声学滑翔机联合的深海水下声源定位

为了验证多台滑翔机用于声源位置估计的可行性,提出了一种基于声学滑翔机的联合水下声源定位方法。首先利用水下滑翔机在东印度洋北部海域获取的声传播数据,分析了宽带脉冲信号的多途传播特性,然后提出了利用单水听器基于脉冲波形结构匹配的声源距离估计方法,在此基础上通过两台水下声学滑翔机联合定位的方式,实现了水下声源距离和方位的同步估计。结果表明:在印度洋深海非完全声道条件下,在100 km范围内,使用单台滑翔机估计的声源距离整体较为准确,但仍有估计误差较大点;联合两台滑翔机进行水下声源定位可进一步提高精度,对于200 m深度的声源,距离估计均方根误差为2.5 km,相对误差小于4%,方位估计均方根误差为2.4°。     

大气声传播通道的声源当量估计方法

提出了一种基于大气声传播通道的爆炸声源能量估计方法,通过将计算大气声学的传播能量分布结果与大气中传播的声压幅度衰减模型相结合,使用平流层通道与热层通道传播损失能量比例作为修正量,提高了对爆炸声源能量的估计精度。在多次地面爆炸实验得到的数据中,使用观测距离800 km以上且同时存在平流层通道与热层通道的次声接收信号,对比了平流层顶风速修正的能量估计方法与该文提出的基于大气声传播通道的能量估计方法。实验结果验证了相对于传统风速修正的能量估计方法,该方法可显著降低估计误差。     

空气中声源激发浅海水下声场传播特性的实验研究

为了获得空气中远距离声源激发水下声场的精细结构,2013年3月,声场声信息国家重点实验室在南海海域进行了一次空气中声源激发水下声场的实验。采用汽笛作为空气声源,海底放置水听器作为接收,在实验过程中,发射船由距离水听器2.4 km处行驶至9.8 km。本文对该次实验数据进行分析,获得了收发距离远达9.8 km、频率分别为128 Hz和256 Hz的声传播损失曲线,该曲线随传播距离变化存在清晰的震荡结构.利用波数积分方法计算实验环境下的水下声场理论值,并对获得的声场传播特性进行了较好的物理解释。     

各种水下声源的发声机理及其特性

扼要综述了现有的七种水下声源产生技术,包括炸药爆炸声源、电声换能器声源、参量阵声源、流体动力式声源、电磁式声源、激光声源和等离子体声源。分析了这些声源的发声机理,结合其性能特点阐述了在实际中的不同应用,并对等离子体声源的机理、特点和实际应用进行了重点分析。列表归纳总结了各种水下声源的原理、主要性能和应用范围,为水下声源的应用拓展提供了依据。     

基于水下滑翔机的海洋环境噪声测量系统*

水下滑翔机是一种新型的水下潜器,将其用于海洋环境噪声测量具有很大的应用潜力。选择的平台是“Petrel II”滑翔机,为其设计和实现了深水水听器和数据采集系统。深水水听器具有耐高静水压和高灵敏度的特点,并通过了60MPa的高静水压力试验;数据采集系统具有体积小、功耗低、控制灵活和易于扩展的特点。搭载声学测量系统的滑翔机顺利通过水池测试和海上试验,测试结果验证了技术方案的可行性和系统工作的稳定性,可为深入进行海洋环境噪声时空特性实验研究提供技术支持。     

基于声传播算子的声源定位实验模拟方法研究

声传播算子是一种高效的时域声场计算方法,它能够很方便地计算出给定系统参数下任意时刻任意位置的声场变化情况,本文采用这种方法计算所得的二维房间声场信息进行传声器阵列的声源定位仿真实验。计算结果表明,用该方法获取的阵列数据能有效地应用于阵列信号处理算法中,准确地估计出初始高斯脉冲声源的方向。声传播算子声场计算方法能为传声器阵列声源定位的实验提供方便,使得传声器阵列声源定位算法在不同混响时间的鲁棒性实验研究变得更加简捷。     

深海大深度声传播特性及直达声区水下声源距离估计

深海大深度声传播特性对在深海近海底进行水声目标探测和定位具有重要意义。利用一次南海中南部深海不完全声道中的脉冲声传播实验数据,分析了海底附近大深度声传播损失及脉冲多途传播特性,并根据直达波和海底-海面反射波的时延差与收发距离的关系,提出一种利用深海直达声区脉冲多途到达时间进行水下声源距离估计的方法。结果表明:当接收器深度位于南海深海海底附近而声源深度较浅时,直达声区水平宽度可达30 km,传播损失相对影区来说较小,有利于水下声源探测;直达声区的直达波与海底-海面反射波的到达时延差随着收发距离的增大单调减小,可被用于水下声源距离估计。得到水下声源的距离估计结果与实验GPS测量结果较为一致,距离估计均方误差为0.28 km。     

