文对麦克风阵列波束形成的原理、进展以及当前常用的方法进行简要综述，内容涵盖延迟求和、超指向、差分、正交级数展开、Kronecker和自适应波束形成方法等。论文侧重于方法原理、机理和架构方面的探讨，具体的算法实现细节感兴趣的读者可以参考相应的文献。      

Self-Calibration-Based Robust Near-Field Adaptive Beamforming for Microphone Arrays

Near-field beamforming using a microphone array has found many applications, such as sound acquisition in small rooms. However, robust near-field adaptive beamforming (NABF) against focal point errors has not been studied much in the literature until recently. In this brief, a robust near-field adaptive beamformer is proposed. The proposed method is developed by combining a new formulation of the point-constrained NABF and a self-calibration technique, in the presence of focal point uncertainties. The proposed method suffers from no loss in the degrees of freedom for interference rejection. Compared with conventional calibration-based adaptive beamformers, the proposed method has the advantage of not needing a noise-free calibration signal. Simulation results demonstrate that the performance of the proposed method is superior to that of the existing methods     

Subband processing for broadband microphone arrays

This paper considers array processing for wideband signals. The optimization techniques and associated performance results correspond to steerable but fixed beam microphone arrays, to be used in hearing aid applications, both in free-space and reverberant conditions. We first review the results on maximum energy (ME) broadband arrays. We subsequently formulate optimization criteria for array subband processing. The uniformly spaced subband and the non-uniformly spaced subband using quadrature mirror filter approaches are treated. Finally, various simulation results for free-space and reverberant conditions are presented to demonstrate the usefulness of this class of microphone arrays, as well as the feasibility of quadrature mirror filter-based subband processing.This work was partially supported by the House Ear Institute and the Retirement Research Foundation.     

宽带聚焦数字波束形成技术

分析了宽带信号波束形成研究的应用背景，并概述其国内外研究现状以及所提出方法的基本思路和应用范围。根据最近提出的频率域频率不变波束形成技术需要进行方位角初次估计和进行多次奇异值分解的问题，提出了在任意传感器阵列存在误差和互耦的情况下，基于摄动方法的宽带信号方位估计算法。该方法在考虑阵列位置、增益和相位测量误差和阵元之间存在互耦的情况下，提出了聚焦矩阵的摄动算法；最后，利用聚焦求和窄带方位估计的方法对宽带信号进行方位估计。     

TDOA声源定位中阵列阵型对误差的影响

在麦克风阵列声源定位中,不同阵列阵型及声源频率高低均对定位结果产生影响,探讨上述不同变量对定位结果产生误差的定量分析。使用到达时间差测量(TDOA)算法,运用16个麦克风分别组成十字型、同心圆、方型、L型、Y型阵列,探讨不同形状的麦克风阵列在不同频率声源下所产生的定位误差,并在Matlab上进行仿真分析,尝试得到较为准确的声源定位结果,提出一种误差最小的用于麦克风阵列声源定位的同心圆阵列阵型。     

WAVES: weighted average of signal subspaces for robust widebanddirection finding

Existing algorithms for wideband direction finding are mainly based on local approximations of the Gaussian log-likelihood around the true directions of arrival (DOAs), assuming negligible array calibration errors. Suboptimal and costly algorithms, such as classical or sequential beamforming, are required to initialize a local search that eventually furnishes DOA estimates. This multistage process may be nonrobust in the presence of even small errors in prior guesses about angles and number of sources generated by inherent limitations of the preprocessing and may lead to catastrophic errors in practical applications. A new approach to wideband direction finding is introduced and described. The proposed strategy combines a robust near-optimal data-adaptive statistic, called the weighted average of signal subspaces (WAVES), with an enhanced design of focusing matrices to ensure a statistically robust preprocessing of wideband data. The overall sensitivity of WAVES to various error sources, such as imperfect array focusing, is also reduced with respect to traditional CSSM algorithms, as demonstrated by extensive Monte Carlo simulations     

Wideband Antenna Patterns and Impulse Response of Broadband RF Phased Arrays With RF and Photonic Beamforming

The general expression for a monochromatic antenna pattern is extended to a two dimensional function with dependence on both space and time. Expressions for the wideband antenna pattern in space and the impulse response in time are developed. The effects of random errors in the spatial domain and errors common to all elements with fluctuations in the frequency domain are analyzed. Examples are given, including RF beamformers and elements in finite arrays, but with an emphasis on a photonic beamformer, which shows improved performance relative to its RF counterparts in both the spatial and time domains     

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.     

