Detection of number of sources and DOA estimation based on the combined information processing of pressure and particle velocity using acoustic vector sensor array

In order to solve the problem of DOA(direction of arrival)estimation of underwater remote targets,a novel subspace-decomposition method based on the cross covariance matrix of the pressure and the particle velocity of acoustic vector sensor arrays(AVSA)was proposed. Whereafter,using spatio-temporal virtual tapped-delay-line,a new eigenvector-based criteria of detection of number of sources and of subspace partition is also presented.The theoretical analysis shows that the new source detection and direction finding method is different from existing AVSA based DOA estimation methods using particle velocity information of acoustic vector sensor(AVS)as an independent array element.It is entirely based on the combined information processing of pressure and particle velocity,has better estimation performance than existing methods in isotropic noise field.Computer simulations with data from lake trials demonstrate,the proposed method is effective and obviously outperforms existing methods in resolution and accuracy in the case of low signal-to-noise ratio(SNR).     

A subspace fitting algorithm of acoustic vector sensor array and corresponding matrix pre-filter design

In order to ease the pass-band response distortion of the matrix pre-filter,a simple approach for designing matrix spatial filter is proposed,which minimizes the sum of the k maximal distortion norm（k is the number of the constraint points）within the pass-band,while constraining the filter response within the stop-band.Considering the costly amount of calculation of the high-resolution methods,an algorithm with small amount of calculation based on matrix pre-filtering and subspace fitting using acoustic vector array（MF-VSSF）is proposed.Through joint processing of signal subspace of both pressure and particle velocity,the pre-filtering matrix and the signal subspace is decreased to M-dimensional（M is the number of array-element）,hence reduces the time-consumption of the matrix pre-filter design and DOA searching.Simulation results show that,the method offers the same performance as MUSIC with pre-filtering,but has much lesser amount of calculation.Moreover,the designed prefilter can efficiently suppress the interference in the stop-band and improve the estimation and resolution performance of successive DOA estimators.     

Geoacoustic Inversion Based on a Vector Hydrophone Array

We propose a geoacoustic inversion scheme employing a vector hydrophone array based on the fact that vector hydrophone can provide more acoustic field information than traditional pressure hydrophones. Firstly, the transmission loss of particle velocities is discussed. Secondly, the sediment sound speed is acquired by a matchedfield processing （MFP） procedure, which is the optimization in combination of the pressure field and vertical particle velocity field. Finally, the bottom attenuation is estimated from the transmission loss difference between the vertical particle velocity and the pressure. The inversion method based on the vector hydrophone array mainly has two advantages： One is that the MFP method based on vector field can decrease the uncertain estimation of the sediment sound speed. The other is that the objective function based on the transmission loss difference has good sensitivity to the sediment attenuation and the inverted sediment attenuation is independent of source level. The validity of the inverted parameters is examined by comparison of the numerical results with the experimental data.     

Robust algorithm of direction of arrival estimation for coherent wideband sources in unknown correlated noise fields

A robust algorithm of direction of arrival (DOA) estimation for coherent wideband sources in unknown correlated noise fields was investigated. The noise is usually unknown and correlated among sensors in practical applications, especially for arrays with comparatively small apertures. The spatially correlated noise incurs an increase in focusing error and a severe degradation in the DOA estimation, and therefore a method of focusing transformation based on differentiating covariance matrix was proposed to eliminate noise, hence reduce the focusing error. The simulation and experimental results demonstrate the effectiveness of the proposed method.     

Two-dimensional direction finding for low altitude target based on intensity measurement using an acoustic vector-sensor

A method of two-dimensional direction of arrival (DOA) estimation for low altitude target, which is based on intensity measurement using a three-dimensional differential pressure acoustic vector-sensor, is presented. With the perfect characteristics of acoustic vector sensor in the low frequency band, accurate DOA estimation is achieved under small array size. The validity of the proposed method was assessed by experiments on the noise signals radiated by a helicopter. The influence of acoustic sensor size, integral time and signal to noise ratio to the accuracy of DOA estimation were investigated, respectively. The performance comparisons demonstrated that it outperformed the traditional time-delay measurement based method for a small acoustic array.     

