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.     

低噪声通过特性的测量仿真研究

本文研究运用组合传感器和声压、振速联合信息处理技术进行低品声通过特性的测量。通过特性的背景噪声出非相干的各向同性白噪声和相干的交通干扰组成,交通干扰又分为平稳与非平稳两种,用平均声强器来抗非相干干扰;用交通干扰能量流中心方位抑制技术来抗平稳的相干干扰;对于非平稳的相干干扰而能量流中心方位抑制技术。仿真试验表明效果良好。     

低信噪比线性调频信号目标的方位估计

线性调频(LFM)信号目标的方位估计是水声探测研究的重要内容,在进行方位估计时,若存在强干扰信号源与强背景噪声,阵元接收信号的信噪比会显著降低,严重影响LFM信号目标方位估计结果的准确性.针对该问题,提出了一种简明分数阶滤波方法,并将其与常规波束形成方法(CBF)相结合来实现低信噪比条件下LFM信号目标的方位估计.简明分数阶傅里叶变换能在正交角度上将LFM信号的能量聚集在特定频点处并形成明显的能量峰,利用该特性,可对阵列各阵元接收的低信噪比LFM信号在简明分数阶域聚集的能量峰进行最佳滤波,以滤除干扰信息及背景噪声.对滤波输出进行逆简明分数阶傅里叶变换可得到增强信干比和信噪比的阵元域信号,进一步用于目标方位估计,就能获得更加准确的目标方位。数值仿真结果和海试实验数据处理结果验证表明,本文所提出的方法可有效抑制干扰和背景噪声,并对低信噪比LFM信号进行准确、稳健的方位估计。      

A covariance fitting approach for correlated acoustic source mapping

Microphone arrays are commonly used for noise source localization and power estimation in aeroacoustic measurements. The delay-and-sum (DAS) beamformer, which is the most widely used beamforming algorithm in practice, suffers from low resolution and high sidelobe level problems. Therefore, deconvolution approaches, such as the deconvolution approach for the mapping of acoustic sources (DAMAS), are often used for extracting the actual source powers from the contaminated DAS results. However, most deconvolution approaches assume that the sources are uncorrelated. Although deconvolution algorithms that can deal with correlated sources, such as DAMAS for correlated sources, do exist, these algorithms are computationally impractical even for small scanning grid sizes. This paper presents a covariance fitting approach for the mapping of acoustic correlated sources (MACS), which can work with uncorrelated, partially correlated or even coherent sources with a reasonably low computational complexity. MACS minimizes a quadratic cost function in a cyclic manner by making use of convex optimization and sparsity, and is guaranteed to converge at least locally. Simulations and experimental data acquired at the University of Florida Aeroacoustic Flow Facility with a 63-element logarithmic spiral microphone array in the absence of flow are used to demonstrate the performance of MACS.     

声矢量圆阵宽带相干目标MVDR方位估计*

针对宽带相干目标的远程探测问题，本文提出一种基于声压振速联合处理和矢量重构的声矢量圆阵MVDR波束形成方法。该方法利用相位模态变换技术，将声矢量圆阵变换为与信号频率无关的虚拟线阵，并构建虚拟线阵声压与组合振速的互协方差矩阵，利用声压与振速各分量间的空间相关性有效地抑制各向同性环境噪声；并对宽带相干信号的互协方差矩阵进行矢量重构，即将最大特征值对应的特征向量划分为相互重叠的子向量，从而构建前/后向Hermitian矩阵；最后，基于MVDR波束形成器实现宽带相干目标的方位估计。仿真计算和实验数据处理结果表明，该方法具较强的解相干能力和噪声抑制能力以及较高的方位估计性能。     

单矢量水听器方位估计的柱状图方法

单矢量水听器可以估计目标方位,矢量水听器信号处理中用到的平均声强器的处理方法能很好地抗各向同性的非相干干扰,但不能抗相干干扰.文中提出了一种新的单矢量水听器方位估计方法柱状图方位估计法,介绍了该方法的原理;对宽带信号中含强线谱相干干扰的情况进行了计算机仿真,结果表明该方法在强线谱相干干扰下能有效检测目标、估计目标方位;海试结果验证了该方法抗强线谱相干干扰的有效性.     

