基于压缩拷贝场向量的空域滤波器设计

近几十年来,匹配场处理技术得到了广泛深入的研究,并针对实际应用提出了一系列的具体处理算法.当感兴趣的水下目标信号被水面强干扰信号掩蔽时,对水下目标的匹配场处理定位性能显著下降.现有的广义空域滤波器可以抑制水面强干扰,但计算速度较慢并且内存消耗较大.提出了一种基于压缩拷贝场算法的空域滤波器设计方案,并通过非相干叠加处理宽带问题.相对于现有的空域滤波器,当接收阵元数N大于波导中有效简正波号数Q时,该滤波器可以大幅度缩减计算时间、节约运行内存,并且保持了对水面强干扰的抑制性能.针对近岸浅海环境进行了仿真计算,并给出了一些近岸浅海海域试验数据处理结果,验证了该空域滤波器的性能和对计算速度的提升.结果表明,应用基于压缩拷贝向量的矩阵滤波器对强干扰下的弱目标进行宽带非相干匹配场定位,可实现水下目标的有效区分.     

Null-broadening in a waveguide

Null-broadening, introduced in plane wave beamforming, is extended to an ocean waveguide in the context of matched field processing. The method is based on the minimum variance processor with white noise constraint and the distribution of fictitious sources using the theory of waveguide invariants. The proposed method is demonstrated in simulation as well as with data collected during the SWellEx-96 experiment. As another application, it is shown that the width of a null can be controlled in an adaptive time reversal mirror with a source-receive array.     

A Bayesian approach to matched field processing in uncertain ocean environments

An approach of Bayesian Matched Field Processing （MFP） was discussed in the uncertain ocean environment. In this approach, uncertainty knowledge is modeled and spatial and temporal data received by the array are fully used. Therefore, a mechanism for MFP is found, which well combines model-based and data-driven methods of uncertain field processing. By theoretical derivation, simulation analysis and the validation of the experimental array data at sea, we find that （1） the basic components of Bayesian matched field processors are the cor- responding sets of Bartlett matched field processor, MVDR （minimum variance distortionless response） matched field processor, etc.; （2） Bayesian MVDR/Bartlett MFP are the weighted sum of the MVDR/Bartlett MFP, where the weighted coefficients are the values of the a posteriori probability; （3） with the uncertain ocean environment, Bayesian MFP can more correctly locate the source than MVDR MFP or Bartlett MFP; （4） Bayesian MFP can better suppress sidelobes of the ambiguity surfaces.     

Matched-field replica model optimization and bottom property inversion in shallow water

Matched-field replica models based on an inaccurate knowledge of geoacoustic parameters such as bottom attenuation, shear, and interfacial sound-speed discontinuities, can predict an incorrect number of propagating modes for a shallow-water channel. The resulting degradation in the matched-field ambiguity surface can be substantially reduced by obtaining optimal replica models via modal-sum-limit optimization or bottom-property inversion. The use of these techniques for multi-tone (70, 95, 145, and 195 Hz) source-tow data recorded near San Diego during the first Shallow-Water Evaluation Cell Experiment (SWellEX-1) significantly increased matched-field correlation levels and improved source localization relative to results obtained with a previous nonoptimized model. The predicted number of propagating modes was also reduced substantially. The inversion for bottom properties (attenuation, interfacial sound-speed discontinuities, no shear) provided sediment attenuation estimates which agree well with Hamilton's models and were an order-of-magnitude greater than that used in the nonoptimized model, which accounts for the reduction in the number of modes. A simulated modal decomposition using the inverted optimal replica model verifies the number of modes predicted by the modal-sum-limit optimization.     

一种水平变化波导中匹配场定位的虚拟时反实现方法

在水平变化波导中,匹配场被动定位的计算量非常大,严重阻碍了其工程应用.本文提出了一种水平变化波导中匹配场定位的虚拟时反实现方法,其抛物方程模型计算网格总数远小于匹配场处理,从而大大减小计算代价.与匹配场处理不同,虚拟时反实现方法是一个利用介质互易性和叠加性的后向传输过程.通过在各水听器位置放置虚拟声源,并在搜索区域产生相应的模糊平面,对各个模糊平面进行相应加权求和,获得的定位模糊平面.利用地中海浅海实验数据验证了虚拟时反实现方法的快速性能.     

