基于声矢量传感器的水声通信技术研究

基于声矢量传感器声压和振速联合加权处理可以提高空间处理增益的原理,将声矢量传感器应用于相位调制的高速水声通信中,并结合自适应均衡算法,研究了相干解调和解码的方法。基于声矢量传感器声强处理可以抵消各向同性干扰、提高信噪比的原理,研究了在频率调制的水声通信系统中,利用声强解码代替声压解码的方法。理论分析、仿真研究和湖上试验结果表明:利用声矢量传感器相对于声压传感器来说,可以提高解码处理增益,进而提高了水声通信系统的作用距离、降低误码率。     

声矢量圆阵相位模态域目标方位估计

为了实现矢量传感器在圆阵阵型下的应用,文中提出了一种适合于声矢量圆阵的目标方位估计算法。该算法首先将声矢量圆阵阵元域信号分解为一系列相互正交的相位模态,在相位模态域构造声压和质点振速的互协方差矩阵,然后进行MUSIC方位估计.理论分析和仿真结果表明,文中算法比相同阵型的声压阵MUSIC方位估计算法具有更好的噪声抑制能力、方位估计性能以及多目标分辨能力,试验结果也表明本文算法具有更好的噪声抑制能力以及更好的目标方位估计性能。该算法实现了声压和质点振速的相干处理,充分利用了声矢量传感器的平均声强抗噪原理,具有较强的抗各向同性噪声能力,并可以将子空间类DOA(Direction of Arrival)估计算法和相位模态域阵列信号处理技术有机结合起来,实现了声矢量传感器在圆阵阵型条件下的高分辨DOA估计。     

一种基于声矢量传感器阵的宽带源二维波达方向估计算法

提出一种基于声矢量传感器阵的宽带源二维波达方向估计算法,在宽带相干源条件下实现了二维波达方向估计参数的自动配对。克服了通常声矢量传感器阵波达方向估计中存在的谱峰搜索和参数配对问题。分析表明:该算法能够可靠判定目标源的个数,具有较高的估计精度;不受目标波达方向角度间存在兼并(入射源含有相同的方位角或俯仰角)的影响;当存在阵列误差时,算法的稳健性好。     

基于实时主动声定位的快速测频算法

针对爆炸试验中冲击波超压传感器位置定位的问题,采用陆上实时主动声定位系统对爆炸试验中冲击波超压传感器位置进行定位。系统中对主动发出声信号频率为已知特定几种频率之一的单频信号的快速实时频率检测,提出了一种快速频率检测算法。算法充分利用信号频率为已知特定几种频率之一这一特定条件,并结合离散时间傅里叶变换(DTFT)与离散傅里叶变换(DFT)的关系以及帕塞瓦尔定理,得出快速频率检测的表达式。经实验验证和计算分析,算法检测频率精准可靠,计算量比其他快速测频算法小得多,更适用于军事紧急状态下陆上实时主动声定位中主动发声和实时定位条件下的快速测频。     

基于多重信号分类法的一种声矢量阵方位估计算法

为了提高声矢量阵高分辨方位估计的性能,文中提出了一种矢量阵MUSIC方位估计算法.该算法先构造声矢量阵声压和振速组合输出的互协方差矩阵,然后进行MUSIC方位估计.理论分析和计算机仿真表明,文中算法比传统声矢量阵MUSIC方位估计算法有更好的双目标分辨能力和弱目标方位估计能力,湖试结果也表明文中算法有更好的目标方位估计性能.该算法基于矢量传感器声压和振速的相干性原理,充分利用声压振速组合指向性抗干扰能力,可以更好地抑制各向同性干扰,提高阵列的处理增益,从而有更好的方位估计性能.     

