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 β -norm optimization problem of the compressed Green＇s function and the data received by a vertieal/horizontal line array. The method is validated by simulation and is verified with the experimental data.

Matched Field Localization Based on CS-MUSIC Algorithm

The problem caused by shortness or excessiveness of snapshots and by coherent sources in underwater acoustic positioning is considered.A matched field localization algorithm based on CS-MUSIC(Compressive Sensing Multiple Signal Classification) is proposed based on the sparse mathematical model of the underwater positioning.The signal matrix is calculated through the SVD(Singular Value Decomposition) of the observation matrix.The observation matrix in the sparse mathematical model is replaced by the signal matrix,and a new concise sparse mathematical model is obtained,which means not only the scale of the localization problem but also the noise level is reduced;then the new sparse mathematical model is solved by the CS-MUSIC algorithm which is a combination of CS(Compressive Sensing) method and MUSIC(Multiple Signal Classification) method.The algorithm proposed in this paper can overcome effectively the difficulties caused by correlated sources and shortness of snapshots,and it can also reduce the time complexity and noise level of the localization problem by using the SVD of the observation matrix when the number of snapshots is large,which will be proved in this paper.

Algorithm of far-field centre estimation based on phase-only matched filter

Estimation of the far-field centre is carried out in beam auto-alignment. In this paper, the features of the far-field of a square beam are presented. Based on these features, a phase-only matched filter is designed, and the algorithm of centre estimation is developed. Using the simulated images with different kinds of noise and the 40 test images that are taken in sequence, the accuracy of this algorithm is estimated. Results show that the error is no more than one pixel for simulated noise images with a 99% probability, and the stability is restricted within one pixel for test images. Using the improved algorithm, the consumed time is reduced to 0.049 s.

基于图像处理的电路板缺陷检测系统设计

针对传统电路板缺陷检测多为人工检测、速度较慢且成本较高的问题,本文研究设计了一款以图像处理为基础、利用现场可编程门阵列(FPGA)实现对电路板缺陷准确、高速的检测系统。在传统图像增强算法的基础上提出一种针对不同图像信息采用不同感兴趣区间的方法,增强效果显著;为减少电路板上标识字样对匹配算法计算速度的影响,提出一种去除丝印算法,将电路板上多余的标识字样取消,减少图像匹配的计算量,加快检测的速度;在传统绝对误差和算法(SAD)模板匹配算法的基础上采用去平均值法计算图像信息,减小光照变化带来的影响;将传统2算子Sobel边缘检测扩展到8算子边缘检测,边缘信息更加明显清晰。采用FPGA作为硬件平台,在Vivado开发环境下实现Verilog HDL硬件逻辑语言,下载到FPGA中实现。实验结果表明,系统的平均检测精度为98.53%,检测单张电路板的时间为8.204 s。本系统设计在检测精度和速度上都有明显提升,且造价成本低。

An experimental study on matched field processing in shallow water

Matched field processing (MFP) is a generalized beamforming method which uses the spatial complexities of acoustic field in an ocean waveguide to localize sources in range, depth and azimuth or to infer parameters of the waveguide itself. In the paper, we present simulated and experimental results on narrow-band point source localization in shallow water by the matched field processing of a vertical array. Range-depth ambiguity surfaces are obtained by the spatial correlation of the incident field (modeled or realistic) with a modeled replica of that field. The simulated results indicate that a high-quality ambiguity surface can be obtained in case of perfect match between the 'true' environmental parameters and those used to compute the replica field. The effects of mismatches result in a degraded ambiguity surface and incorrect localization. Examples of localizations obtained with real sea test data are presented. It is shown that the conventional methods have better robustness than the minimum variance distortionless response (MVDR) based method. By employing the reduced minimum variance beamforming (RMVB), we can also get better results.