Applications of RF aperture-array spatially-bandpass 2-D IIR filters in sub-Nyquist spectrum sensing,wideband doppler radar and radio astronomy beamforming

The application of two-dimensional (2-D) infinite impulse response (IIR) spatially-bandpass (SBP) filters as a digital beamformer for a wide spectrum of practical applications spanning wireless cognitive radio communications, doppler radar, and radio astronomy instrumentation is discussed. The paper starts with an introduction of the recently proposed 2-D SBP filter. The first application is a spectrum sensing scheme for dynamic spectrum access based cognitive radios. A 2-D IIR SBP filter is used in conjunction with a sub-Nyquist wideband signal reconstruction technique to achieve aperture-array directional spectrum sensing using sub-Nyquist sparse sampling based on the recently reported Eldar algorithm. The second application is related to wideband pulse and continuous-wave frequency modulated Doppler radar sensing. The SBP filter is integrated with a wideband radar back-end connected to an electronically-steerable aperture antenna. A a low-complexity directional localization algorithm is presented, which estimates the range and angle of a target scatterer with a signal to interference ratio improvement of 10 dB. We also present applications of 2-D IIR SBP in the fields of classification and remote sensing of unmanned aerial vehicles. Finally, a digital aperture-array wideband beamforming model using the 2-D IIR SBP filters is presented for radio telescope systems based on dense aperture arrays and time-domain beamforming. A well-known example is the study of pulsar astrophysics using a highly-directional aperture antenna system. The 2-D IIR SBP beamformer is simulated as the digital backend of the time-domain beamforming system with array signals synthesized using measured time-domain signatures from the Crab pulsar obtained from the GAVRT. The SBP filter shows a gain of 12.3 dB with an order of magnitude lower circuit complexity compared to traditional phased-array digital beamformers. To obtain comparable levels of SINR improvement, the wideband phased-array beamformers require 48-point FFTs per antenna. Assuming the optimum three real-multiplications per complex multiplication for the Gauss algorithm, it is discovered that the proposed 2-D IIR SBP beamformers are more than 97 % lower in digital multiplier complexity compared to traditional FIR phased-array FFT-beamformers.     

Subband design of fixed wideband beamformers based on the least squares approach

Subband method is an effective way to reduce the computational complexity of a wideband system and in this paper we study the subband design problem for fixed wideband beamformers, with an emphasis on the design of frequency invariant beamformers (FIBs). We first express the equivalent fullband beam response as a function of the subband beamformer coefficients and then formulate the design problem based on the least squares approach. One direct least squares formulation is first proposed for the design of a general wideband beamformer, and then extended to the FIB design case, followed by three further variations.     

Robust Adaptive Beamformers Based on Worst-Case Optimization and Constraints on Magnitude Response

In this paper, novel robust adaptive beamformers are proposed with constraints on array magnitude response. With the transformation from the array output power and the magnitude response to linear functions of the autocorrelation sequence of the array weight, the optimization of an adaptive beamformer, which is often described as a quadratic optimization problem in conventional beamforming methods, is then reformulated as a linear programming (LP) problem. Unlike conventional robust beamformers, the proposed method is able to flexibly control the robust response region with specified beamwidth and response ripple. In practice, an array has many imperfections besides steering direction error. In order to make the adaptive beamformer robust against all kinds of imperfections, worst-case optimization is exploited to reconstruct the robust beamformer. By minimizing array output power with the existence of the worst-case array imperfections, the robust beamforming can be expressed as a second-order cone programming (SOCP) problem. The resultant beamformer possesses superior robustness against arbitrary array imperfections. With the proposed methods, a large robust response region and a high signal-to-interference-plus-noise ratio (SINR) enhancement can be achieved readily. Simple implementation, flexible performance control, as well as significant SINR enhancement, support the practicability of the proposed methods.     

