Adaptive beamforming for array signal processing in aeroacoustic measurements

Phased microphone arrays have become an important tool in the localization of noise sources for aeroacoustic applications. In most practical aerospace cases the conventional beamforming algorithm of the delay-and-sum type has been adopted. Conventional beamforming cannot take advantage of knowledge of the noise field, and thus has poorer resolution in the presence of noise and interference. Adaptive beamforming has been used for more than three decades to address these issues and has already achieved various degrees of success in areas of communication and sonar. In this work an adaptive beamforming algorithm designed specifically for aeroacoustic applications is discussed and applied to practical experimental data. It shows that the adaptive beamforming method could save significant amounts of post-processing time for a deconvolution method. For example, the adaptive beamforming method is able to reduce the DAMAS computation time by at least 60% for the practical case considered in this work. Therefore, adaptive beamforming can be considered as a promising signal processing method for aeroacoustic measurements.     

Frequency-invariant robust adaptive beamforming based on interference covariance matrix reconstruction

Consider the problems of frequency-invariant beampattern optimization and robustness in broadband beamforming.Firstly,a global optimization algorithm,which is based on phase compensation of the array manifolds,is used to construct the frequency-invariant beampattern.Compared with some methods presented recently,the proposed algorithm is not only available to get the global optimal solution,but also simple for physical realization.Meanwhile,a robust adaptive broadband beamforming algorithm is also derived by reconstructing the covariance matrix.The essence of the proposed algorithm is to estimate the space-frequency spectrum using Capon estimator firstly,then integrate over a region separated from the desired signal direction to reconstruct the interference-plus-noise covariance matrix,and finally caleulate the adaptive beamformer weights with the reconstructed matrix.The design of beamformer is formulated as a convex optimization problem to be solved.Simulation results show that the performance of the proposed algorithm is almost always close to the optimal value across a wide range of signal to noise ratios.     

基于干扰协方差矩阵重构的恒定束宽鲁棒自适应波束形成

针对宽带波束形成中的恒定束宽波束响应优化设计问题与鲁棒性问题展开研究。首先,提出一种基于相位补偿的恒定束宽全局优化设计方法,通过对阵列流形向量进行相位补偿来设计恒定束宽波束,与现有的一些方法相比,该方法不仅能获得全局最优解,而且物理实现简单。同时,还提出一种基于协方差矩阵重构的鲁棒自适应宽带波束形成算法。该算法采用Capon估计器估计样本数据的空间一频率谱密度函数,然后对期望信号波达方向之外的角度区间进行积分来重构干扰加噪声协方差矩阵,最后利用重构的协方差矩阵设计自适应波束形成器权系数。该波束形成器设计问题被表述成凸优化问题求解。仿真结果表明,在整个输入信噪比范围内,该算法几乎都能获得接近理想值的输出信干噪比。      

一种新的稳健波束形成算法及其一维搜索策略

存在条件失配时自适应波束形成器的性能急剧下降,凸优化技术的引入使稳健波束形成器的设计更加灵活,但同时带来了计算复杂度的增加和工程实现上的困难.针对上述问题,提出了一种基于最小二乘估计的稳健波束形成算法,并推导得到一种基于一维搜索的求解方法.首先利用广义旁瓣对消器的结构将标准Capon波束形成器转化为稳健最小二乘问题,并将该问题转化为二阶锥规划的形式.为了减少计算量,利用二阶锥规划问题的原始问题和对偶问题的关系,将求解过程转化为一维搜索,并利用牛顿迭代法获得最优解,从而获得与标准Capon波束形成相近的计算复杂度.仿真分析表明,该算法具有良好的抗导向矢量失配和快拍数不足的稳健性.     

