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An MIMO Sonar Array for High-resolution 3D Forward-looking Imaging 用于高分辨率3D前视成像的MIMO声纳阵列
Pub Date : 2019-06-17 DOI: 10.1109/OCEANSE.2019.8867062
Xionghou Liu, Chi Zhang, Hongyu Chen, Chao Sun, Yixin Yang, Kuan Fan, Jiapeng Liu
The three-dimensional imaging sonar using a planar or volumetric hydrophone array is useful for underwater acoustic imaging, since it can provide the volumetric information of an underwater target. However, the system cost is at a high level due to the large number of hydrophones adopted. To reduce the system cost, the sparse array optimization is often used to remove a number of hydrophones and simultaneously, to keep a desired beampattern performance. Nevertheless, the angle resolution of a sparse optimized hydrophone array is not enough for relatively long range imaging application, such as the small target detection. Different from the sparse array optimization method, using a forward-looking sonar composed of several horizontally paralleled uniform linear arrays (ULAs) can achieve a good 3-D imaging ability. The 3-D forward-looking sonar is based on the slant looking imaging processing, and it combines the conventional horizontal beamforming and the high-resolution vertical beamforming together. Nevertheless, the horizontal angle resolution is restricted by the limited physical size of the sonar platform (e.g., an underwater manned vehicle or an underwater robot). What is worse, the restricted angle resolution in the horizontal direction will degrade the imaging performance of the vertical beamforming. To solve the problem, we design a MIMO sonar array layout for the 3-D forward-looking imaging. The designed MIMO sonar array is composed of two sparsely located transmitting transducers and several parallel ULAs. By doing so, the horizontal angle resolution doubles that of a traditional sonar array (which is composed of one transmitter and several paralleled ULAs), and the vertical imaging ability is substantially improved. We give an example of the MIMO sonar array, and give the imaging performance analysis to validate the effectiveness of the designed array layout.
利用平面或体积型水听器阵列的三维成像声呐能够提供水下目标的体积信息,是水声成像的重要手段。然而,由于采用了大量的水听器,系统成本处于较高水平。为了降低系统成本,通常采用稀疏阵列优化来去除多个水听器,同时保持理想的波束方向图性能。然而,稀疏优化水听器阵列的角度分辨率不足以满足小目标探测等较远距离成像应用。与稀疏阵列优化方法不同,使用由多个水平平行均匀线性阵列(ULAs)组成的前视声纳可以获得良好的三维成像能力。三维前视声呐以斜视成像处理为基础,将传统水平波束形成和高分辨率垂直波束形成相结合。然而,水平角度分辨率受到声纳平台有限的物理尺寸的限制(例如,水下载人车辆或水下机器人)。此外,水平方向上受限的角度分辨率会降低垂直波束形成的成像性能。为了解决这一问题,我们设计了一种用于三维前视成像的MIMO声呐阵列布局。所设计的MIMO声呐阵列由两个稀疏分布的发射换能器和多个并行ula组成。通过这样做,水平角度分辨率是传统声纳阵列(由一个发射机和多个并联ula组成)的两倍,并且垂直成像能力大大提高。最后以MIMO声呐阵列为例,对阵列的成像性能进行了分析,验证了所设计阵列布局的有效性。
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引用次数: 1
Mono-hydrophone localization of baleen whales: a study of propagation using a spectral element method applied in Northern Chile 须鲸的单水听器定位:在智利北部应用的光谱元素方法的传播研究
Pub Date : 2019-06-17 DOI: 10.1109/OCEANSE.2019.8867333
J. Patris, D. Komatitsch, M. Sepúlveda, Macarena Santos, H. Glotin, Franck Malige, Susannah J. Buchan, M. Asch
In the context of passive acoustic monitoring of large whales, we propose a new method for localizing blue whales (Balaenoptera musculus) from the acoustic recordings of only one sensor. We use a precise modelling of the sound propagation thanks to SPECFEM, a spectral element code for solving wave propagation equations. Based on field measurements in Northern Chile, we ran a simulation on a large supercomputer. We also exploited a recording device, Bombyx II, for one and a half months, with visual monitoring of the zone by a group of experts. We find that the method applied to the south east Pacific song of blue whales gives theoretical results of about 50% success in position recovery. Since we have redundancy in our data, we were able to locate the whale with a precision of 500 m over a box of 10 km by 5 km in the case when we have both visual detection and a strong acoustic signal. More tests should be performed before validating this method, but these first results are encouraging.
