一种水下未知声源定位方法的研究

随无线传感器网络技术快速发展,基于传感器网络的水下定位系统被广泛提出;然而,降低节点成本、降低节点功耗成为该技术走向实用化发展的关键所在;通过将传感器网络技术和声波传播衰减原理相融合,进一步建立新的基于传感器网络的水下未知声源定位方法数学模型,并通过实测水下声源与计算机仿真相结合,分析了该模型受反射波、环境噪声和噪声源距离变化影响程度,验证其可行性,提出系统误差修正方法。     

Development of a new underwater positioning system based on sensor network

In those days, the performance of underwater robot is improving because requirements for it are becoming higher and more complex than before. For those work, a highly precise and wide regional underwater positioning system is indispensable. However, the conventional positioning system that has three standard stations, is applicable for the field with no obstacle, because its principal depends on the time based measurement. Therefore, we developed a new underwater positioning system based on sensor network technology that is using a lot of standard stations equipping hydrophone and GPS sensor on the water surface. And decreasing the cost of sensor, we applied a simple method for measurement of distance, which is using sound power level. Therefore, this study has started with confirming the new principal for underwater positioning method. This paper is showing the availability with theoretical analysis and the performance of new method under the noise and reflection of sound in the water, and suggestions for the measures and an error compensation method. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Development of a new positioning system for underwater robot based on sensor network

We are developing a new positioning system for an underwater vehicle based on the sound power decreasing with the distance transmitted and sensor network technology. Conventional positioning systems use the difference between the time sound occurs at the station and the time it is received at a vehicle. However, this is very expensive because of the high operational costs and the fact that the measuring field is not very wide. We therefore need a new positioning system with low cost, easy operation, easy maintenance, and high accuracy. Our system is expected to satisfy such requirements. At the first stage, we confirmed the principle with theoretical and experimental methods. In the research, we considered only the direct waves in the received data. These showed good precision for short distances, but also showed that it was easily affected by reflected waves, and the positioning area was limited to within only a few hundred meters when a reflective surface existed near to the receiver. These results were reported at AROB2008. Therefore, in the second stage of this study, we tried a new idea that uses a low-frequency sound and sends plural-frequency sounds simultaneously. We then tried to assess the performance of this method. This article gives the results of the simulation and the water tank experiment. With these improvements, the influence of reflected sound was suppressed and the positioning area became larger than in previous research. Then the underwater positioning system using sound power transmission loss will become useful.     

水声传感器网络中的节能路由协议改进算法

在大规模三维水声传感器网络中,针对节点能耗和网络传输效率的问题,本文基于节点定位和LEACH算法,提出了一种适用于水声通信传感器网络路由算法,该算法采用定位、聚类、唤醒和排列的思想,首先通过定位,确定节点的位置信息,再通过聚类方法,使水下的节点分成不同的簇,形成节点休眠及唤醒的单元.在数据通信过程中,通过及时唤醒簇单元,使需要利用的簇节点及时被唤醒,处于活跃状态,而暂时不被需要的节点进行休眠,从而达到节能的效果.而在簇内传输时,考虑了节点的剩余能量信息,选择最优节点进行信息传输.仿真实验表明,该算法能够提高网络的整体寿命时间.     

基于区域划分自适应粒子群优化的超短基线定位算法

为了降低由声速不确定引起的水下声学定位误差,提出一种基于区域划分自适应粒子群优化的超短基线定位算法.该算法将声速作为未知量,利用冗余的定位信息构建定位模型,针对标准粒子群算法收敛速度慢及容易早熟的问题,采用区域划分的方法动态调整粒子的惯性权重和学习因子,达到寻优能力与收敛速度的平衡,并引入自适应变异操作避免种群陷入局部最优解.仿真实验表明,所提出的算法能够有效提高声速未知情况下超短基线系统的定位精度.     

New acoustic positioning system for an underwater robot using multiple frequencies

Nowadays, robots are used for many types of underwater work, and knowing their position accurately is very important. Conventional positioning systems are based on the time difference or phase lag of sound waves. However, such systems are complex and expensive, and real-time positioning is difficult and not very accurate. We propose a new system using the loss of sound propagation and a sensor network. In a previous study, we separated directly arrived waves from received waves and measured their amplitude or power. Using this data, we calculated the distance. However, the signal included many types of reflected wave, and we were not able to obtain a correct value over long distances where the direct waves cannot be separated from the influence of the reflected waves. In this study, we propose a new method based on sounds at multiple frequencies. This method uses sounds of several different frequencies, and sends them sequentially at constant intervals. The distance can be calculated by taking the average power of the signals received. The advantage of this method is that it is not necessary to use any separating process, and longer distances can be measured.     

