激光探测水下声信号的实验研究

在实验室条件下,对于不同频率、不同振动强度的水下声音信号展开激光相干探测研究,建立了基于该方法的实验系统。水表面在水下声音信号作用下产生波动时,用激光照射水表面,其产生的水表面散射光携带了声波信息并与参考光发生干涉,对干涉信号进行采集并处理可得到水下声信号的频率与强度信息。对不同条件下得到的实验结果进行对比分析。实验结果表明,激光相干探测技术可有效地探测水下声信号,并且随着声信号的频率提高、强度减弱,探测效果趋于变差。实验系统采用全光纤光路设计,取得了较好的效果。     

水下声场激光相干探测的实验研究

设计了一套光纤光路探测水下声场的实验系统, 对水下振动进行相干探测。实验结果和特征提取分析表明该系统可对水下振源在水表面激起的横向微波的频率进行实时、准确的监测; 频谱分析和时-频域联合分析结果显示该系统能够实时探测10 Hz到20 kHz的水下声信号。     

中低频水下声信号的激光干涉法探测

基于迈克尔逊干涉仪原理,提出了在非平静水面情况下探测中低频水下声信号的激光干涉方法。利用携带声波信息的散射光和参考光的干涉结果提取水下声信号的频率信息,并进行了理论分析和实验验证,结果表明,激光干涉法可以准确探测出中低频水下声信号的频率信息。     

利用激光探测水下声信号的研究

对激光探测水下声信号可行性进行了研究.水下声信号造成的水表面微扰导致了反射的激光光通量的变化,探测器接收到的光通量的变化频率与水下声信号的频率相同,并给出了探测器位置与接收光通量的关系.     

水下声信号红外激光探测的光线分析

水下声信号在水-空气界面会引起表面波动而对打在水表面的激光进行调制。利用直接光强检测方法可以检测到受水下声信号调制的激光信号,本文用光线分析理论模型证明了利用激光进行水下声波探测的可行性。     

水下声信号激光探测技术研究

水下声信号激光探测技术采用了激光接收技术。它在空气中利用光波,而在水中利用声波,把两种最佳的信道和物理场结合了起来,是遥感探测水下声信号的一种比较理想的方法。水下声信号在水空气界面会引起表面波动而对打在水表面处的激光束进行幅度调制。利用直接光强检测方法可以检测受水下声信号调制的激光信号。本文在理论分析的基础上通过试验验证了激光探测水下声信号技术的可行性,同时对水下声信号光电探测存在的问题进行了探讨并提出了相应的解决途径。     

激光空中探测水下目标的新方法研究

为了实现在空中利用激光技术对水下目标进行探测的目的,基于迈克尔逊干涉仪的基本原理,提出了一种从水面散射激光中获取水下声源信息的新方法。设计并实现了一套空中探测水下声信号的实验装置。实验结果表明：频谱分析图中的峰值频率即为水下声源的发声频率,系统能够实时探测发声频率在1 kHz～14 kHz的水下声源,且测量标准偏差小于7 Hz。该方法为航空遥感水下目标提供了一条新的技术途径。     

水下声信号光电探测技术的实验研究

为了实现水下声信号的遥感探测,针对水下声信号光电探测技术的强度调制理论,提出了光线分析理论模型,并进行了初步的理论分析和实验验证,取得了频率为65Hz和100Hz的水下声信号的探测数据,验证了水下声信号光电探测技术的强度调制理论.实验结果表明,在空气中利用激光,在水中利用声波,通过这两种信号载体来探测水下声信号技术是可行的,这一结果对于水下声信号光电探测技术的研究具有一定的参考价值.     

水下目标的激光双波段探测技术

研究了一种采用蓝绿波段激光、红外波段激光相结合的水下双波段激光探测技术,分析了红外波段激光击穿水辐射声波应用于水下探测的基本模式、探测特点及声信号的激发机理,实验研究了激光声信号的强度、波形、频谱等特性.实验结果表明,双波段激光复合探测模式可将空中光信道、水中声信道结合起来,具有强大的技术优势;激光声信号应用于水下探测,具有优良的脉冲特性及频谱特征.研究结果有助于推动激光在海洋中的探测应用.     

机载激光水下探测技术

机载激光探测技术片６０年代中后期在美国、澳大利亚等国率先出现后，得到了比较迅速的发展，它与传统的声纳探测技术相比，具有战术性强、探测速度快、特别适用于近海水域探测等优点。     

一种水声信号的模拟研究和检测

为了实现对水下目标的定位,提出一种CW信号与LFM信号组合的水声信号机制,并完成了模拟检测。该信号机制中CW信号用于测距,LFM信号用于测深。一组帧信号与三组行信号组合,共同完成目标定位,并且有效减小误差。仿真结果表明,该信号机制在水声信道中能有效的传输,被检测及实现定位要求。     

Optimized deep learning driven signal detection and adaptive channel estimation in underwater acoustic IoT networks

Nowadays, multiple input multiple outputs with orthogonal frequency division multiplexing (MIMO-OFDM) provide better communication performance that can be applied to the fast-growing Internet of Things (IoTs). In underwater IoT, information fades away rapidly due to varying water conditions. Therefore, the MIMO model can be applied to the OFDM acoustic system, enabling high-speed data transmission without affecting the channel effectively. However, detecting the underwater signal and estimating the channel is highly necessary for enhancing underwater acoustic communication (UWAC). Recently, many techniques have been introduced for effectively performing signal detection and channel estimation. However, those techniques face high time complexity due to increased channel interferences and noises during data transmission. Hence, this article brings a novel technique for SD and CE for the UWAC-IoT-enabled MIMO-OFDM system. An adaptive recursive least square (ARLS) technique is proposed in this study for CE that aids in evaluating the acoustic channel parameters effectively. For performing SD, a bi-directional deep pelican convolutional neural network (BDPCNN) technique is introduced to ensure the presence and absence of signals at the receiver end. The proposed method is analyzed via the MATLAB platform, and the performances are analyzed under different water types like turbid water, coastal water, clear ocean water, and pure seawater. Different performance metrics like bit error rate (BER), mean square error (MSE), energy efficiency (EE), and time complexity are analyzed with different existing techniques. The experimental section obtains the BER of 0.0086, 0.013, 0.017, and 0.021 for turbid, coastal, clear, and pure seawater, respectively.     