一种最差情况下性能最优化的特征分析自适应波束形成方法

自适应波束形成在弱目标检测和空域滤波中应用广泛。然而在实际海洋环境中,失配情况比较普遍,往往会导致传统自适应波束形成方法性能明显下降。针对此问题,本文基于特征分析重构观测信号协方差矩阵来抑制干扰对弱目标检测的影响,在此基础上进一步利用凸优化算法来提高波束形成方法的鲁棒性。数值仿真和海试数据处理结果表明,本文所提方法在抑制干扰对弱目标影响的基础上,在阵元位置平均误差不超过入射信号中心频率对应波长的40%的情况下,仍可以鲁棒地检测目标信号。同时,该方法显著提高了自适应波束形成方法的输出信干噪比,且受对角加载量取值的影响较小。      

Adaptive signal processing for reducing nearby generated flow noise

By the acoustic holography method, it was found that there were multiple nearby noise sources, which are hard to be rejected by using the conventional beamforming technique. Instead of the conventional beamforming, we propose a new adaptive beamforming method to suppress nearby generated flow noise by using sonar sub-arrays.     

Adaptive beamforming for photoacoustic imaging

An adaptive photoacoustic image reconstruction technique that combines coherence factor (CF) weighting and the minimum variance (MV) method is introduced. The backprojection method is widely used to reconstruct photoacoustic tomography images. Owing to the scattering of light, the quality of the photoacoustic imaging can be degraded. CF, an adaptive weighting technique, is known to improve the lateral resolution of photoacoustic images. In addition, an MV adaptive beamforming method can further improve the image quality by suppressing signals from off-axis directions. Experimental studies are performed to quantify the spatial resolution and contrast of the adaptive photoacoustic beamforming methods.     

基于半定规划和秩-1分解的稳健波束形成

针对标准Capon波束形成器在存在导向矢量失配时性能急剧下降问题, 提出了一种基于半定规划和秩-1分解的稳健波束形成算法. 该方法通过对实际导向矢量的估计提高自适应波束形成算法稳健性. 首先分别从干扰抑制和噪声抑制两个方面推导了新导向矢量应满足的约束条件, 并证明了利用矩阵滤波器构造约束条件的合理性; 构造了估计最优导向矢量的优化问题并将其转化为易于求解的松弛半定规划问题, 同时引入秩-1分解理论用于优化问题的求解. 仿真分析表明, 与目前较为常见的算法相比, 本文算法只需利用期望信号可能入射区间这一先验信息, 能获得更高输出信干噪比和功率估计精度. 关键词： 稳健自适应波束形成 半定规划 秩-1分解 导向矢量估计     

基于近场聚焦逆波束形成的UUV平台噪声自适应抵消

UUV平台自噪声会对舷侧阵产生干扰，从而影响其探测性能，本文针对平台尾部自噪声源的直达噪声和海面反射噪声，提出了基于近场聚焦逆波束形成的平台噪声自适应抵消方法。文中利用UUV平台设计参数、深度以及运动姿态信息对尾部自噪声传播到舷侧阵的路径建立几何模型，并分析了影响该路径的因素；通过该模型，平台尾部自噪声能够实时自适应地通过聚焦波束形成被估计出来，从而在舷侧阵的接收信号中实现干扰抵消。仿真结果与海试实验数据处理结果表明，该方法能够有效抑制尾部自噪声干扰，显著提高UUV探测弱目标的能力。     

Acoustic analysis by spherical microphone array processing of room impulse responses

Spherical microphone arrays have been recently used for room acoustics analysis, to detect the direction-of-arrival of early room reflections, and compute directional room impulse responses and other spatial room acoustics parameters. Previous works presented methods for room acoustics analysis using spherical arrays that are based on beamforming, e.g., delay-and-sum, regular beamforming, and Dolph-Chebyshev beamforming. Although beamforming methods provide useful directional selectivity, optimal array processing methods can provide enhanced performance. However, these algorithms require an array cross-spectrum matrix with a full rank, while array data based on room impulse responses may not satisfy this condition due to the single frame data. This paper presents a smoothing technique for the cross-spectrum matrix in the frequency domain, designed for spherical microphone arrays, that can solve the problem of low rank when using room impulse response data, therefore facilitating the use of optimal array processing methods. Frequency smoothing is shown to be performed effectively using spherical arrays, due to the decoupling of frequency and angular components in the spherical harmonics domain. Experimental study with data measured in a real auditorium illustrates the performance of optimal array processing methods such as MUSIC and MVDR compared to beamforming.     