在大型鲸鱼被动声学监测的背景下,我们提出了一种仅从一个传感器的声学记录中定位蓝鲸(Balaenoptera musculus)的新方法。我们使用SPECFEM(一个用于求解波传播方程的谱元代码)对声音传播进行精确建模。根据在智利北部的实地测量,我们在一台大型超级计算机上进行了模拟。我们还使用了一个记录设备,Bombyx II,用了一个半月的时间,由一组专家对该区域进行了视觉监控。我们发现,应用于东南太平洋蓝鲸之歌的方法在位置恢复方面的理论结果成功率约为50%。由于我们的数据有冗余,在我们同时拥有视觉检测和强大的声学信号的情况下,我们能够在10公里乘5公里的范围内以500米的精度定位鲸鱼。在验证此方法之前,还需要进行更多的测试,但这些初步结果令人鼓舞。
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引用次数: 1
Numerical and experimental study on wave propagation in granular media using a spectral-element method 波谱元法在颗粒介质中传播的数值与实验研究
Pub Date : 2019-06-17 DOI: 10.1109/OCEANSE.2019.8867525
K. Mizuno, P. Cristini, D. Komatitsch, Y. Capdeville
Acoustic systems with various operating frequencies are commonly used for the detection of objects buried in the marine sediments. However, the propagation of acoustic waves in sediments is generally much more complicated than in water because sediments are, in general, granular media composed of solid and fluid parts. It makes the understanding of signals more difficult and engineers have to rely on a cut-and-try method for the design of the new sub-bottom devices which results in an increase of the total cost of sea surveys. Therefore, a better understanding of wave propagation in the granular media and of the numerical model used for the prediction of reflected signals from buried objects is required. In the present study, we evaluate the performances of the prediction tools based on the spectral element method for the simulation of backscattered signals by comparing them to experimental results obtained in a tank filled with water and calibrated glass beads having a wide range of ratio of the grain size to the wavelength.
不同工作频率的声学系统通常用于探测海洋沉积物中的物体。然而,声波在沉积物中的传播通常比在水中复杂得多,因为沉积物通常是由固体和流体部分组成的粒状介质。这使得对信号的理解变得更加困难,工程师们不得不依靠一种反复尝试的方法来设计新的海底设备,这导致海洋调查的总成本增加。因此,需要更好地理解波在颗粒介质中的传播以及用于预测埋藏物体反射信号的数值模型。在本研究中,我们将基于谱元方法的预测工具用于模拟后向散射信号,并将其与在装满水的水箱中获得的实验结果进行比较,并将其与具有宽范围晶粒尺寸与波长比的校准玻璃珠进行比较。
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引用次数: 0
Wavelet Learning by Adaptive Hermite Cubic Splines applied to Bioacoustic Chirps 自适应埃尔米特三次样条小波学习在生物声学啁啾中的应用
Pub Date : 2019-06-17 DOI: 10.1109/OCEANSE.2019.8867410
Randall Balestriero, H. Glotin
Acoustic monitoring is used to study marine mammals in oceans. Automated analysis for captured sound is almost essential because of the large quantity of data. The deep learning approach is an efficient method, however acoustic features are often not adapted. Convolutional Neural Net can be seen as an optimal kernel decomposition, nevertheless it requires large amount of training data to learn its kernels. An alternative using pre-imposed kernels and thus not requiring any amount of data is the scattering framework which imposes as kernels wavelet filters. Our research focuses on adaptive time-frequency decomposition of bioacoustic signal, based on cubic spline learning representation. We give the theoretical derivations of the model, and demonstrates efficient real applications of various signal, including chirps of songs of Blue Whale.
声学监测用于研究海洋中的海洋哺乳动物。由于数据量大,对捕获的声音进行自动分析几乎是必不可少的。深度学习方法是一种有效的方法,但声学特征往往不适应。卷积神经网络可以看作是一种最优的核分解,但是它需要大量的训练数据来学习它的核。另一种方法是使用预施加的核,因此不需要任何数据量,这是散射框架,它施加核小波滤波器。我们的研究重点是基于三次样条学习表示的生物声信号的自适应时频分解。给出了该模型的理论推导,并对包括蓝鲸鸣叫声在内的各种信号进行了有效的实际应用。
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引用次数: 2
ABYSOUND, an end to end system for noise impact measurement of deep sea mining production tools 深海采矿生产工具噪声影响测量的端到端系统
Pub Date : 2019-06-17 DOI: 10.1109/OCEANSE.2019.8867555
Rania Bassila, Théo Bertet, L. Somaglino, M. Bouhier, H. Glotin, Paul Best, Valentin Baron, C. Noel, P. Cristini, Florent Fayet, B. Nicolas, J. Mars
The project’s main objective is to establish the feasibility of a new service and an associated system aimed to estimate the noise radiated into the water by the equipment and systems deployed on the ground during deep offshore sea floor operations. Based on this estimation, the main purpose of the project will be to assess the acoustic environmental impact on marine fauna. It will also make it possible to assess the acoustic disturbance generated by the devices or systems deployed on the ground on the operation of the sub-robots monitoring and implement adaptive strategies to prevent malfunctions of the latter. The project involves technological developments and system validation through deep sea experiments.