Matched-field localization using a virtual time-reversal processing method in shallow water

Time-reversal processing(TRP) is an implementation of matched-field processing(MFP) where the ocean itself is used to construct the replica field.This paper introduces virtual time-reversal processing(VTRP) that is implemented electronically at a receiver array and simulates the kind of processing that would be done by an actual TRP during the reciprocal propagation stage.MFP is a forward propagation process,while VTRP is a back-propagation process,which exploits the properties of reciprocity and superposition and is realized by weighting the replica surface with the complex conjugate of the data received on the corresponding element,followed by summation of the processed received data.The number of parabolic equation computational grids of VTRP is much smaller than that of MFP in a range-dependent waveguide.As a result,the localization surface of VTRP can be formed faster than its MFP counterpart in a range-dependent waveguide.The performance of VTRP for source localization is validated through numerical simulations and data from the Mediterranean Sea.

浅海大孔径水平阵列差频匹配场定位研究

随着阵列孔径的增大,常规匹配场在获得更高增益的同时也面临着对失配更加敏感的风险。文章通过对接收信号和拷贝声压同时进行差频自积处理,运用差频匹配场降低了匹配场对失配的敏感度,从而提高定位的稳健性。从简正波理论出发对比了差频匹配场和常规匹配场对阵形失配、环境失配的敏感性,分析差频匹配场应用于浅海大孔径水平阵列定位的优势。仿真和实验结果表明,差频匹配场方法有更好的定位稳健性。

一种改进的匹配干涉场被动定位方法

匹配干涉场被动定位方法具有较好的宽容性,对声场参数建模误差要求较低,但当声场失配程度较高,或目标信号信噪比较低时,基于干涉场结构匹配的相关峰值不明显,使得匹配性能降低。因此,在原始的匹配干涉场的基础上提出了一种基于Radon变换的改进方法,利用Radon变换对拷贝声场的干涉结构和实际声场的精细干涉结构进行图像处理后再对其作相关处理。仿真和实验数据表明,经此改进后,即使是在建模声场存在一定失配的条件下,在匹配相关峰值提高的同时,旁瓣也能得到有效抑制,能够有效地改进匹配干涉场的被动定位效果。

基于差频匹配场的深海声源定位方法

匹配场处理是水下目标定位的重要方法,其利用声场的空间结构匹配来反演声源位置,但传统匹配场处理(CMFP)对环境参数的失配非常敏感,容易产生误差。频率差匹配场处理(FDMFP)相比于CMFP具有更高的稳健性,但不适用于深海环境;仅相位匹配自积处理(POMAP)在FDMFP基础上改进后适用于深海环境,但POMAP的抗噪性较低。因此,本文在仅相位匹配自积处理(POMAP)方法的基础上,将带宽平均处理移动到匹配处理后的位置,提出了改进的仅相位匹配自积处理(IPOMAP)方法,以及将CMFP、POMAP、IPOMAP组合处理的方法(CPIP),该方法既有较好的抗噪性,又能在深海环境下保持差频匹配场处理方法的高稳健性。数值仿真和实验数据分析结果表明,CPIP在CMFP、POMAP、IPOMAP、CPIP中具有最优的定位性能,在40 km范围内具有最小的声源定位误差。这为失配环境和低信噪比时的深海声源定位方法的研究提供一种可行的思路。

Matched field noise suppression: Principle with application to towed hydrophone line array

Discrete noise source suppression in underwa-ter acoustic channel has attracted great attention in recent years. The paper proposes a new principle for dealing with the problem. This new principle is called matched field noise suppression (MFNS). Based on a previous work of the au-thors group, a full understanding about how a discrete noise source shows effects on the performance of a towed hydro-phone line array has been obtained. In light of that finding, MFNS is proposed, which explores and utilizes the charac-teristics of the noise transmission channel to achieve much greater suppression of the noise in comparison with existing approaches. MFNS combines the concept of matched field processing (MFP) and optimal sensor array processing (OSAP) together to suppress the discrete noise source and to maintain an optimal beam for receiving far-field wanted plane wave signals. A MFNS beam-former is deduced in constraint with signal plane-wave response being unit and noise matched field response being zero. A closed-form solution of the weight vec-tor for the beam-former is given. Computer simulation results agree well to the theoretical analysis.