Observer-based beamforming algorithm for acoustic array signal processing

In the field of noise identification with microphone arrays, conventional delay-and-sum (DAS) beamforming is the most popular signal processing technique. However, acoustic imaging results that are generated by DAS beamforming are easily influenced by background noise, particularly for in situ wind tunnel tests. Even when arithmetic averaging is used to statistically remove the interference from the background noise, the results are far from perfect because the interference from the coherent background noise is still present. In addition, DAS beamforming based on arithmetic averaging fails to deliver real-time computational capability. An observer-based approach is introduced in this paper. This so-called observer-based beamforming method has a recursive form similar to the state observer in classical control theory, thus holds a real-time computational capability. In addition, coherent background noise can be gradually rejected in iterations. Theoretical derivations of the observer-based beamforming algorithm are carefully developed in this paper. Two numerical simulations demonstrate the good coherent background noise rejection and real-time computational capability of the observer-based beamforming, which therefore can be regarded as an attractive algorithm for acoustic array signal processing.     

圆弧形面阵自适应波束形成快速计算方法

针对圆弧形面阵估计水下目标二维波达方向的问题,提出一种降维处理的自适应波束形成方法。利用圆弧形面阵模型简化阵列内插矩阵的计算,通过垂直和水平两阶段波束加权,降低自适应波束形成维数,从而实现快速估计声源二维波达方向的目的。仿真结果表明,所提改进方法的计算量较传统二维最小方差无失真波束形成方法降低约一个数量级,且在低快拍条件下具有更明显的噪声抑制优势。湖上实验数据处理结果验证,在复杂水声环境下,所提方法具有较好的目标分辨性能。      

水下线谱噪声源识别的波束域时频分析方法研究

从联合空时频三维信息从发, 提出了波束域时频分析识别水下运动航行器低频线谱噪声源位置的方法. 首先, 利用小孔径圆环阵的超指向性波束形成, 将各线谱噪声源匀速通过正横位置附近时产生的多普勒信号在时域上分离. 其次, 分别使用伪Wigner-Ville分布和调频小波变换两种时频分析方法对波束输出的信号进行处理, 得到各噪声源信号的时频图像. 最后, 转换时间坐标到空间并参考配置信标, 即可识别低频线谱噪声源在水下航行器上的位置. 该方法解决了阵列识别水下低频噪声源的孔径受限问题, 同时对处理同频相干噪声源也适用. 仿真试验结果表明: 两种波束域时频分析方法都能较精确地识别低频线谱噪声源的位置; 在测量系统信息的配合下, 波束域调频小波变换的识别效果更优.     

Improving the resolution of three-dimensional acoustic imaging with planar phased arrays

This paper examines and compares two methods of improving the quality of three-dimensional beamforming with phased microphone arrays. The intended application is the detection of aerodynamic noise sources on wind turbines. Both methods employ Fourier based deconvolution. The first method involves a transformation of coordinates that tends to make the response to a point source, the point spread function, more shift invariant. The result is a significant improvement in sound source imaging in the transformed coordinate system. However, the inverse transformation to Cartesian coordinates introduces range dependent resolution limitations because of the irregular distribution of the focal points. The second method combines the transformation of coordinates with an alternative scanning technique. This method can be used in near field three-dimensional acoustic imaging to produce maps free of sidelobes and with constant resolution. The robustness of the proposed methods is validated both with computer simulations and experimentally.     

基于压缩感知的矢量阵聚焦定位方法

本文针对噪声源近场定位识别问题,利用声源分布在空间域具有稀疏性,在压缩感知理论框架下建立了新体系下的矢量阵聚焦波束形成方法,用于解决同频相干声源的定位识别问题.新方法可在小快拍下准确获得噪声源的空间位置,且不损失对噪声源贡献相对大小的评价能力.通过详细的理论推导、仿真分析和试验验证,证明了基于压缩感知的矢量阵聚焦定位新方法本质上实现了l1范数正则化求解下的波形恢复和空间谱估计,因此具有较高的定位精度,较强的相干声源分辨能力、准确的声源贡献相对大小评价能力以及较高的背景压制能力,可应用于水下复杂噪声源的定位识别.     