基于矢量传感器的低空目标声测向算法及实验研究

将基于二维压差式矢量传感器的声压振速联合处理技术应用于低空目标无源测向的研究中,提出了一种新的无源声测向算法,该方法在小尺寸和低频条件下实现了对低空目标的精确测向。采用实测直升机辐射的噪声信号对算法进行了分析,研究了传感器尺寸、积分时间和信噪比对算法性能的影响。结果表明,矢量传感器尺寸为0.2 m,信噪比为0 dB时,测向误差小于2°,优于基于时延估计测向的方法。该研究为小基阵高精度的低空目标无源声测向提供了一种实现方法。     

分布式矢量传感器对宽带源被动定位的方法研究

本文给出了两种基于矢量传感器的被动定位方法。一般来说，对目标进行被动定位可以通过方位信息或时延信息来实现。单个矢量传感器就可以实现目标方位估计，而对多个矢量传感器接收的信号进行互相关运算即可得到目标对各矢量传感器的时延信息。本文先给出了利用方位信息进行被动定位的方法，然后给出了利用分布式矢量传感器进行方位一时延信息联合被动定位的新方法，并通过仿真分析对这两种方法的定位性能进行了比较。     

超高速高性能门控型三分幅相机

提出了一种改进块匹配宏块分布排列的快速传感器电子稳像算法,通过陀螺传感器测量摄像系统的抖动,利用小范围快速块匹配算法估计局部运动矢量,再运用最小二乘法解算全局运动矢量.小范围快速块匹配算法得到的局部运动矢量准确度高,仅需部分局部运动矢量即可准确解算出全局运动矢量.基于此在保证运动矢量准确度情况下,对块匹配宏块的分布排列进行了改进,从而减少匹配宏块数量加快算法速度.通过对宏块网格模型的分析,得出对小范围快速块匹配算法进行宏块分布改进的方案,进而设计出快速传感器电子稳像算法.仿真及实验表明:运算时间提高89%左右,且算法准确度略高于改进前算法.     

改进块匹配宏块的快速传感器电子稳像方法

提出了一种改进块匹配宏块分布排列的快速传感器电子稳像算法,通过陀螺传感器测量摄像系统的抖动,利用小范围快速块匹配算法估计局部运动矢量,再运用最小二乘法解算全局运动矢量.小范围快速块匹配算法得到的局部运动矢量准确度高,仅需部分局部运动矢量即可准确解算出全局运动矢量.基于此在保证运动矢量准确度情况下,对块匹配宏块的分布排列进行了改进,从而减少匹配宏块数量加快算法速度.通过对宏块网,格模型的分析,得出对小范围快速块匹配算法进行宏块分布改进的方案,进而设计出快速传感器电子稳像算法.仿真及实验表明:运算时间提高89％左右,且算法准确度略高于改进前算法.     

用正四棱锥形阵对声目标定位研究

文章结合声阵列在智能雷系统中的应用，提出了用立体五元声阵列对声目标进行定位，将智能雷中用于预警的传感器也参与到定位阵列中来，这样就在不增加传感器的条件下实现了市体阵列对声目标的定位。文章推导了定位公式和误差公式，并对结果进行仿真分析，与平面阵相比取得了较好的效果。不但提高了精度还降低了声阵列的盲区。     

Acoustic vector sensor signal processing

Acoustic vector sensor simultaneously, colocately and directly measures orthogonal components of particle velocity as well as pressure at single point in acoustic field so that is possible to improve performance of traditional underwater acoustic measurement devices or detection systems and extends new ideas for solving practical underwater acoustic engineering problems. Although acoustic vector sensor history of appearing in underwater acoustic area is no long, but with huge and potential military demands, acoustic vector sensor has strong development trend in last decade, it is evolving into a one of important underwater acoustic technology. Under this background, we try to review recent progress in study on acoustic vector sensor signal processing, such as signal detection, DOA estimation, beamforming, and so on.     