Enhancement of underwater acoustic signal based on denoising automatic-encoder

Aiming at the difficulty of feature extraction of echo signal in active sonar,a self-encoder algorithm based on the combination of denoising self-encoder and convolution denoising self-encoder was proposed.Firstly,the preprocessing of noisy signal was carried out by using the advantage of denoising self-encoder in signal as a whole,and then the local feature of signal was optimized by combining convolutional denoising self-encoder to denoise the signal locally,so as to enhance the signal.The time domain waveform of the received signal is used as the feature input by the algorithm,and retains the signal’s amplitude and phase characteristics.The experimental results show that the algorithm not only effectively reduces the noise component in the signal,but also achieves better recovery effect in both time and frequency domains.     

基于支持向量机的水声信号多分类器设计

目标分类器是水下目标自动识别系统的重要组成部分,目前水下目标分类的方法主要有统计分类、神经网络和专家系统等三大类的分类方法。支持向量机（SVM,Support Vector Machine）是根据统计理论提出的一种新的算法,该算法具有良好的泛化性能,不仅对训练样本的分类性能较好,对未知的检验样本同样具有好的分类效果,特别适用于小样本数据的分类。本文将该算法推广至多分类情况,并对三类水声信号样本进行分类试验。实验结果表明,该算法可以有效的避免“维数灾难”问题,且分类正确率高于传统的神经网络分类器。     

水下目标在被追踪过程中的声反射信号模拟

为模拟水下目标在被追踪过程中的声反射信号,根据鱼雷和目标的运动方程,采用尾追法进行弹道分析,研究鱼雷追踪目标的轨迹,同时根据鱼雷与目标的距离,生成不同自导信号形式,并通过计算得到反射信号的多普勒频偏和信号强度,最终将数字信号转换为模拟信号供实验室测试,或为其他任务提供模拟信号,对水下目标的设计及研制具有重要作用。     

基于PCI8602的水声信号监测系统设计

为了提高水声信号监测效果和能力,设计了一种基于PCI8602数据采集卡和LabVIEW编程软件的靶标水声信号监测系统。系统采用RHSA20标准水听器为前端传感器,连接信号调理模块,以PCI8602数据采集卡为核心硬件,通过LabVIEW编程软件快速实现对水声信号的实时数据采集、显示与存储,可满足对水声信号的监测需求。     

Multiuser detection in a horizontal underwater acoustic channelusing array observations

We present a multisensor, multiuser receiver that is capable of operating in an underwater acoustic channel with severe multipath. For each active user, the receiver consists of a multi-input, single-output array processing filter followed by a single-channel adaptive equalizer. The array processing filter is chosen to maximize an averaged performance metric which measures reduction in the interference from multiple asynchronous cochannel users and the reduction in intersymbol interference caused by time spreading of the transmitted signal. The single-channel adaptive equalizer that follows the array processing filter eliminates the remaining intersymbol interference prior to hard symbol decisions. The division of labor between the array processing filter and single-channel equalizer reduces receiver complexity by allowing the array processing filter weights to be based on the fixed deterministic channel component and the single-channel equalizer to be based on the stochastic channel component. Receiver performance is demonstrated using data obtained from two shallow-water acoustic channels where two cochannel users are transmitting in shallow water at 18 and 30 nautical miles from the receiver array     

Vertical and horizontal synchronization services with outlier detection in underwater acoustic networks

Underwater Acoustic Networks (UANs) have important applications in ocean exploration and lake pollution monitoring. UANs are however different from terrestrial sensor networks due to their highly variable, long propagation delay, and mobility. Clock synchronization is an important protocol to achieve timing‐based sensor communications. In this paper, we propose a three dimensional, scalable UAN time synchronization scheme that can achieve both horizontal (i.e., in the same water depth) and vertical (i.e., from bottom up to the surface) clock synchronization to overcome the effects of long acoustic delay. To secure UAN clock synchronization services, we also propose a two‐step security UAN synchronization model: (1) correlation test and (2) statistical reputation and trust model. The proposed model can detect outlier timestamp data and identify nodes generating insider attacks. Copyright © 2007 John Wiley & Sons, Ltd.     

水下目标激光周向扫描探测模型与仿真分析

蓝绿激光在水下目标精细探测中具有重要的应用前景。基于端面圆周的快速数值遍历算法,通过建立扫描光束与运动目标的交会方程,对水下目标的激光扫描探测过程进行了数值建模。结果表明:目标穿越光束扫描区的最短时间并非出现在迎头相遇的交会情况中。其次,通过采用蒙特卡罗模拟,仿真分析了脉冲频率、扫描频率、扫描半角以及目标距离对探测概率的影响,并得出扫描参数的最优设计。文中建立的数值模型可为水下激光探测系统的合理设计提供理论依据。