A Numerical Method for Modeling the Effects of Irregular Shape on Interconnect Resistance

When clock frequencies exceed gigahertz, the skin depth in analog and digital circuits greatly decreases. The irregular shape of the cross section of the interconnect plays an increasingly important role in interconnect parasitic extraction. However, existing methods only focus on the rough surface of the interconnect, while ignoring other irregular shapes, such as the trapezoidal cross section. In this work, a new simulation method is proposed for irregular interconnects, which is applicable to arbitrary irregular shapes and to a wide range of frequencies. The method involves generating a mesh information file firstly, and then extracting the frequency-dependent resistance based on a numerical solution of scalar wave modeling by using the method of moments. The singularity extraction method is used to calculate the self-inductors. The data from experiments verify the accuracy of our proposed method.     

Fourth-order cumulant multiple matrix reconstruction to estimate direction of arrival for coherent sound source under low signal-to-noise ratio

To address the problem of energy diffusion in the subspace of coherent sources and the difficulty of estimating the direction of arrival(DOA) with an under-ranked covariance matrix, an estimation method using a higher-order matrix transformation, i.e. the fourth-order cumulant multiple matrix reconstruction(FOC-MMR), is proposed. Firstly, short-time Fourier transform is performed on the array sound pressure data in frames. Then, the singular value decomposition of the fourth-order cumulant-expan...     

An approximate method to acoustic radiation problems: element radiation superposition method

An approximate method is brought forward to predict the acoustic pressure based on the surface velocity. It is named Element Radiation Superposition Method （ERSM）. The study finds that each element in Acoustic Transfer Vector （ATV） equals the acoustic pressure radiated by the corresponding surface element vibrating in unit velocity and other surface elements keep still, that is the acoustic pressure radiated by the corresponding baffled piston vibrating in unit velocity. So, it utilizes the acoustic pressure radiated by a baffled piston to establish the transfer relationship between the surface velocity and the acoustic pressure. The total acoustic pressure is obtained through summing up the products of the surface velocity and the transfer quantity. It adopts the regular baffle to fit the actual baffle in order to calculate the acoustic pressure radiated by the baffled piston. This approximate method has larger advantage in calculating speed and memory space than Boundary Element Method. Numerical simulations show that this approximate method is reasonable and feasible.     

Direction of arrival estimation using array model in time-frequency domain

Time-frequency analysis is combined with array processing to develop a direction of arrival (DOA) estimation method. The array data model is constructed in time-frequency domain by cross time-frequency distribution between the output of a reference sensor and those of two symmetric sub-arrays. Accordingly a subspace method is presented based on the average of two sub-arrays‘ time-frequency data vector model instead of the conventional array model, to estimate DOAs of multiple signals. Because the array data is processed both in spatial domain and 2-D time-frequency domain, the proposed method has an ability to select the signal of interesting, and is suitable for non-stationary signal. Additionally, the method is robust to noise and holds an advantage of low computational load. Simulations are conducted to verify the efficiency of the method and comparision is made with other methods.     

Fast direction of arrival estimation of wideband sources in unknown correlated noise fields

A computational efficient wideband Direction of Arrival (DOA) estimation method in the presence of unknown correlated noise is presented. A fast Two-sided Correlation Transformation (TCT) focusing matrix that transforms only the signal subspace is developed firstly, and then the propagator method is utilized to compute the focusing matrix and noise correlation matrix. In contrast to conventional wideband DOA estimation method, the proposed method requires only linear operation but does not involve any eigenvelue-decomposition to estimate the focusing matrix; it has a lower computational load, especially when the sensor number is greater than the source number. Because noise correlation matrix is estimated and eliminated from the array correlation matrix, the accuracy of DOA estimation is improved even in the presence of unknown correlation noise. Computer simulation results verified the efficiency of the method.     

矢量声纳高速运动目标稳健高分辨方位估计

针对水声矢量信号处理框架中的高速运动目标低信噪 比小快拍条件下的稳健高分辨方位估计问题, 将压缩感知技术应用于水声矢量信号空间谱估计模型中. 结合声矢量传感器结构特性, 探讨了基于声压振速联合处理的广义时域滤波方法; 结合矩阵空域预滤波理论, 设计了基于阻带约束通带均方误差最大值最小的空域滤波器, 研究了矢量声纳空域预滤波方法; 结合以上分析, 提出了基于压缩感知技术的时空联合滤波高分辨方位估计方法, 给出了方法的数学模型、物理解释及具体实施步骤.理论分析和计算机仿真试验表明, 新方法对于小快拍数 条件下的矢量声纳高速运动目标高分辨方位估计问题, 具有较低的双目标分辨门限和较高的估计精度, 有着良好的应用前景.湖上试验验证了方法的有效性. 关键词： 声矢量传感器 空间谱估计 时空滤波 压缩感知     