水下地形匹配导航现状及发展趋势

为了深入研究水下地形匹配导航技术,本文依据国内外最新研究成果,系统地总结了该技术的研究进展,认为已建立了融合实测和反演水深的全球海底地形模型,形成了适用于不同情况的地形匹配算法体系,建立了地形特征集与适配性关系,构建了满足间歇/连续地形匹配的策略及与惯性导航系统信息融合的抗差模型,发展了匹配导航系统,综合促进了水下地形匹配导航技术的进步。分析了当前研究存在的问题,并指出高精度高分辨率全球水深模型构建、在航测深数据处理、稳健匹配导航算法和系统研发是该技术未来的发展方向。

离网格压缩匹配场处理

水声被动目标定位在海洋资源勘探、水下探测、海上安全监测等任务中有着重要应用,是水声领域最重要的课题之一。已有的经典方法如匹配场处理和压缩匹配场处理等,能够在预先划分好的距离-深度网格点上进行源定位,但是实际情况中的目标源会偏离网格点,导致此类方法的性能下降;且在压缩匹配场处理中,离网格源可能导致多个稀疏解对应单个源,呈现出多峰值模糊问题。针对该问题,考虑到由于水下相邻位置处的信道冲激响应极为相似,本文基于任意离网格位置的信道冲激响应可被周围网格点处的拷贝场向量近似拟合这一特性,建立了一种面向水下目标定位的群稀疏信号模型,并提出了相应的离网格压缩匹配场处理方法,通过恢复的稀疏信号计算出网格点处的插值系数对离网格源进行高精度定位。实验表明,在双源定位任务中,离网格压缩匹配场处理的定位性能优于传统的匹配场处理和压缩匹配场处理方法。当网格的距离间隔为0.05 km、深度间隔为10 m时,在信噪比大于−5 dB的条件下,离网格压缩匹配场处理的双源平均测距误差与压缩匹配场处理相比降低了250 m以上。

联合匹配场和神经网络的声速时间场构建方法

局域声速场变化严重影响了海洋声学定位与导航的精度,构建高精度、高分辨率的声速时间场尤为重要。针对局域声速场参考样本不足导致声速场构建精度较低的问题,本文依据匹配场和神经网络理论,建立了联合匹配场和神经网络的声速时间场构建方法。利用通信数据和全水深声速剖面数据,采用匹配场处理进行声速剖面仿真,其次通过后向传播神经网络拟合经验正交函数分解重构系数构建声速剖面,并与实测抛弃式温盐深剖面仪数据进行对比。结果表明:与平均声速剖面的1.079 m/s相比,考虑匹配场仿真声速剖面的联合匹配场和神经网络的声速时间场构建方法的均方根误差为0.665 m/s,提高了38.4%。因此,该算法可以提高复杂海洋环境中声速时间场的构造精度。

基于机器视觉的机耕船障碍检测及避障策略研究

随着农村劳动力转移城市,传统的劳作也逐渐被先进的劳动生产方式替代,机耕船的制造厂家在考虑如何将机耕船进行高智能性、高工作效率的升级,实现无人驾驶。对机耕船障碍检测和避障策略进行了研究分析,选用基于OpenCV的BM和SGBM算法来实现双目立体匹配测距,通过实验对比两种算法的实际测距效果,BM和SGBM算法测距数据误差分别控制在0.867%和1.23%以内;通过构建样本库训练分类器,得到稳定的障碍物识别模型;选取人工势场法作为研究的基础,提出了一种改进的人工势场法,使机耕船顺利跳出局部极小值点,顺利避开了障碍物抵达目标终点。

由矢量水听器阵反演海底地声参数

矢量水听器能同时测量声压和质点振速信号,为了对这些信息在海底地声参数反演中加以充分利用,根据声传播理论研究了不同号简正波对声矢量场的影响,并在此基础上提出了一种将声压和质点振速相联合的地声反演方法.理论与实验研究表明,对声压和质点水平振速而言,低号简正波往往占主要贡献,而对于质点垂直振速,高号简正波的贡献更大.海底地声参数反演的数值仿真与实验结果表明,基于矢量水听器阵的地声反演方法可以有效降低海底声学参数反演的不确定性.这为矢量水听器应用于海洋环境监测提供了一种新方法.

