总体最小二乘算法模波束形成方法研究

研究了模波束形成处理算法,并在此基础上提出了一种总体最小二乘算法模波束形成技术。该方法利用总体最小二乘算法修正了从垂直接收基阵数据中提取出的简正波模态函数信息,准确估计出各阶简正波模态系数,提高了对目标检测和定位的性能。针对典型的浅海波导环境,进行了计算机仿真实验,结果表明:在低频远程目标条件下,该方法与常规最小二乘算法模波束形成相比,估计出的简正波模态系数更精确,具有旁瓣低,分辨率高,定位性能好的优点。      

基于简正波分解的不同阵列匹配场定位性能分析

针对利用不同阵列对浅海环境中水下目标的定位问题,基于简正波分解方法,对组合阵的目标声源定位性能进行了研究,着力解决在实际实验环境下定位性能不够高的问题,并降低实验设备布放难度.在浅海环境下,基于匹配场理论的声接收阵可实现目标的定位,但定位性能受阵形、阵元数目等影响.通过研究不同声接收阵的简正波分解矩阵,可以有效辨别不同阵形定位性能的优劣.仿真实验表明,当某一子阵简正波分解效果较差时,会降低组合阵的定位性能.基于实际实验的需求,在对短垂直阵和组合阵性能的研究中发现,由于水平阵对接收声场的定位模糊度函数中的旁瓣有抑制效果,从而造成模糊度函数表面上旁瓣较低,定位目标的主旁瓣比有所提升的现象.仿真实验表明,不同组合阵形的定位准确度均在90%以上,基于实际应用的考虑,组合阵无疑是对定位性能和实验复杂度的折中选择.     

Matched localization of a horizontal array in shallow sea

I.IntroductionInsha1lowsea,passivesource1ocalizationisadifficu1t,yctinterestingprob1emthathasre-ceivcdagrcatdca1ofattcnti0ninthelastfCwycars.l'-'1Theconventiona1sourccloca1izationistOmatchthercceivcdacousticdatawiththesoundficldprcdictcdbythepropagationmodcl.Thistechniqueiscallcdmatchcd-ficldproccssing(MFP).Itiscommonlyacceptcdthatinshal-low-watercnvironmcnLssoundficldcanbcwclldcscribcdbyanormal-modemodel.Accord-ingtothismodcl,thcacousticprcssurecanbecxprcsscdasalincarcombinationofthenorma…     

Regularized matched-mode processing for source localization

This paper develops a new approach to matched-mode processing (MMP) for ocean acoustic source localization. MMP consists of decomposing far-field acoustic data measured at an array of sensors to obtain the excitations of the propagating modes, then matching these with modeled replica excitations computed for a grid of possible source locations. However, modal decomposition can be ill-posed and unstable if the sensor array does not provide an adequate spatial sampling of the acoustic field (i.e., the problem is underdetermined). For such cases, standard decomposition methods yield minimum-norm solutions that are biased towards zero. Although these methods provide a mathematical solution (i.e., a stable solution that fits the data), they may not represent the most physically meaningful solution. The new approach of regularized matched-mode processing (RMMP) carries out an independent modal decomposition prior to comparison with the replica excitations for each grid point, using the replica itself as the a priori estimate in a regularized inversion. For grid points at or near the source location, this should provide a more physically meaningful decomposition; at other points, the procedure provides a stable inversion. In this paper, RMMP is compared to standard MMP and matched-field processing for a series of realistic synthetic test cases, including a variety of noise levels and sensor array configurations, as well as the effects of environmental mismatch.     

失配情况下匹配模处理的仿真研究*

匹配场处理是一种水声学和物理学相结合的信号处理技术,其在水下目标定位方面的高精度特点使得该方法受到广泛关注。匹配模处理是工作在模态空间的匹配处理方法。相对于匹配场处理方法,匹配模处理方法只处理声场中有关声源位置信息的数据(然而匹配场处理方法使用了全部声场数据),这样就可以减小环境失配对定位的影响。本文研究了在环境发生失配时,通过选取受失配影响较小的模态组合,得出的定位结果更加精确。     

拖曳阵被动合成孔径目标深度稳健估计

使用水下无人平台作为载体的拖曳阵进行被动目标深度估计具有灵活性高和隐蔽性好的优点,针对实际应用中存在的平台自噪声和阵列瞬时随机加速度扰动问题,提出了一种稳健的目标深度估计方法。该方法分为三个步骤,首先对阵元接收信号进行自适应噪声抵消和相位抖动滤波,然后对声压进行距离积分实现简正波模态估计,最后计算模态匹配度,最大值对应的深度为目标深度估计结果。仿真表明在干扰背景下该方法的目标深度估计稳健性优于传统方法,声源频率、合成孔径距离和信干比决定了目标深度估计误差。利用实验数据验证了该方法对水下低频线谱声源的深度估计能力。     

Fast implementation of sparse iterative covariance-based estimation for source localization

Fast implementations of the sparse iterative covariance-based estimation (SPICE) algorithm are presented for source localization with a uniform linear array (ULA). SPICE is a robust, user parameter-free, high-resolution, iterative, and globally convergent estimation algorithm for array processing. SPICE offers superior resolution and lower sidelobe levels for source localization compared to the conventional delay-and-sum beamforming method; however, a traditional SPICE implementation has a higher computational complexity (which is exacerbated in higher dimensional data). It is shown that the computational complexity of the SPICE algorithm can be mitigated by exploiting the Toeplitz structure of the array output covariance matrix using Gohberg-Semencul factorization. The SPICE algorithm is also extended to the acoustic vector-sensor ULA scenario with a specific nonuniform white noise assumption, and the fast implementation is developed based on the block Toeplitz properties of the array output covariance matrix. Finally, numerical simulations illustrate the computational gains of the proposed methods.     