L-M非线性拟合的TDLAS氧气测量研究

氧气浓度是工业生产过程中重要监测参数,采用可调谐二极管激光吸收光谱法(tunable diode laser absorption spectroscopy,TDLAS),结合波长调制技术,可以实现对现场氧气浓度的高精度在线监测,利用氧气位于760 nm处的特征吸收峰进行了氧气浓度的测量。由于激光具有很强的相干性,所以TDLAS技术的检测灵敏度受到光学干涉噪声的严重制约,特别在低浓度时,光学干涉引起的基线起伏使得提取吸收峰波形信号时出现较大误差,影响了TDLAS分析仪的监测灵敏度。针对这一情况,采用了Levenberg-Marquardt非线性拟合算法,并且利用了吸收谱线线型——洛伦兹线型的导数形式对波长调制后获得的二次谐波波形信号进行拟合,提取波形信息。另一方面Levenberg-Marquardt非线性拟合方法需要有大量的计算,为了使研制的TDLAS分析仪能够实现现场的实时监测,采用了支持浮点运算的DSP的C28系列芯片进行数据处理,实现仪器在现场实时监测的功能。实验结果表明,该算法能够有效提取二次谐波信号的吸收峰特征值、克服背景噪声影响,由算法反演得到的氧气浓度与实际浓度的线性比值为1.01,浓度测量的线性误差为1.18%。     

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.     

浅海波导环境失配下的协方差矩阵拟合稳健匹配场声源功率估计

实际浅海波导中环境噪声为相干噪声,最小方差匹配场声源功率估计方法能在相干噪声背景下准确估计声源辐射功率,但该方法受环境不确定性影响较大;此外,由于最小方差匹配场声源功率估计方法使用信号幅度作为中间量估计声源功率,信号幅度估计误差会二次放大并传递到声源功率估计结果中。本文提出一种协方差矩阵拟合稳健最小方差匹配场声源功率估计方法,该方法引入信道传递函数不确定集,结合协方差矩阵拟合思想将声源功率估计问题建模为在信道传递函数不确定集约束下对函数取极值的问题,使用Lagrange乘子法求解该问题得到信道传递函数估计值和声源辐射功率估计值。环境失配影响声源辐射功率估计性能的根本原因在于信道传递函数偏差较大,协方差矩阵拟合稳健匹配场声源功率估计方法有效减小了环境失配时信道传递函数的偏差,从而显著提升环境失配稳健性。此外,该方法使用权值直接估计声源功率,无需使用信号幅度作为中间量,避免了估计误差的传递。仿真验证了协方差矩阵拟合稳健匹配场声源功率估计方法的环境失配稳健性。     

Design and implementation of a shielded underwater vector sensor for laboratory environments

Underwater acoustic vector sensors, for measuring acoustic intensity, are typically used in open water where electromagnetic interference (EMI) is generally not a contributor to overall background noise. However, vector sensors are also useful in a laboratory setting where EMI can be a limiting factor at low frequencies. An underwater vector sensor is designed and built with specific care for EMI immunity. The sensor, and associated signal processing, is shown to reduce background noise at EMI frequencies by 10-50 dB and 10-20 dB across the entire frequency bandwidth, as compared to an identical unshielded vector sensor.     

频域盲源分离与波束形成结合抑制方向性强干扰方法

针对方向性强干扰严重影响无源声呐弱目标检测的问题,提出了频域盲源分离与波束形成结合的干扰抑制方法:以子带分解的方法实现宽带干扰抑制。对每个子带进行频域盲源分离,并估计出各分离信号的方位,将与给定强干扰方位匹配的分离信号置零,利用估计的解混矩阵和处理后的分离信号重构回阵元域信号并进行波束形成实现目标方位估计。声呐模拟器数据与海试数据验证结果表明,相对于传统零陷常规波束形成与零陷最小方差无失真响应波束形成方法有2 dB以上的增益,约6 dB的背景级降低,证明该方法在抑制方向性强干扰方面是有效的。      

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。     

Robust adaptive acoustic vector sensor beamforming using automated diagonal loading

In this paper, a novel robust adaptive acoustic vector sensor beamformer based on shrinkage is derived. Unlike many existing methods, the proposed method is completely automatic (or so-called user parameter-free), which means, it do not need the choice of user parameters. The proposed diagonal loading algorithms use shrinkage-based covariance matrix estimates, instead of the conventional sample covariance matrix, in the standard Capon acoustic vector sensor beamforming formulation. The numerical results show that our method is robust against errors on the steering vector and small sample sizes, and meanwhile gives high output signal to interference plus noise ratio (SINR).     