Efficient wideband source localization using beamforming invariancetechnique

A novel scheme for wideband direction-of-arrival (DOA) estimation is proposed. The technique performs coherent signal subspace transformation by a set of judiciously constructed beamforming matrices. The beamformers are chosen to transform each of the narrowband array manifold vectors into the one corresponding to the reference frequency, regardless of the actual spatial distribution of the sources. The focused data correlation matrix can thus be obtained without any preliminary DOA estimation or iteration. A simplified version of the beamspace Root-MUSIC algorithm is developed and used in conjunction with the proposed method to efficiently localize multiple wideband sources with a linear, equally spaced array. Numerical simulations are conducted to demonstrate the efficacy of the new scheme     

A Competitive Mean-Squared Error Approach to Beamforming

We treat the problem of beamforming for signal estimation where the goal is to estimate a signal amplitude from a set of array observations. Conventional beamforming methods typically aim at maximizing the signal-to-interference-plus-noise ratio (SINR). However, this does not guarantee a small mean-squared error (MSE), so that on average the resulting signal estimate can be far from the true signal. Here, we consider strategies that attempt to minimize the MSE between the estimated and unknown signal waveforms. The methods we suggest all maximize the SINR but at the same time are designed to have good MSE performance. Since the MSE depends on the signal power, which is unknown, we develop competitive beamforming approaches that minimize a robust MSE measure. Two design strategies are proposed: minimax MSE and minimax regret. We demonstrate through numerical examples that the suggested minimax beamformers can outperform several existing standard and robust methods, over a wide range of signal-to-noise ratio (SNR) values. Finally, we apply our techniques to subband beamforming and illustrate their advantage in estimating a wideband signal.     

具有高测向精度的最优麦克风对称阵设计研究

麦克风平面阵列布局方式的不同会导致其测向性能的不同,而现有的阵列设计方法并不能使麦克风面阵的测向性能达到最优且其计算复杂度高。针对该问题,本文提出了基于克拉美罗界（Cramer Rao Bound）的最优麦克风对称阵设计方法。该方法给出了设计最优麦克风对称阵的约束条件,该约束条件能够使各阵元之间的相对位置满足特定的关系,从而提高阵列测向精度,同时也能降低阵列设计复杂度。本文利用该方法设计出了最优麦克风对称阵,并对其测向性能进行了理论分析和仿真验证。结果表明,与常见布局阵列相比,按照本文方法设计出的最优麦克风对称阵的测向性能最优。      

Further Study on Robust Adaptive Beamforming With Optimum Diagonal Loading

Significant effort has gone into designing robust adaptive beamforming algorithms to improve robustness against uncertainties in array manifold. These uncertainties may be caused by uncertainty in direction-of-arrival (DOA), imperfect array calibration, near-far effect, mutual coupling, and other mismatch and modeling errors. A diagonal loading technique is obligatory to fulfil the uncertainty constraint where the diagonal loading level is amended to satisfy the constrained value. The major drawback of diagonal loading techniques is that it is not clear how to get the optimum value of diagonal loading level based on the recognized level of uncertainty constraint. In this paper, an alternative realization of the robust adaptive linearly constrained minimum variance beamforming with ellipsoidal uncertainty constraint on the steering vector is developed. The diagonal loading technique is integrated into the adaptive update schemes by means of optimum variable loading technique which provides loading-on-demand mechanism rather than fixed, continuous or ad hoc loading. We additionally enrich the proposed robust adaptive beamformers by imposing a cooperative quadratic constraint on the weight vector norm to overcome noise enhancement at low SNR. Several numerical simulations with DOA mismatch, moving jamming, and mutual coupling are carried out to explore the performance of the proposed schemes and compare their performance with other traditional and robust beamformers     

Phone-based filter parameter optimization of filter and sum robust speech recognition using likelihood maximization

Because of noise and reverberation, accuracy of speech recognition systems decreases when the distance between talker and microphone increases. By the using of microphone arrays and appropriate filtering of received signals, the accuracy of recognizer can be increased. Many different methods for using microphone arrays have been proposed that can be classified into two main approaches: systems that perform in two independent stages of array processing and then recognition and systems that use array processing to generate a sequence of features which maximize the likelihood of generating the correct hypothesis in recognition phase. Following second approach, in this paper a new method for microphone array processing is proposed in which the parameters of array processing are adjusted in calibration phase based on phones used in language and maximum likelihood method. Optimized filter parameters are stored and used during recognition phase. A new modified Viterbi algorithm using optimal phone-based filter parameters is used for recognition phase. The proposed algorithm is analytically formulated and Persian language is used to find any improvement in speech recognition accuracy compared with results of delay and sum and utterance-based filter and sum algorithms. The results show 12.2% improvement in accuracy compared to utterance-based algorithm.