该项目的主要目标是建立一项新服务和相关系统的可行性,旨在评估在深海海底作业期间部署在地面的设备和系统辐射到水中的噪音。在此基础上,该项目的主要目的是评估对海洋动物的声环境影响。它还可以评估部署在地面上的设备或系统对子机器人监控操作产生的声干扰,并实施自适应策略以防止后者发生故障。该项目涉及通过深海实验进行技术开发和系统验证。
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引用次数: 1
The Multicriteria Constrained Stochastic Matched Filter For Underwater Bioacoustic Signals 水下生物声信号的多准则约束随机匹配滤波器
Pub Date : 2019-06-17 DOI: 10.1109/OCEANSE.2019.8867083
B. Xerri, B. Borloz, Maissa Chagmani
The aim of this paper is the detection of a bioacoustic signal embedded in several noises such as sea noise and other bioacoustic signals (dolphins, sperm whales). All the signals are real world signals.Only second order statistics are use through the estimated correlation matrices of the signals.This paper proposes an extension of the Constrained Stochastic Matched Filter (CSMF) based on the optimization of the Signal to Noise Ratio after linear filtering. The approach proposed is a multicriteria one, merging three different versions of the CSMF, and is named Multicriteria CSMF (MCSMF).The objective is that the results obtained are better than the other methods, or at least equal to the best among the three.The results are provided on ROC curves and the method is compared to the classical method Stochastic Matched Filter (SMF).
本文的目的是检测嵌入在几种噪声中的生物声信号,如海洋噪声和其他生物声信号(海豚,抹香鲸)。所有的信号都是真实世界的信号。通过估计信号的相关矩阵,只使用二阶统计量。本文提出了一种基于线性滤波后信噪比优化的约束随机匹配滤波器(CSMF)的扩展方法。提出的方法是一种多标准的方法,合并了三个不同版本的CSMF,并被命名为多标准CSMF (MCSMF)。目标是获得的结果优于其他方法,或至少等于三种方法中的最佳方法。在ROC曲线上给出了结果,并与经典的随机匹配滤波(SMF)方法进行了比较。
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引用次数: 0
Analysing Fibre Composite Designs for High-Solidity Ducted Tidal Turbine Blades 高固体度导流式潮汐涡轮机叶片纤维复合材料设计分析
Pub Date : 2019-06-17 DOI: 10.1109/OCEANSE.2019.8867566
Mitchell G. Borg, Q. Xiao, Steven Allsop, A. Incecik, C. Peyrard
This study elaborates a one-way fluid-structure interaction numerical model utilised in investigating the structural mechanics concerning the rotor blades comprising a ducted high-solidity tidal turbine. Coupling hydrodynamic outcomes as structural inputs in effort of acknowledging the most applicable setup, distinct designs are investigated, solid blades and cored blades, utilising fibre-reinforced composite materials, analysed within criteria related to blade axial deformation, induced radial strains, and rotor specific mass.
本文建立了一个单向流固耦合数值模型,用于研究导管式高固体度潮汐涡轮机转子叶片的结构力学问题。耦合流体力学结果作为结构输入,以确认最适用的设置,研究了不同的设计,使用纤维增强复合材料的实心叶片和带芯叶片,在与叶片轴向变形,诱导径向应变和转子比质量相关的标准内进行了分析。
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引用次数: 0
Estimation of Doubly Spread Underwater Acoustic Channel via Gram-Schmidt Matching Pursuit 基于Gram-Schmidt匹配跟踪的双扩频水声信道估计
Pub Date : 2019-06-17 DOI: 10.1109/OCEANSE.2019.8867540
Feiyun Wu, Kunde Yang, Tian Tian, Chunlong Huang, Yunchao Zhu, F. Tong
The underwater acoustic channel (UAC) exhibits strongly time delay and Doppler (DD) spread especially when the UAC is rapidly time-varying. These dynamic factors result to a serious impact on communication performance such as Inter-Symbol Interference (ISI). Hence, estimation of complex amplitude, time delay and the Dopplers of the UAC becomes the key part in underwater acoustic communication and is hopeful for improving the performance of equalization. However, the estimation is challenged by multiple factors to be estimated in delay and Doppler dimensions. This study exploits the sparsity of the UAC and develops an estimator via using Gram-Schmidt to find orthogonal bases, which leads to the fast and orthogonal way to select the supports of the dictionaries. The support list of the dictionaries constructed by probe signal can be used for estimating the DD functions from a noisy received signal. Matching Pursuit (MP) and Least Square (LS) methods are used for comparisons. The effectiveness of the proposed method is verified by the experimental data.