一种基于反光带方案的ARV对接视觉定位算法

针对自主遥控潜水器（ARV）近距离水下对接面临的定位方法效果不佳、定位信息误差较大等问题,设计了一种基于反光带方案的水下视觉定位算法。首先提出一种基于Q学习的混合鲸鱼优化算法（QHWOA）来提高算法的收敛精度和收敛速度,并以中继器对接口外布置的反光带为目标,利用QHWOA算法优化Otsu目标函数分割对接图像;然后提出基于PCA（主成分分析）降维法的关键点提取算法来提取关键轮廓与关键点;最后采用SRPnP算法解算ARV与中继器的相对位姿。通过水下对接实验进行关键点像素提取误差和视觉定位误差的计算,结果表明定位误差满足水下对接的精度要求。该算法能够在ARV水下对接时输出有效定位信息,引导ARV与中继器对接。     

基于梯度差的声速剖面自适应分层算法

声速剖面表示声速与深度的函数关系,常用于水声定位,以纵轴表示海深,横轴表示声速。针对高精度水声定位系统中定位精度与计算量相互矛盾的问题,提出一种声速剖面自适应分层算法。该算法根据声速在有限范围内规律变化的特点,对声速剖面逐层搜索。通过声速层之间声速变化梯度差情况找出声速变化的节点,保留原始声速剖面特征,实现对声速剖面的简化。仿真实验结果表明,根据阈值选取的大小,算法自适应分层处理后对原声速剖面的精简可达70%。在选取合适阈值时,与D-P算法相比可以获得更小的定位误差,具有良好的工程应用价值。     

水下基于层级的约束加权最小二乘时差定位

针对距离无关定位算法与距离相关定位算法中定位精度的问题,分析了误差对定位性能的影响及影响误差的因素,在最小二乘定位算法的基础上,提出了一种基于层级结构的约束加权最小二乘时差定位算法。该算法利用AUV( Autonomous Underwater Vehicle)对水下节点进行分层,使得具有层级和深度信息的信标节点升降至未知节点所在平面,从而将三维定位转换为二维定位,降低了算法的复杂度,同时避免了距离未知节点较远的信标节点对定位的影响,提高了测距精度,使定位误差进一步降低。仿真结果表明,该算法在位置误差较小的情况下,可以明显地提高定位精度。     

基于洋流模型的水下传感器网络实时定位算法

针对近海监控领域内水下传感器网络的节点随着海洋运动具有流动性的问题,提出了基于洋流模型的水下传感器网络实时定位算法(RTLC).利用洋流模型表示节点的运动模型消除流动性对定位造成的影响,成功模拟了节点在水中的移动速度.通过卡尔曼预测方法结合观测值与估计值优化运动模型,使其更贴近节点运动规律.采用信息记录机制及列表更新机制保证信息的时效性从而提高了定位准确度.通过仿真分析,RTLC算法性能优于基于移动预测的大规模水下传感器网络可扩展定位算法(SLMP),具有较高的定位覆盖度,较低的平均定位误差及平均通信能耗.     

Cooperative localization and evaluation of small-scaled spherical underwater robots

With the goal of supporting localization requirements of our spherical underwater robots, such as multi robot cooperation and intelligent biological surveillance, a cooperative localization system of multi robot was designed and implemented in this study. Given the restrictions presented by the underwater environment and the small-sized spherical robot, an time of flight camera and microelectro mechanical systems (MEMS) sensor information fusion algorithm using coordinate normalization transfer models were adopted to construct the proposed system. To handle the problem of short location distance, limited range under fixed view of camera in the underwater environment, a MEMS inertial sensor was used to obtain the attitude information of robot and expanding the range of underwater visual positioning, the transmission of positioning information could implement through the normalization of absolute coordinate, then the positioning distance increased and realized the localization of multi robot system. Given the environmental disturbances in practical underwater scenarios, the Kalman filter model was used to minimizing the systematic positioning error. Based on the theoretical analysis and calculation, we describe experiments in underwater to evaluate the performance of cooperative localization. The experimental results confirmed the validity of the multi robot cooperative localization system proposed in this paper, and the distance of cooperative localization system proposed in this paper is larger than the visual positioning system we have developed previously.

     

AUV辅助的水下传感器网络时钟同步算法

针对当前水下传感器网络中的时钟同步难题,设计了一种三元阵被动定位自主水下航行器（ AUV）模型,并基于此模型提出了AUV辅助的时钟同步（ AUV-Sync）算法。该算法通过AUV与节点之间相对运动过程中进行的信息交换来对节点相对距离进行估计,进而基于相对距离计算单向传播时延来降低由于节点移动性所导致的误差。最后,通过两轮加权最小二乘法进行线性回归来估计时钟同步的参数。仿真结果表明：在存在节点漂移的动态水下传感器网络环境中,该算法较其他相关算法有更高的精度。     

基于距离重构的无线传感器网络多维定标定位算法

无线传感器网络中基于多维定标的定位算法通常采用最短路径代替距离矩阵中的未知项,会导致较大的定位误差。针对这一问题,提出一种基于距离矩阵重构的无线传感器网络多维定标定位算法DR-MDS。算法利用节点间的公共邻居信息对距离矩阵线性重构,计算距离矩阵中的未知项,然后对重构的距离矩阵运用双中心化并进行特征分解,从而求得网络坐标。由于算法能够更为准确的获得网络节点之间的空间相对关系,并充分利用其空间相关性计算节点相对坐标,可获得较好的定位效果。仿真结果表明,本文提出的DR-MDS算法与MDS-MAP、ISOMAP相比定位精度更高,误差范围更小。     