Medical ultrasound imaging method combining minimum variance beamforming and general coherence factor

In medical ultrasound imaging field,in order to obtain high resolution and correct the phase errors induced by the velocity in-homogeneity of the tissue,a high-resolution medical ultrasound imaging method combining minimum variance beamforming and general coherence factor was presented.First,the data from the elements is delayed for focusing;then the multi-channel data is used for minimum variance beamforming;at the same time,the data is transformed from array space to beam space to calculate the general coherence factor;in the end, the general coherence factor is used to weight the results of minimum variance beamforming. The medical images are gotten by the imaging system.Experiments based on point object and anechoic cyst object are used to verify the proposed method.The results show the proposed method in the aspects of resolution,contrast and robustness is better than minimum variance beamforming and conventional beamforming.     

The array invariant

A method is derived for instantaneous source-range estimation in a horizontally stratified ocean waveguide from passive beam-time intensity data obtained after conventional plane-wave beamforming of acoustic array measurements. The method has advantages over existing source localization methods, such as matched field processing or the waveguide invariant. First, no knowledge of the environment is required except that the received field should not be dominated by purely waterborne propagation. Second, range can be estimated in real time with little computational effort beyond plane-wave beamforming. Third, array gain is fully exploited. The method is applied to data from the Main Acoustic Clutter Experiment of 2003 for source ranges between 1 to 8 km, where it is shown that simple, accurate, and computationally efficient source range estimates can be made.     

超声成像中基于特征空间的前后向最小方差波束形成

针对最小方差(MV)波束形成在算法稳健性和超声成像对比度方面存在的缺点,提出一种将特征空间法和前后向空间平滑法融合用于最小方差波束形成的超声成像方法。首先用前后向空间平滑取代传统的前向空间平滑,得到更精确的协方差矩阵;然后计算最优加权向量,并将该向量投影到由协方差矩阵特征空间构造的信号子空间中;最后利用投影所获得的向量与阵元数据进行运算得到成像回波数据。为了验证算法的有效性,对医学成像中常用的点目标和斑目标进行了成像实验。仿真结果表明:所提出的方法不依赖于对角加载参数的选取,在保持MV算法高分辨率的同时,还有效提高图像的对比度和算法的稳健性。      

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。     

利用拖船辐射噪声的深海声学参数近场匹配场反演方法

针对深海声学参数难以通过远距离合作声源反演获取的问题,提出了利用拖船低频噪声近场匹配场反演方法。首先,利用聚焦波束形成计算拖曳阵接收拖船噪声的方向性,获得传播路径特征;然后,构建多参数反演模型,由波数积分声传播模型计算拷贝场,采用遗传算法对多频匹配场目标函数进行反演。同时,采用蒙特卡罗方法分析参数后验概率密度。仿真与试验结果表明:深海环境中拖曳阵接收拖船噪声主要来自海底反射路径,利用该特性反演得到海水深度、噪声源距离、阵列深度、沉积层厚度等参数,多频联合反演可以提高沉积层厚度等参数反演准确性。宽带匹配场处理表明,利用反演最优参数模型能准确给出拖船噪声源的空间位置。      

Ocean bottom profiling with ambient noise: a model for the passive fathometer

A model is presented for the complete passive fathometer response to ocean surface noise, interfering discrete noise sources, and locally uncorrelated noise in an ideal waveguide. The leading order term of the ocean surface noise contribution produces the cross-correlation of vertical multipaths and yields the depth of sub-bottom reflectors. Discrete noise incident on the array via multipaths give multiple peaks in the fathometer response. These peaks may obscure the sub-bottom reflections but can be attenuated with use of minimum variance distortionless response (MVDR) steering vectors. The seabed critical angle introduces discontinuities in the spatial distribution of distant surface noise and may introduce spurious peaks in the passive fathometer response. These peaks can be attenuated by beamforming within a bandwidth limited by the array geometry and critical angle.     