西太平洋远距离声传播特性

声信号在海水中能够传播上千千米,远距离声传播与近距离声传播的特性不同.本文利用西太平洋声源与接收最远距离近2000 km的水声实验数据,对实验海区的海洋环境信息、实验使用的接收垂直阵信息进行处理,分析大洋完全声道环境下,远距离声传播能量衰减规律和多途到达结构特性.在远距离传播能量衰减规律方面,随着传播距离增大,海水吸收对声能衰减的作用凸显,海水吸收系数的选取对声场能量预报的准确性至关重要.较低频信号海水吸收较小,中心频率100 Hz的声信号,传播距离从1000—2000 km,传播损失仅增大6 dB左右.深海声道远距离声传播多途到达结构特性方面,实验海区温跃层声速较高,使得到达接收点的本征声线数目更多,多途到达结构更复杂,海面反射声线形成的到达结构处在整体到达结构的靠前位置,且能量相对较强;受西北太平洋副热带模态水的影响,声速剖面存在双跃层结构,导致部分声线到达接收点的时间较早,多途到达结构在时间轴上的长度延长.     

水下声传播的发展及其应用

文章介绍了水声学中的基础研究领域水下声传播影响因素和研究进展,分析了海洋环境因素对水下声传播的影响机理,给出了不同类型海域以及不同季节的水下声传播特征。文章还列举了目前水下声传播研究的热点问题：水下三维声传播和复杂海洋环境下的水下声传播不确定性研究,并阐述了它在目标探测研究中的应用。最后文章着重讨论了水下声传播的重要应用之一——自适应匹配场处理技术。     

海洋声学环境下水中声源的时延估计法定位精度分析

水中声源的定位精度受到海洋声学环境的重要影响。结合海上试验的实际应用,分析了水下观测平台采用时延估计法对声源的定位精度问题。根据理论分析,计算了时延估计误差、海洋中声速不均匀、平台非稳性、及声传播起伏等因素引起的俯仰角和方位角误差。利用误差传递公式,获得了上述因素引起的不同平台深度下,不同距离声源的定位误差。比较了采用平面阵与立体阵、是否补偿声线弯曲效应等条件下定位误差的变化,并通过海上试验结果进行了部分验证。研究结果表明,海洋声速不均匀对定位误差的贡献最大。采用立体阵代替平面阵、测量海洋声速剖面并补偿声线弯曲引起的定位误差,在1000m距离上可使定位相对误差从最大30%降低到约10%,有效提高了较远距离上的定位精度。研究结果对于采取措施提高水中声源的定位精度有指导意义。     

Direct regressions for underwater acoustic source localization in fluctuating oceans

In this paper, we show the potential of machine learning regarding the task of underwater source localization through a fluctuating ocean. Underwater source localization is classically addressed under the angle of inversion techniques. However, because an inversion scheme is necessarily based on the knowledge of the environmental parameters, it may be not well adapted to a random and fluctuating underwater channel. Conversely, machine learning only requires using a training database, the environmental characteristics underlying the regression models. This makes machine learning adapted to fluctuating channels. In this paper, we propose to use non linear regressions for source localization in fluctuating oceans. The kernel regression as well as the local linear regression are compared to typical inversion techniques, namely Matched Field Beamforming and the algorithm MUSIC. Our experiments use both real tank-based and simulated data, introduced in the works of Real et al. Based on Monte Carlo iterations, we show that the machine learning approaches may outperform the inversion techniques.     

Near-field beamforming analysis for acoustic emission source localization

This paper attempts to introduce a near-field acoustic emission (AE) beamforming method to estimate the AE source locations by using a small array of sensors closely placed in a local region. The propagation characteristics of AE signals are investigated based on guided wave theory to discuss the feasibility of using beamforming techniques in AE signal processing. To validate the effectiveness of the AE beamforming method, a series of pencil lead break tests at various regions of a thin steel plate are conducted. The potential of this method for engineering applications are explored through rotor-stator rubbing tests. The experimental results demonstrate that the proposed method can effectively determine the region where rubbing occurs. It is expected that the work of this paper may provide a helpful analysis tool for near-field AE source localization.     

Decentralized acoustic source localization in a distributed sensor network

The purpose of this work is to investigate acoustic source localization algorithms suitable for use with distributed sensor networks. Traditional sensor networks employ a central controller; however centralized data processing in large-scale sensor networks is not always desirable because of the excessive communication and computational complexity it requires. Therefore, fully distributed localization algorithms are considered. The most important aspect of these algorithms is that they be scalable for use in large sensor networks. The scalability is achieved by forming sensor nodes into groups which collaborate to locate sources. Source locations are determined from time of arrival (TOA) information of the acoustic wave front. Two source location solution methods are used: least squares (LS) and Tikhonov regularized inversion (RI). Experimental results validate the accuracy of a distributed localization approach, and the effectiveness of the LS and RI methods are compared. Additionally, important parameters of the distributed localization algorithm are considered.     

