Geometric distortions in side-scan sonar images: a procedure fortheir estimation and correction

A procedure is introduced for the estimation and correction of geometric distortions frequently observed in side-scan sonar images as a result of motion instabilities of the sonar towfish. This procedure estimates geometric distortions from the image itself, without requiring navigational or altitude measurements. Estimates of the local degree of geometric distortion are obtained by cross-correlating segments of adjacent lines of the image. A mathematical model for the distortions is derived from the geometry of the problem and is applied to these estimates to reconstruct the sampling pattern on the seabed, under the assumption of a planar bottom. The estimated sampling pattern is then used for resampling the image to correct the geometric distortions. The model parameters may also be used for calculating approximate estimates of the attitude parameters of the towfish. A simulation is employed to evaluate the effectiveness of this technique and examples of its application to high-resolution side-scan sonar images are provided     

High-resolution deep-tow survey imagery,Gulf of Mexico

Data are presented from a commercially available deep-tow 100-kHz side-scan sonar and 3.5-kHz subbottom profiler acquisition system. The towfish is a positively buoyant vehicle referenced to the seafloor with an anchor chain deadweight. This enables the acoustic sources and receivers to be towed at a constant altitude of 30 to 35 m above the seafloor. The records illustrate a capability for imaging deep-water seafloor morphology and near-surface sediments to water depths of 2200 m in the Gulf of Mexico.     

Sea-bed characterisation and classification from the power spectra of side-scan sonar data

This work is concerned with the automatic characterisation and classification of the sea-bed for side-scan sonar trace power-spectra.A parametric model of side-scan sonar trace power-spectra is developed from the equation for the magnitude frequency response of a Butterworth filter. The model's parameters are optimised to give a least squares fit with observed spectra. Three of the optimised parameters are used to define features.     

联合小波和NLM滤波的侧扫声纳回波信号降噪

为进一步降低侧扫声纳回波信号中非高斯分布的乘性噪声,获取更佳效果的侧扫声纳图像,提出了一种利用小波和NLM(nonlocal means)滤波的组合降噪方法.首先采用同态变换将侧扫声纳回波ping信号中的乘性噪声转换为加性噪声,然后利用小波阈值和NLM滤波对侧扫声纳每ping回波数据实施降噪处理,最后经过小波反变换和指...     

侧扫声纳和浅地层剖面仪在海管断裂点定位中的应用

结合侧扫声纳和浅地层剖面仪能够探测出海底管道附近异常,路由区浅层地质灾害以及海底管道位置等特点,通过实例探讨了侧扫声纳和浅地层剖面仪在海底管道断裂位置定位中的应用。船锚、浅层气等外力作用,导致海底油气管道断裂,使用侧扫声纳和浅地层剖面仪探测的方法,综合分析海水中的气体屏蔽现象、海底面的地貌异常特征、海底管道的平面位置及埋深变化、地层剖面的反射空白等异常特征,快速准确定位海底油气管道断裂位置。     

国内外侧扫声纳测量标准比较研究

由于侧扫声纳应用领域不断扩大,用户要求不断提高,国际海道测量组织和世界测量技术发达国家相继发布了各自的新版测量规范和标准。本文将我国侧扫声纳现行测量标准与国际相关标准在系统探测能力、测线布设、数据采集、质量控制等方面进行比较详细的分析比较,指出了我国侧扫声纳测量规范在测线布设、数据采集要求等方面的不足,旨在推进我国测量标准尽快实现与国际接轨。     

Fault scarp identification in side-scan sonar and bathymetry images from the Mid-Atlantic Ridge using wavelet-based digital filters

Digital filters designed using wavelet theory are applied to high resolution deep-towed side-scan sonar data from the median valley walls, crestal mountains, and flanks of the Mid-Atlantic Ridge at 29°10 N. With proper tuning, the digital filters are able to identify the location, orientation, length, and width of highly reflective linear features in sonar images. These features are presumed to represent the acoustic backscatter from axis-facing normal faults. The fault locations obtained from the digital filters are well correlated with visual geologic interpretation of the images. The side-scan sonar images are also compared with swath bathymetry from the same area. The digitally filtered bathymetry images contain nine of the eleven faults identified by eye in the detailed geologic interpretation of the side-scan data. Faults with widths (measured perpendicular to their strike) of less than about 150 m are missed in the bathymetry analysis due to the coarser resolution of these data. This digital image processing technique demonstrates the potential of wavelet-based analysis to reduce subjectivity and labor involved in mapping and analyzing topographic features in side-scan sonar and bathymetric image data.     