水声信道表现出强烈的时间延迟和多普勒(DD)扩散,特别是在快速时变的水声信道中。这些动态因素会对通信性能造成严重影响,如码间干扰(ISI)。因此,对UAC的复幅度、时延和多普勒的估计成为水声通信的关键部分,有望提高均衡性能。然而,在时延和多普勒维度上,估计受到多种因素的挑战。本研究利用UAC的稀疏性,利用Gram-Schmidt寻找正交基的方法开发了一个估计器,从而实现了快速正交选择字典支持的方法。探测信号构造的字典支持列表可用于估计接收到的带噪声信号的DD函数。采用匹配追踪(MP)和最小二乘(LS)方法进行比较。实验数据验证了该方法的有效性。
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引用次数: 2
Data Assimilation Versus Machine Learning: Comparative Study Of Fish Catch Forecasting 数据同化与机器学习:鱼类捕捞预测的比较研究
Pub Date : 2019-06-17 DOI: 10.1109/OCEANSE.2019.8867066
Yuka Horiuchi, Yuya Kokaki, Tetsunori Kobayashi, Tetsuji Ogawa
Data assimilation (DA) and machine learning (ML) are empirically compared for automatic daily fish catch forecasting (DFCF). ML would be a promising approach if large-scale data are available for training. Otherwise, DA would perform well, where prior knowledge on a monitoring target is incorporated into modeling. The present study aims to clarify the robustness of both approaches in DFCF with a small amount of data, and their evolution as the amount of training data increases. Experimental comparisons using catch and meteorological data demonstrate that a DA-based DFCF system yields a significant improvement over an ML-based systems with a small amount of data, and is comparable with ML-based systems with sufficient amount of data.
对数据同化(DA)和机器学习(ML)在自动每日渔获量预测(DFCF)中的应用进行了实证比较。如果有大规模数据可用于训练,ML将是一种很有前途的方法。否则,在将监视目标的先验知识纳入建模的情况下,数据分析将表现良好。本研究旨在阐明两种方法在少量数据的DFCF中的鲁棒性,以及它们随着训练数据量的增加而演变。使用捕鱼量和气象数据进行的实验比较表明,基于数据分析的DFCF系统比具有少量数据的基于机器学习的系统产生了显著的改进,并且与具有足够数据量的基于机器学习的系统相当。
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引用次数: 0
EMI Sensing for Underwater Metallic Targets Detection and Classification 水下金属目标的电磁干扰检测与分类
Pub Date : 2019-06-17 DOI: 10.1109/OCEANSE.2019.8867057
F. Shubitidze, B. Barrowes, I. Shamatava
Electromagnetic induction (EMI) sensing phenomenon are investigated for a conducting and multilayer environment to aid in underwater unexploded ordnance (UXO) detection and classification. The marine environment introduces complexities, such salinity gradient, sharp conductivity changes at air-water-sediment etc., which adversely can affect targets EMI signals and make underwater targets classification more difficult problem than classifying the same buried targets on land. The sensitivity of a secondary EMI signal with respect the water/air and/or water/sediment boundaries and temporal (diffusive EM field propagation speed) variability of EMI fields in an underwater (UW) environment are studied and demonstrated using the unconditionally stable Crank-Nicolson finite different time domain method (FDTD).
研究导电多层环境下的电磁感应(EMI)传感现象,以辅助水下未爆弹药的探测与分类。海洋环境的复杂性,如盐度梯度、空气-水-沉积物电导率的急剧变化等,会对目标的电磁干扰信号产生不利影响,使水下目标分类比陆地上相同的埋藏目标分类更加困难。利用无条件稳定的Crank-Nicolson有限不同时域方法(FDTD)研究了水下环境中二次电磁干扰信号相对于水/空气和/或水/沉积物边界的灵敏度以及电磁干扰场的时间(扩散电磁场传播速度)变异性。
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引用次数: 0
期刊
OCEANS 2019 - Marseille
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