相干噪声快速去除算法及其在声源定位中的应用

针对相干噪声干扰声源辨识问题,将强跟踪滤波器理论与阵列-信号采集模型相结合,发展了一种快速估计相位变化的算法。算法引入多重次优渐消因子,能够进一步提取相位残差中的有用信息,使输出残差序列处处正交,且该因子能根据噪声相位差变化自动调节。通过仿真对连续相位突变进行跟踪表明,在参数失配条件下该算法实现了相位差的准确估计,且其性能在宽频范围具有稳定性。通过音箱实验给出了宽频范围内的成像结果,与已有算法对比表明,该算法不仅能够实时消除噪声干扰并可将收敛速度提高一倍以上。本研究实现了对随机变化相位的准确估计,提升了传声器阵列在相干噪声干扰下的声源实时定位能力。      

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.     

On array design for matched-field processing

Conventional plane-wave beamforming array design guidelines are motivated by the desire to obtain particular beampattern characteristics, such as main lobe width and side lobe levels. These design guidelines are appropriate for arrays employed for beamforming, where a plane-wave signal model is utilized to derive both the array design parameters and the beamforming algorithm. However, matched-field processing utilizes full-field acoustic propagation models to exploit the complexities of ocean acoustic propagation. As a result, there may be more appropriate design guidelines for arrays employed for matched-field processing. In this paper, general guidelines for matched-field processing array design utilizing a normal mode propagation model are proposed. Various line array configurations are evaluated with respect to source localization performance, and the results suggest that arrays designed for matched-field processing should provide a unique representation of each propagating mode along the extent of the array. Further, the empirical analyses support the guidelines suggested by the theoretical analyses and show that arrays which are far from meeting conventional beamforming array design requirements may be more than sufficient for matched-field processing.     

基于实孔径成像的水下高速小目标末弹道 测量方法

在没有合作声信标和水下弹道测量系统配合的条件下,传统的基线定位法难以测量水下高速小目标末弹道。文中提出了一种测量高速小目标末弹道的方法,该方法通过在靶标上安装实孔径声学成像系统,发射双曲调频信号保持系统在目标回波多普勒偏移量较大时的输出幅值稳定,并采用频域宽带信号处理技术修正多普勒偏移造成的目标方位测量误差和抑制混响干扰,经过湖上试验,系统获取了较清晰的声学图像,准确分辨出目标位置,能够较精确地测量高速小目标末弹道。     

A fast signal subspace approach for the determination of absolute levels from phased microphone array measurements

Phased microphone arrays are used in a variety of applications for the estimation of acoustic source location and spectra. The popular conventional delay-and-sum beamforming methods used with such arrays suffer from inaccurate estimations of absolute source levels and in some cases also from low resolution. Deconvolution approaches such as DAMAS have better performance, but require high computational effort. A fast beamforming method is proposed that can be used in conjunction with a phased microphone array in applications with focus on the correct quantitative estimation of acoustic source spectra. This method bases on an eigenvalue decomposition of the cross spectral matrix of microphone signals and uses the eigenvalues from the signal subspace to estimate absolute source levels. The theoretical basis of the method is discussed together with an assessment of the quality of the estimation. Experimental tests using a loudspeaker setup and an airfoil trailing edge noise setup in an aeroacoustic wind tunnel show that the proposed method is robust and leads to reliable quantitative results.     

瞬时混合盲源分离和最优波束形成的关系研究

最优波束形成和盲源分离是近几十年迅速发展起来的两种重要阵列信号处理方法,在瞬时混合情况下它们具有相似的信号模型,所以本文研究了二者之间的关系。指出,当不存在噪声时,多数盲源分离算法构造的是最优波束形成;当存在噪声时,可以利用盲源分离算法估计的信号导向向量设计最优波束形成。计算机仿真实验验证了这一结论。     

机车驾驶室中自适应有源降噪系统的研究

根据机车驾驶室中噪声特征的分析结果，提出了采用FIR滤波器的自适应有源降噪(ANNC)系统。为消除机车驾驶室中严重的背景噪声干扰影响，应用伪随机相关法对驾驶室中的噪声脉冲响应进行测量。通过数字仿真研究，对基于IMS算法的ANNC系统的关键参数进行了寻优。最后，在实际声场中建立了实时双通道ANNC系统并进行了相关的实验验证。仿真与实验的结果证明了本文提出的AANC系统的可行性和有效性。