基于水平合成阵列的简正波波数估计

针对浅水声波导中简正波模数估计的孔径约束问题,提出了一种基于运动合成孔径高分辨谱分解的简正波波数估计方法。该方法先利用短水平阵运动合成大孔径虚拟阵列,再通过合成阵列进行高分辨谱分解来进行简正波波数估计。数值仿真结果和海试数据测试表明,孔径运动合成技术的应用,解决了水平阵进行简正波模数估计时孔径不足的问题;拖曳阵在远离目标水平运动的过程中,做垂直向机动可以提高简正波模数估计精度。      

基于垂直阵模态分解的低频水声信号盲解卷处理研究

研究了基于人工时反处理的水声信号盲解卷方法,并在此基础上提出了一种基于简正波模态分解的低频水声信号的盲解卷处理方法。该方法适用于浅海波导中垂直阵接收的远程低频水声信号的盲解卷处理。该方法首先从浅海中垂直阵接收的信号中提取(估计)出波导中传播的简正波模态函数信息,然后,根据估计的模态函数信息通过模态滤波来实现水声信道盲解卷处理。针对典型的浅海波导环境,进行了计算机仿真试验,结果表明:(1)远程低频条件下,模态分解方法可以从垂直阵接收的信号中提取出波导中有效传播的模态函数信息,因此这种方法解决了目前人工时反处理方法需要准确的模态函数先验信息的问题;(2)在一定带宽条件下,接收信号信噪比较低时,本文给出的这种基于模态滤波的盲解卷方法比人工时反处理具有更好的解卷性能。     

利用宽带引导声源重构拷贝声场的目标声源定位

为了避开传统的匹配场目标定位技术对环境先验知识的依赖性,提出了在均匀浅海环境中只知道少量环境参数的情况下,利用垂直接收阵和不同距离上的两枚宽带引导声源重构声场对目标声源进行定位的一种方法。这种方法主要基于简正波估计和声场重构两种关键技术,同时省去了匹配场定位技术中大量的拷贝声场计算。数值仿真主要采用线性Bartlett匹配处理器分析了目标定位效果,在信噪比高于10 d B的情况下,定位效果良好。     

Bayesian localization in an uncertain ocean environment

In order to improve the ability to localize a source in an uncertain acoustic environment,a Bayesian approach,referred to here as Bayesian localization is used by including the environment in the parameter search space.Genetic algorithms are used for the parameter optimization.This method integrates the a posterior probability density(PPD) over environmental parameters to obtain a sequence of marginal probability distributions over source range and depth,from which the most-probable source location and localization uncertainties can be extracted.Considering that the seabed density and attenuation are less sensitive to the objective function of matched field processing,we utilize the empirical relationship to invert those parameters indirectly.The broadband signals recorded by a vertical line array in a Yellow Sea experiment in 2000 are processed and analyzed.It was found that,the Bayesian localization method that incorporates the environmental variability into the processor,made it robust to the uncertainty in the ocean environment.In addition,using the empirical relationship could enhance the localization accuracy.     

The influence of environmental conditions on estimation of source distance and height using a single vertical array

The performance of microphone arrays outdoors is influenced by the environmental conditions. Numerical simulations indicate that, while horizontal arrays are hardly affected, direction-of-arrival (DOA) estimation with vertical arrays becomes biased in presence of ground reflections and sound speed gradients. Turbulence leads to a huge variability in the estimates by reducing the ground effect. Ground effect can be exploited by combining classical source localization with an appropriate propagation model (ground effect inversion). Not only does this allow the source elevation and range to be determined with a single vertical array but also it allows separation of sources which can no longer be distinguished by far field localization methods. Furthermore, simulations provide detail of the achievable spatial resolution depending on frequency range, array size and localization algorithm and show a clear advantage of broadband processing. Outdoor measurements with one or two sources confirm the results of the numerical simulations.     