面向海洋监测的水声传感器网络节点定位算法

为解决面向海洋监测应用的大规模水声传感器网络的节点定位问题,首先,采用整数线性规划理论,提出了多目标约束的水面网关优化部署策略;其次,针对水声传感器网络不同节点的特点,设计不同的定位方案,提出了有预测性的水声传感器网络节点部署算法。仿真实验验证了该方法的可行性与有效性,结果表明,该算法能明显提升节点的定位范围,降低通信能耗,减小定位误差,为水声传感器网络的海洋大规模部署提供相应技术指导。     

水声对抗仿真系统研究的新思路及其应用

结合水声对抗系统的建设,我们进行了水声对抗仿真系统的研究。根据先期研制声诱饵仿真系统的经验教训,紧扣仿真的实质,提出了水声对抗仿真系统研究中采用的一些新思路,其中包括仿真合成环境、信号处理异地化以及信道变化律等。文章详细描述了它们的内容和应用思路,并分析了它们的合理性。     

基于改进加权最小二乘支持向量机的UWSN定位

针对水下无线传感器网络锚节点较少、迭代误差大导致的节点定位精度低的问题,提出一种基于改进加权最小二乘支持向量机的水下三维节点定位算法;该算法将水下三维空间分为若干立方体,以锚节点与网格交点的距离向量作为训练集进行训练;并利用改进的多类别模式识别方法进行分类,以未知节点到锚节点的距离向量作为测试集确定节点坐标;通过引入加权的思想和多类别模式识别方法增大机器学习算法的鲁棒性、降低分类次数,从而实现水下三维节点预测定位;仿真结果表明,该算法在锚节点较少、网络区域较大的水下仍能保持较高的定位精度与较好的鲁棒性.     

结合极大似然距离估计的MDS-MAP节点定位算法

基于多维定标的定位算法通常利用节点间的最短路径长度代替欧式距离构建距离矩阵,当网络拓扑结构不规则时,会导致较大的定位误差。针对这一问题,提出了一种结合极大似然距离估计和多维定标的节点定位算法MDS-MAP（MLE）。算法将待测节点的一跳邻居节点信息作为极大似然方法的输入,利用与邻居节点的距离信息计算待测节点的相对坐标,然后根据已知锚节点的坐标,将所有节点的相对坐标映射为绝对坐标。实验结果表明,针对规则网络和不规则网络,MDS-MAP （MLE）算法均可取得较好的定位精度,且当网络连通度在一定范围内变化时,定位误差可保持在较低的稳定区间内。     

Modulated opto-acoustical sounding of the upper ocean

We analyse a new optical method to detect and utilize underwater acoustic signals from above the ocean surface. The method is based on scattering of modulated laser light by natural inhomogeneities (hydrosoles, bubbles, turbulence, etc.) whose concentration oscillates in a vertically propagating sound wave. Measurement of the Doppler shifted modulation frequency in the scattered light may be used both for monitoring of the upper ocean sound speed profile and for communication with underwater objects.     

非合作信标条件下水下无线传感网可靠定位技术

传统假设水下无线传感器网络的传感器节点和信标节点都是合作的,但是在军事应用等特殊场合下,某些节点容易被敌方捕获或入侵,因而水下无线传感网络中有时会存在一些非合作的恶意节点。针对存在若干非合作信标的水下无线传感器网络定位应用,提出了一种非合作信标节点约束下水下无线传器网的可靠节点定位算法。本文算法利用一跳邻居范围内信标节点独自投票机制实现对非合作信标的判决与剔除,从而减少由于存在非合作信标节点对定位误差的影响,同时也分析了不同比例非合作信标下的定位误差界限。仿真结果验证了本文提出的算法相比传统定位算法,在平均定位精度和定位覆盖率等方面都有所提高。     

基于无线传感网络的水质在线移动监测系统

针对静态离线水质监测方法存在采样误差大、监测频次低、监测数据分散以及无法实时反馈水质状况的连续动态变化等问题,研发了基于无线传感网络的水质在线移动监测系统.该系统由水下监测器、浮标节点和可视化软件组成.水下监测器模仿金枪鱼外观设计,内部装备水质传感器(温度、pH、浊度和电导率等)用于获取水质参数信息;浮标节点采用太阳能供电方式,负责接收、处理、中继及转发来自多个水下监测器的数据;多个水下监测器之间,水下监测器与浮标节点之间采用170 MHz无线射频模块或水声通信,浮标节点与岸边基站采用ZigBee通信;可视化软件包括上位机与移动终端.本系统的实施解决了传统人工取样监测的局限性,实现水域任意点的水质在线监测.