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     

交叉验证多路径匹配追踪水声矢量阵稀疏方位估计

水下运动目标的高分辨DOA估计和目标的左右舷分辨问题一直是水声阵列信号处理中的一个核心问题。矢量阵相比于声压阵具有天然的左右舷分辨能力和更高的处理增益,近年来得到了广泛关注。Capon等一些传统高分辨处理方法存在不能解相干源、需要多快拍处理以及对阵列流行误差敏感等多种问题。针对水声阵列信号处理领域面临的以上问题,利用声呐工作场景中空间目标的稀疏性,本文提出了一种基于交叉验证技术的多路径匹配追踪（Multiplepath Matching Pursuit with Cross Validation,CV-MMP）声矢量阵稀疏DOA估计算法。该算法采用交叉验证技术可以在未知场景中目标个数的条件下实现稀疏DOA的估计,相比于常规的声矢量阵Capon算法而言,可以在小快拍数甚至单快拍数条件下实现多目标的稀疏DOA估计以及高分辨能力。仿真和海试试验数据处理验证了提出的算法的有效性。      

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).     

Direction-of-arrival estimation for extensible acoustic vector sensor array

Aiming at high-resolution estimation of the direction-of-arrival of closely-spaced sources at low signal-to-noise ratio regions, this paper proposes a DOA estimation algorithm that is suitable for an extensible acoustic vector sensor array. Taking the 3D array composed of the minimum number(four) of acoustic vector sensors as the acquisition module, a virtual array having the same structure as the original array structure is extended in the three-dimensional space based on the aperture expansion characteristic of higher-order cumulants. The virtual array and the real array can construct a matrix with rotational invariance, which contains the angular information for estimating DOA. The Cramer-Rao bound of the algorithm are derived. We analyze the influence of SNR, the number of snapshots and the elevation angle on the performance of the algorithm. Simulation results show that the proposed algorithm has better noise suppression ability and higher resolution in DOA estimation than the conventional ESPRIT algorithm using the acoustic vector array. Experiments are conducted to validate the proposed algorithm.     

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。     

Acoustic array tracking performance under moderately complex environmental conditions

The direction-of-arrival (DOA) tracking performance of microphone arrays having aperture sizes ranging from 0.3 to 34 m is examined for an experiment involving a vehicle traversing a moderately complex terrain. A segment of the vehicle’s path was obscured behind a small, 6.7-m high, vegetated hill. The combination of the hill and upwind propagation created an acoustic shadow during this segment. DOA tracks were estimated with a minimum-variance distortionless response (MVDR) beamformer operating in two frequency bands: 25-60 Hz and 60-105 Hz. In the lower frequency band, array sizes between 1 and 8 m gave the best results, with DOA errors between 2° and 5°. Furthermore, in this band shadowing from the hill and wind refraction had a minimal affect on DOA error. In the higher frequency band, the acoustic shadow zone produced a distinct interval of high DOA error, with the 8-m array giving the best overall performance. Modeling of the beamforming process shows that high DOA errors corresponded to MVDR wavenumber patterns that are degraded by distortions to the propagating wavefronts. Our experimental results indicate that small acoustic arrays with apertures less than 0.3 m, operating at frequencies above 100 Hz, should be considered line of sight sensors. Given the moderate complexity of the test conditions, it is anticipated that the observed effects are likely to be present in most attempts to localize outdoor sound sources.     

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)。      

On the angular error of intensity vector based direction of arrival estimation in reverberant sound fields

An acoustic vector sensor provides measurements of both the pressure and particle velocity of a sound field in which it is placed. These measurements are vectorial in nature and can be used for the purpose of source localization. A straightforward approach towards determining the direction of arrival (DOA) utilizes the acoustic intensity vector, which is the product of pressure and particle velocity. The accuracy of an intensity vector based DOA estimator in the presence of noise has been analyzed previously. In this paper, the effects of reverberation upon the accuracy of such a DOA estimator are examined. It is shown that particular realizations of reverberation differ from an ideal isotropically diffuse field, and induce an estimation bias which is dependent upon the room impulse responses (RIRs). The limited knowledge available pertaining the RIRs is expressed statistically by employing the diffuse qualities of reverberation to extend Polack's statistical RIR model. Expressions for evaluating the typical bias magnitude as well as its probability distribution are derived.