Seabed geoacoustic characterization with a vector sensor array

This paper proposes a vector sensor measurement model and the related Bartlett estimator based on particle velocity measurements for generic parameter estimation, illustrating the advantages of the Vector Sensor Array (VSA). A reliable estimate of the seabed properties such as sediment compressional speed, density and compressional attenuation based on matched-field inversion (MFI) techniques can be achieved using a small aperture VSA. It is shown that VSAs improve the resolution of seabed parameter estimation when compared with pressure sensor arrays with the same number of sensors. The data considered herein was acquired by a four-element VSA in the 8-14 kHz band, during the Makai Experiment in 2005. The results obtained with the MFI technique are compared with those obtained with a method proposed by C. Harrison, which determines the bottom reflection loss as the ratio between the upward and downward beam responses. The results show a good agreement and are in line with the historical information for the area. The particle velocity information provided by the VSA increases significantly the resolution of seabed parameter estimation and in some cases reliable results are obtained using only the vertical component of the particle velocity.     

压差式矢量水听器方位估计中的干扰抵消

矢量水听器由于能获取声场中标量（声压）和矢量（振速）信息，因此单个的矢量水听器就可实现目标方位估计。单个矢量水听器是利用信号的声压和质点振速之间相关性进行信号方位估计，但是当存在干扰，并且干扰和信号之间相关时，如果对运用能量流进行方位估计的方法不加改进，则会出现很大的误差，甚至出现错误的估计。本文提出一种存在已知噪声干扰情况下的干扰抵消方法，并针对该方法进行了仿真试验，最后运用湖试数据进行了验证。结果表明，该方法能有效地减弱相千千柑对信号的影响，实现对信号的方位估计。     

声矢量阵阵元位置及幅相误差有源校正算法*

针对声矢量阵幅相误差及阵元位置误差校正问题,基于特征分解法,提出一种简单实用的有源校正算法。该方法需要合作信源的至少3个方位信息,根据声矢量阵的通道特征,利用特征分解法构造矩阵方程组,通过矩阵运算得到声矢量阵阵元位置和幅相误差参数,从而实现对声矢量阵的校正。大量计算机仿真表明该校正算法具有良好的声矢量阵阵列误差参数估计性能。     

观测平台转向时稀疏贝叶斯学习方位估计

针对观测平台转向时固定安装于其上的声呐线列阵指向快速变化导致的空间谱谱峰变宽问题,提出一种稀疏贝叶斯学习方位估计方法。该方法利用大地坐标系下不同接收快拍中的空域稀疏信号具有相同先验分布的特性,将转向过程中多个阵列指向分别对应的接收快拍信息联合处理,以求得目标方位。仿真分析与海试数据处理显示出,所提方法可以获得谱峰较尖锐的空间谱,具有较高的测向精度和角度分辨力,此外,对由左右舷模糊引起的伪峰有较强的抑制效果。所得结果表明,所提方法可以有效解决谱峰变宽问题,提升了平台转向时的方位估计性能,同时有效地利用阵列指向的变化提高了线阵抗左右舷模糊能力。      

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。     

基于Khatri-Rao子空间和传播算子的宽带声源波达方向估计算法

本文提出基于Khatri-Rao子空间和传播算子的宽带声源波达方向估计算法。该算法将声源不同频率处的协方差矩阵变换重排为一个高维矩阵,然后利用传播算子方法估计宽带声源波达方向。该算法计算复杂度介于聚焦Khatri-Rao子空间和相干子空间算法之间。仿真和实验结果表明,该算法在降低计算量的同时,估计误差与聚焦Khatri-Rao子空间算法相近,远小于相干子空间算法。     

稳健的高精度单矢量传感器测向方法

针对单矢量传感器各通道之间的相位误差引起已有方法测向不准的问题,提出一种对相位误差稳健的高精度测向方法.该测向方法首先利用单矢量传感器接收信号协方差矩阵的主特征向量与其共轭向量做Hadamard积来构造空间谱,实现对水下目标的方位估计;由于Hadamard积消除了相位误差,此估计值与相位误差无关,但存在方位估计模糊。然后利用相位误差的估计值进行解模糊操作,从而得到正确的方位估计。该测向方法的测向性能独立于相位误差,估计精度高。仿真和试验数据处理结果验证了该测向方法对相位误差稳健;在相位误差条件下,其方位估计精度高于平均声强法、CAPON测向方法以及MUSIC测向方法。而且仿真结果表明,该测向方法的测向精度接近克拉美洛下界(CRB)。