不确实海洋中最小方差匹配场波束形成对环境参量失配的灵敏性分析

浅海环境背景下由于空-时采样不充分、介质的空时变化性,海洋环境参量通常是不确知的,由此驱动数值传播模型得到的拷贝声场也是不确实的,从而导致基于拷贝声场和测量声场作拷贝相关处理的最小方差匹配场波束形成性能下降.针对上述问题,利用NRL Workshop′93提供的典型浅海不确实海洋环境,以不确实情况下定位偏置、不确实时与确知时模糊度表面主瓣峰值比、主瓣背景比3个量为性能度量,量化分析了宽带最小方差匹配场波束形成的性能对水体声速、海深等8个环境参量不确实性的灵敏性.经对环境参量失配的全面量化分析,结果表明:海深、水体声速是最敏感参量,沉积层声速次之,其他参量的灵敏性最弱.

阵间模基处理被动定位技术研究

随着目标声源级不断减小、环境噪声级不断增大,常规的基于单节点的被动定位方式已经不能满足声纳探测的需求,因此提出一种新的将网络化探测系统和模基处理技术相结合的被动定位方法,可以从空间不同角度对目标进行观察并充分利用环境声场的复杂性对目标进行定位。模基处理方法主要有匹配场处理、匹配模处理等,以匹配场处理为例进行分析,将常规波束形成(Conventional Beamforming,CBF)、自适应波束形成(Minimum Variance Distortionless Response,MVDR)两种匹配场处理器和阵间相干、非相干信号处理方法相结合进行仿真,对单阵和多阵、MVDR和CBF、相干处理和非相干处理、宽带和窄带之间的定位性能进行了对比。仿真结果显示,基于多节点的阵间模基相干处理方式在定位性能上明显优于单节点的模基处理结果。

浅海地声参数宽带匹配场反演的实验研究

根据不同浅海环境参数在不同的频段对匹配场功率具有不同贡献的特点 ,提出了宽带匹配场反演的多步优化策略 ,并与直接全参数反演进行了实测数据的性能对比。采用多步反演策略对亚洲海实验 ( ASIAEX2 0 0 1 )数据进行处理 ,按照不同海区水文条件的差异 ,分别进行了水平不变和水平变化的环境参数反演 ,得到了东中国海

由矢量水听器阵列反演浅海地声参数

基于矢量水听器能够比传统的声压水听器提供更多的声场信息,文章提供了一种利用矢量水听器阵列(AVS)进行浅海地声参数反演的方法。首先,对声场矢量的传播规律进行了研究;其次,利用矢量匹配场(MFP)方法进行了海底声速的反演;最后利用声压和质点垂直振速的传播损失差反演了海底吸收。基于矢量水听器的海底参数反演方法主要具有下述优点:一是利用矢量匹配场反演海底声速能够有效减小参数估计误差;二是利用声场矢量传播损失差进行海底吸收反演能够排除信号源级起伏对反演的干扰。实验结果表明,基于矢量水听器阵列的海底参数反演能够很好的进行声场传播预报工作。

指纹中心点的定位和特征匹配方法

提出了一种新的指纹中心点搜索的方法及基于中心点的指纹匹配算法 .它利用指纹块方向图中块方向的变化进行中心点的粗细两步搜索 ,首先在粗方向图中搜索方向锐变区域 ,然后在细方向图中对相应的区域再进一步搜索方向锐变的区域 ,最终得到中心点 .在此基础上介绍了基于网格的旋转匹配方法 .此方法对噪声大的指纹有较强的抗干扰性 ,算法相对简单且效果良好 .