基于波数积分的水声传播建模实现方法研究

研究了基于波数积分的水声传播建模数值实现方法,利用局部系数矩阵的映射,建立了全局系数矩阵,分析了保持数值稳定性的方法。用FFP方法实现了数值积分,并讨论了实现过程中的一些细节。结合仿真实例与基于简正波的模型KrakenC和Kraken的计算结果进行了比较分析。结果表明,波数积分方法在近场计算时更为准确,同时还具有容易扩展到复数域计算衰减的问题、容易求解粘弹性介质中声场的特点。     

不等间距非直线三元阵在水声平面声源被动定位中的应用

根据实际实验环境和布放需求,在对称直线阵被动定位基本理论基础上,推导了不等间距非直线三元阵进行水声被动定位的精确显式公式,将非直线阵形误差角用于修正测距、测向过程,并采用平均法和卡尔曼滤波法对实测数据的中间处理结果和最终结果进行后置处理。海上试验结果验证了算法的正确性,在近距离有效范围内取得较为满意的目标定位结果。     

基于水声信道传播特性实现三元阵三维定位研究

三元阵通常被用来完成测距任务,要实现三维定位需要与其他设备合作或增加阵元数来完成。针对常规三元阵三维定位问题,本文基于水声信道传播特性,通过虚拟阵元实现三元阵的全方位被动三维定位;同时,本文通过对三元阵进行非直线布阵来解决直线三元阵对 轴方向定位的左右模糊问题,实现全方位三维定位。数值分析和仿真表明该方法能够很好的完成三元阵全方位三维定位问题,尤其对浅海近程目标。     

Nonlinear Kalman Filtering for acoustic emission source localization in anisotropic panels

Nonlinear Kalman Filtering is an established field in applied probability and control systems, which plays an important role in many practical applications from target tracking to weather and climate prediction. However, its application for acoustic emission (AE) source localization has been very limited. In this paper, two well-known nonlinear Kalman Filtering algorithms are presented to estimate the location of AE sources in anisotropic panels: the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). These algorithms are applied to two cases: velocity profile known (CASE I) and velocity profile unknown (CASE II). The algorithms are compared with a more traditional nonlinear least squares method. Experimental tests are carried out on a carbon-fiber reinforced polymer (CFRP) composite panel instrumented with a sparse array of piezoelectric transducers to validate the proposed approaches. AE sources are simulated using an instrumented miniature impulse hammer. In order to evaluate the performance of the algorithms, two metrics are used: (1) accuracy of the AE source localization and (2) computational cost. Furthermore, it is shown that both EKF and UKF can provide a confidence interval of the estimated AE source location and can account for uncertainty in time of flight measurements.     

Determination of the best carrier frequency based on the system and environmental parameters in underwater acoustic systems

One of the most challenging features of underwater acoustic (UWA) channel in comparison with its terrestrial radio frequency counterpart is highly frequency-dependent path loss. Thus, utilizing efficient carrier frequencies in UWA systems can considerably reduce the path loss. In this context, this paper presents an approximate formula for determining the best carrier frequency based on both the system and environmental parameters. To achieve this goal, this research first addresses a simple algorithm including general steps for tuning the parameters of Francois and Garrison (FG) formula in the frequency range of 10 to 100 kHz based on the appropriate experimental data which can be acquired from any interest region. Second, for a more accurate modeling of path loss, this paper considers the loss due to the reflections of sound from both the rough surface and bottom of the sea by employing the ray theory. Third, this study presents a general algorithm for modification of the power spectral density (PSD) of ambient noise based on Wenz formula in the frequency range of 10 to 100 kHz and the required experimental measurements which can be simply collected from any interest channel. Moreover, it is mathematically demonstrated that the ambient noise in the frequency range of 10 to 100 kHz, can be generally approximated with a strict sense stationary (SSS) colored normal stochastic process which is ergodic not only in mean and covariance but also in distribution. Finally, an approximate formula for the best carrier frequency is derived by maximizing the sound to noise intensity ratio (SNR). To verify the validity of simplifications and approximations utilized in this study and to assess the performance of our proposed algorithms and formulas, experimental results obtained in the Strait of Hormuz (SoH) are compared with the original, simplified, and modified models under different scenarios.     

A novel location estimation based on pattern matching algorithm in underwater environments

In this paper, we present a novel approach based on pattern recognition to treat the underwater localization. The goal is to achieve underwater localization by the pattern matching algorithm. It should be noted that the reflected signals in underwater environments do not affect our location estimation. Therefore, the underwater localization in this study is straightforward and efficient by using the pattern matching algorithm. We exploit the maximum likelihood (ML) to perform our study. Initially, the underwater signals are collected by the sound receiver at some sampling locations. These signals are suitably processed by the ML models and are stored in database. The test location in real-time is estimated through the database. Experimental results show that good accuracy of positioning can be obtained by proposed schemes. The proposed localization schemes can be applied to many other applications in underwater environments.