特征空间和符号相干系数融合的最小方差超声波束形成

为了提高医学超声成像的空间分辨率,提出一种融合了特征空间最小方差与符号相干系数的波束形成方法。首先利用最小方差法计算回波数据的协方差矩阵和加权向量;然后对协方差矩阵进行特征分解得到信号子空间,并将加权向量投影到该空间上;最后计算符号相干系数,用于优化特征空间法得到的回波信号,最终获得超声成像数据。为验证算法的有效性,对医学超声成像中常用的点目标、斑目标进行仿真,对点目标仿体和人体颈动脉组织进行超声成像实验。结果表明:所提出的方法在分辨率、对比度以及稳健性等方面都优于传统的延时叠加算法、最小方差算法、特征空间最小方差法以及特征空间与相干系数融合的方法。      

A method of improving overall resolution in ultrasonic array imaging using spatio-temporal deconvolution

In this paper a beamforming method for ultrasonic array imaging is presented that performs both spatial and temporal deconvolution based on a minimum mean square error (MMSE) criteria. The presented MMSE receive mode beamformer performs a regularized inversion of the propagation operator for the ultrasonic array system at hand. The MMSE beamformer accounts for the transmit and receive processes, defined in terms of finite array element sizes, transmit focusing laws and electrical transducer characteristics. The MMSE beamformer is compared to the traditional delay-and-sum (DAS) beamformer with respect to both resolution and signal-to-noise ratio. The two algorithms are compared using both simulated and measured data. The simulated data was obtained using ultrasonic field simulations and the measured data was acquired using a linear phased array imaging wire targets in water. The results show that the MMSE beamformer has superior temporal and lateral resolution compared to DAS. It is also shown that the MMSE beamformer can be expressed as a filter bank, which enables parallel processing at high frame rates.     

Improvement in matched field processing using the CLEAN algorithm

Adaptive matched field processing such as the minimum variance distortionless processor (MV) provides excellent sidelobe (or ambiguity) suppression capability in source localization given a perfect knowledge of the ocean environment. Unfortunately, this processing is very sensitive to sources of mismatch and robust adaptive algorithms are then employed such as a white noise constraint (WNC) often at the expense of insufficient sidelobe control. The CLEAN algorithm was introduced in radio astronomy [Astron. Astrophys. Suppl. Ser. 15, 417-426 (1974)] to produce a high quality image of the sky by reducing sidelobe-induced artifacts. In this paper, the CLEAN concept is extended to matched field processing. Numerical simulations and experimental data demonstrate that matched field processing combined with the CLEAN algorithm can improve performance, especially when a weak source is masked by sidelobes from a much stronger source.     

Beam intensity striations and applications

The single-element spectrogram for a continuous broadband signal, plotted as a function of range, has been shown to exhibit striated bands of intensity maxima and minima. The slope of the striations is an invariant of the modal interference and is described by a waveguide invariant parameter "beta." The striation pattern is analyzed and modeled in this paper for the beam outputs of a horizontal line array obtained by conventional beamforming. Array beamforming makes it possible to measure the waveguide invariant parameter for weak signals due to the enhancement of signal levels by the array gain over that of a single element. It is shown that the signal beam spectrogram as a function of range exhibits the same striation pattern as that (predicted) for a single element. Specifically, for a broadside signal, the beam striation is identical to that of a single-element plus a constant signal gain. For a nonbroadside target, the signal beam intensity will be modified by a frequency-bearing dependent signal gain due to the signal spread over multiple beams, nevertheless the beam spectrogram retains the same striation pattern (slope) as for a single element. The sidelobe beams (outside the canonical cones containing the signal arrivals) exhibit an entirely different striation pattern as a function of frequency and range. For array processing, it is shown that a fast range-rate, close range target and a distant, slow range-rate interference source will have a different striation pattern (slope) in the corresponding beam spectrograms as a function of time, assuming no prior knowledge of the source ranges. The difference in the striations between the beam spectrograms can be used in array processing to suppress the interference contribution. A 5-7 dB interference suppression is demonstrated using simulated data.     