不确知海洋环境下的贝叶斯声源定位法

为了提高不确知海洋环境下的声源定位性能,贝叶斯声源定位法将环境参数与声源位置同时反演。该方法利用遗传算法在参数空间中寻优,将后验概率密度在环境参数起伏变化范围内积分,得到声源距离和深度的边缘概率分布,从中求得声源位置的最优值,并进行定位结果的不确定性分析。考虑到海底密度和衰减系数对匹配场处理代价函数的敏感性较弱,利用海底参数之间的经验关系实现这两个参数的间接反演。处理并分析了2000年的一次黄海声传播实验数据,研究表明,贝叶斯声源定位法对环境失配有较好的宽容性。采用经验公式可减少待反演参量维数,进一步提高定位的精度。      

传感器网络基于特征值分解的信号被动定位技术

基于传感器网络的信号被动定位技术在电磁学、声学、声呐系统以及传热学等领域具有广泛的应用前景,当传感器网络节点所接收噪声强度不同或传输信道存在阴影衰落效应时,给出了目标信号到达距离比定位关联度量的估计方法与基于信号到达距离比的被动定位算法.将特征值分解技术引入到信号到达距离比定位关联度量估计中,通过接收信号协方差矩阵特征值分解技术估计各节点所接收噪声强度,并通过网络参考节点轮换与特征值分解方法消除阴影衰落效应所引入的定位误差,最后给出该算法的最小二乘定位解.该方法可较好的消除由于节点接收噪声强度不同以及阴影衰落效应等因素所带来的定位性能恶化.     

格林函数解卷积处理的阵不变量浅海无源定位

水下声源无源定位是声呐技术重要的研究方向.针对水下声源无源定位问题,本文提出了一种基于格林函数解卷积处理的阵不变量无源定位方法.该方法使用盲解卷积算法从水平阵接收信号中提取时域格林函数,然后采用空域解卷积方法处理得到的时域格林函数,获得波束时间偏移,从波束时间偏移中计算得到阵不变量,解算目标距离,从而实现声源定位.区别...     

Localization of distinct reflections in rooms using spherical microphone array eigenbeam processing

This paper presents an experimental and comparative study of several spherical microphone array eigenbeam (EB) processing techniques for localization of early reflections in room acoustic environments, which is a relevant research topic in both audio signal processing and room acoustics. This paper focuses on steered beamformer-based and subspace-based localization techniques implemented in the spherical EB domain, including the plane-wave decomposition, eigenbeam delay and sum, eigenbeam minimum variance distortionless response, eigenbeam multiple signal classification (EB-MUSIC), and eigenbeam estimation of signal parameters via rotational invariance techniques (EB-ESPRIT) methods. The directions of arrival of the original sound source and the associated reflection signals in acoustic environments are estimated from acoustic maps of the rooms, which are obtained using a spherical microphone array. The EB-domain-based frequency smoothing and white noise gain control techniques are derived and employed to improve the performance and robustness of reflection localization. The applicability of the presented methods in practice is confirmed by experiments carried out in real rooms.     

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.     

不同频段下利用虚拟接收方法的声源测距性能分析

考虑到传统的匹配场处理定位需要复杂的匹配声场计算,并对环境参数和声场模型有很高的依赖,为了克服这种缺点,采用虚拟接收方法对声源进行测距。首先对垂直阵接收到的引导声源和目标声源的信号进行相关处理,得到虚拟接收声场并估计虚拟接收声场干涉条纹的斜率,结合波导不变特征量β对目标声源进行测距。通过数值仿真和2004年南海实验数据处理,讨论了浅海斜坡海域环境中不同频段下利用虚拟接收方法对宽带声源测距的性能。随着频率升高,需要展宽频带以获得完整的干涉条纹和良好的测距结果。在实验数据处理中,选取频段较高的信号时,由于阵列间距偏大不能保证采样的简正波模式的正交归一特性,不能获得正确的测距结果。      

Extraction of acoustic normal mode depth functions using vertical line array data

A method for extracting the normal modes of acoustic propagation in the shallow ocean from sound recorded on a vertical line array (VLA) of hydrophones as a source travels nearby is presented. The mode extraction is accomplished by performing a singular value decomposition (SVD) of individual frequency components of the signal's temporally averaged, spatial cross-spectral density matrix. The SVD produces a matrix containing a mutually orthogonal set of basis functions, which are proportional to the depth-dependent normal modes, and a diagonal matrix containing the singular values, which are proportional to the modal source excitations and mode eigenvalues. The conditions under which the method is expected to work are found to be (1) sufficient depth sampling of the propagating modes by the VLA receivers; (2) sufficient source-VLA range sampling, and (3) sufficient range interval traversed by the source. The mode extraction method is applied to data from the Area Characterization Test II, conducted in September 1993 in the Hudson Canyon Area off the New Jersey coast. Modes are successfully extracted from cw tones recorded while (1) the source traveled along a range-independent track with constant bathymetry and (2) the source traveled up-slope with gradual changes in bathymetry. In addition, modes are successfully extracted at multiple frequencies from ambient noise.     

Source-Space Compressive Matched Field Processing for Source Localization

Source localization by matched-field processing(MFP) can be accelerated by building a database of Green's functions which however requires a bulk-storage memory.According to the sparsity of the source locations in the search grids of MFP,compressed sensing inspires an approach to reduce the database by introducing a sensing matrix to compress the database.Compressed sensing is further used to estimate the source locations with higher resolution by solving the l_1-norm optimization problem of the compressed Green's function and the data received by a vertical/horizontal line array.The method is validated by simulation and is verified with the experimental data.