Waveguide invariant focusing for broadband beamforming in an oceanic waveguide

The performance of broadband sonar array processing can degrade significantly in shallow-water environments when interference becomes angularly spread due to multipath propagation. Particularly for towed line arrays near endfire, elevation angle spreading of multipath interference often results in masking of weaker sources of interest. While adaptive beamforming in a series of narrow frequency bands can suppress coherent multipath interference, this approach requires long observation times to estimate the required narrowband covariance matrices. To form wideband covariance matrices which can be estimated with less observation time, plane-wave focusing methods have been used to avoid interference covariance matrix rank inflation. This paper extends wideband focusing to the case of coherent multipath interference. The approach presented here, called waveguide invariant focusing (WIF), exploits a robust relationship for the frequency dependence of horizontal wave number differences. Unlike matched-field methods, WIF does not model multipath wave fronts but rather makes the interference appear to occupy the same rank-one subspace across frequency. This permits formation of wideband covariance matrices without interference rank inflation. Simulation experiments in a realistic ocean environment indicate that adaptive beamforming using WIF covariance matrices can provide a significant array gain improvement over conventional adaptive methods with limited observation time.     

平面波超声成像中的波束合成方法研究进展*

平面波成像通过单次全孔径发射-接收即可获取整幅图像,将成像帧频显著地提升至1000帧/秒以上。然而,平面波成像过程中发射的非聚焦波束将导致回波信号信噪比降低,进而使图像的分辨率和对比度变差。通过多角度相干复合成像技术可以改善平面波成像的图像质量,但是会以牺牲帧频为代价。因此研究人员们开始将新型波束合成技术引入平面波成像中,例如自适应波束合成、基于逆问题求解的波束合成及基于深度学习的波束合成方法等,以期实现图像质量和成像帧频间更好的权衡。该文综述了平面波成像中的新型波束合成方法领域的研究进展,并对该应用进行了总结和展望。     

基于时频分析的多目标盲波束形成算法

针对现有盲波束形成算法适用范围较窄, 多目标信号分离级联模式结构复杂、并联模式稳定性较差等问题, 提出一种基于时频分析的多目标盲波束形成算法. 该算法首先利用时频分析技术给出信号导向矢量的不确定集, 然后优化求解导向矢量的最优估计, 最后利用Capon方法实现多目标信号的并行输出. 理论分析及仿真结果表明, 该算法对信号特性没有特殊要求, 适用性较广, 性能稳定, 且输出信干噪比高于其他盲波束形成算法, 接近于最优Capon波束形成器.     

圆柱阵子阵分级处理的稳健超指向性波束形成方法

提出了圆柱阵子阵分级处理的稳健超指向性波束形成方法。首先建立了圆柱阵分两级子阵进行波束形成的信号模型,接着利用空间均匀噪声场中噪声互谱矩阵的循环特性得到基于特征波束分解与综合模型的圆柱阵超指向性的最优解,然后仿真研究了其误差敏感度函数、阵增益和波束图等性能指标,并与圆柱阵的传统全局处理方法进行了对比。提出的分两级子阵处理的超指向性方法与传统全局处理方法相比不仅降低了数据存储量和波束形成计算量,而且进一步提升了稳健性,并且在低频段的阵增益远远高于常规波束形成的值,对水下声呐阵列的设计具有一定的参考价值。      

Wind turbine noise measurement using a compact microphone array with advanced deconvolution algorithms

This paper experimentally investigates the noise from a large wind turbine (GE 1.5 MW) with a compact microphone array (OptiNav 24) using advanced deconvolution based beamforming methods, such as DAMAS and CLEAN-SC beamforming algorithms, for data reduction. Our study focuses on the ability of a compact microphone array to successfully locate both mechanical and aerodynamic noise sources on the wind turbine. Several interesting results have emerged from this study: (i) A compact microphone array is sufficient to perform a detailed study on wind turbine noise if advanced deconvolution methods are applied. (ii) Noise sources on the blade and on the nacelle can clearly be separated. (iii) Noise of the blades is dominated by trailing edge noise which is frequency dependent and is distributed along the length of the blade with the dominant noise source closer to the tip of the blade. (iv) The LP and DAMAS algorithms represent the distributed trailing edge noise source better than CLEAN-SC and classical beamforming. (v) Additional tonal noise produced during yawing operation is believed to be radiating from the tower of the wind turbine that acts like a resonator. (vi) Ground reflection is not believed to have a significant effect on noise source location estimates in this study.