A waveguide invariant adaptive matched filter for active sonar target depth classification

This paper addresses depth discrimination of a water column target from bottom clutter discretes in wideband active sonar. To facilitate classification, the waveguide invariant property is used to derive multiple snapshots by uniformly sub-sampling the short-time Fourier transform (STFT) coefficients of a single ping of wideband active sonar data. The sub-sampled target snapshots are used to define a waveguide invariant spectral density matrix (WI-SDM), which allows the application of adaptive matched-filtering based approaches for target depth classification. Depth classification is achieved using a waveguide invariant minimum variance filter (WI-MVF) which matches the observed WI-SDM to depth-dependent signal replica vectors generated from a normal mode model. Robustness to environmental mismatch is achieved by adding environmental perturbation constraints (EPC) derived from signal covariance matrices averaged over the uncertain channel parameters. Simulation and real data results from the SCARAB98 and CLUTTER09 experiments in the Mediterranean Sea are presented to illustrate the approach. Receiver operating characteristics (ROC) for robust waveguide invariant depth classification approaches are presented which illustrate performance under uncertain environmental conditions.     

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.     

Target detection and localization in shallow water: an experimental demonstration of the acoustic barrier problem at the laboratory scale

This study demonstrates experimentally at the laboratory scale the detection and localization of a wavelength-sized target in a shallow ultrasonic waveguide between two source-receiver arrays at 3 MHz. In the framework of the acoustic barrier problem, at the 1/1000 scale, the waveguide represents a 1.1-km-long, 52-m-deep ocean acoustic channel in the kilohertz frequency range. The two coplanar arrays record in the time-domain the transfer matrix of the waveguide between each pair of source-receiver transducers. Invoking the reciprocity principle, a time-domain double-beamforming algorithm is simultaneously performed on the source and receiver arrays. This array processing projects the multireverberated acoustic echoes into an equivalent set of eigenrays, which are defined by their launch and arrival angles. Comparison is made between the intensity of each eigenray without and with a target for detection in the waveguide. Localization is performed through tomography inversion of the acoustic impedance of the target, using all of the eigenrays extracted from double beamforming. The use of the diffraction-based sensitivity kernel for each eigenray provides both the localization and the signature of the target. Experimental results are shown in the presence of surface waves, and methodological issues are discussed for detection and localization.     

MASS-RAB: Robust adaptive beamforming for general-rank signal models via matched spatial spectrum processing

The wavefront of acoustic signal suffers from fast fluctuation after a long distance propagation in a random and inhomogeneous ocean channel, which makes the rank of the covariance matrix for the desired signal (signal of interest) remarkably higher than one. Consequently, the assumption of rank-one point signal model for existing adaptive beamforming algorithms is no longer suitable. In this paper, a matched spatial spectrum processing based robust adaptive beamforming (MASS-RAB) algorithm is presented for general-rank signal models. First, the interference-plus-noise covariance matrix and the desired signal covariance matrix are reconstructed using the matched spatial spectrum processing method. Second, the weight vector is directly calculated using these reconstructed covariance matrices for the minimum variance distortionless response (MVDR) algorithm, which is developed for the general-rank signal models. Due to covariance matrix reconstruction, the MASS-RAB algorithm is more robust than those methods relying on the sample covariance matrix. The cases of the rank-one point signal model and the full-rank non-point signal model are considered by several numerical examples. Experimental results have demonstrated the superiority of the proposed MASS-RAB method.     

Geoacoustic inversion of short range source data using a plane wave reflection coefficient approach

Acoustic time series data were collected in a shallow, hard bottom lake environment located in central Texas using both short range (2 m) implosive data, obtained with the source and a single hydrophone located near mid-depth in the waveguide, along with longer range implosive and explosive data from a near surface source to a bottom mounted hydrophone. Matched field inversions using simulated annealing were performed with a ray trace plus complex plane wave reflection coefficient forward propagation model that was validated in previous work. Isolating bottom interacting paths to perform the inversions is shown to be essential to reduce parameter uncertainties in the hard bottom environment and enables a systematic approach to the inversions which establishes the number of layers needed to represent the lake environment. Measured transmission loss data from a towed source were compared through a RMS error analysis to modeled transmission loss, constructed with the parameters from inversions of data from several source types, to further establish the validity of the inversion approach for this environment. Geoacoustic parameters obtained by inversions of short range, low frequency impulsive data are used to predict transmission loss at longer ranges and higher frequencies. The range dependence of the global minimum is discussed.