Enhanced Kalman Filter Algorithm Using the Invariance Principle

Target tracking in multistatic active sonar systems is often limited in shallow-water environments due to the high level of bottom reverberation that produces false detections. Past research has shown that these false alarms may be mitigated when complete knowledge of the environment is available for discrimination, but these methods are not robust to environmental uncertainty. Recent work has demonstrated the existence of a waveguide invariant for active sonar geometries. Since this parameter is independent of specifics of the environment, it may be used when the environment is poorly known. In this paper, the invariance extended Kalman filter (IEKF) is proposed as a new tracking algorithm that incorporates dynamic frequency information in the state vector and uses the invariance relation to improve tracker discrimination. IEKF performance is quantified with both simulated and experimental sonar data and results show that the IEKF tracks the target better than the conventional extended Kalman filter (CEKF) in the presence of false detections.      

侧扫声纳探测技术的研究现状及发展

侧扫声纳是海洋地形地貌测量的必备仪器之一。主要介绍了侧扫声纳探测技术的研究现状,重点阐述了其最新研究进展,给出了侧扫声纳技术未来的发展趋势。针对国内外实际应用需求,提出了几点建议,以期为我国侧扫声纳技术相关研究提供参考。     

基于虚警函数的侧扫声纳水下目标实时检测方法

研究了侧扫声纳系统进行水下目标探测过程中目标信号的检测问题。通过分析海底回波信号的统计模型及其参数的估计,讨论了目标信号对统计模型拟合的影响规律,提出了侧扫声纳回波信号虚警函数和虚警率的概念,及其对Ping信号中目标信号的检测方法。算例结果表明,回波信号的三种分布模型中K分布拟合程度最优,在相同虚警率的条件下,基于K分布的虚警函数目标检测率最高。该法可为侧扫声纳回波信号中目标的实时报警提供技术支撑。     

Active learning for detection of mine-like objects in side-scan sonar imagery

A data-adaptive algorithm is presented for the selection of the basis functions and training data used in classifier design with application to sensing mine-like targets with a side-scan sonar. Automatic detection of mine-like targets using side-scan sonar imagery is complicated by the variability of the target, clutter, and background signatures. Specifically, the strong dependence of the data on environmental conditions vitiates the assumption that one may perform a priori algorithm training using separate side-scan sonar data collected previously. In this paper, a novel active-learning algorithm is developed based on kernel classifiers with the goal of enhancing detection/classification of mines without requiring an a priori training set. It is assumed that divers and/or unmanned underwater vehicles (UUVs) may be used to determine the binary labels (target/clutter) of a small number of signatures from a given side-scan collection. These sets of signatures and associated labels are then used to train a kernel-based algorithm with which the remaining side-scan signatures are classified. Information-theoretic concepts are used to adaptively construct the form of the kernel classifier and to determine which signatures and associated labels would be most informative in the context of algorithm training. Using measured side-looking sonar data, the authors demonstrate that the number of signatures for which labels are required (via diver/UUV) is often small relative to the total number of potential targets in a given image. This procedure designs the detection/classification algorithm on the observed data itself without requiring a priori training data and also allows adaptation as environmental conditions change.     

基于数学形态学的侧扫声呐图像轮廓自动提取

侧扫声呐图像特征自动提取的难点在于特征地貌边缘检测较困难,依据图像灰度突变检测得到的边缘比较粗糙、不连续,而且有断口和小洞。本文在对图像进行预处理和阈值化的基础上,采用数学形态学方法对图像进行处理,即用具有一定形态的结构元素去量度和提取图像中的对应形状,得到连续化、粗化、圆滑的特征区域边缘填充目标内部阴影且消除背景噪声。基于数学形态学的侧扫声呐图像特征自动提取的主要步骤为:首先对侧扫声呐图像进行预处理,然后进行灰度阈值化,接着采用数学形态学方法进行处理,最后对处理后的图像进行边缘检测,提取出特征地貌边缘。实验表明,采用数学形态学方法进行处理后,错断、离散的海底目标物变得连续,背景噪声大大减少,自动提取结果准确可靠。     

A processing requirement and resolution capability comparison ofside-scan and synthetic-aperture sonars

The processing requirements and resolution capabilities of both side-look sonar (SLS) and synthetic-aperture sonar (SAS) systems are outlined. Side-look sonar is presented as a real-beam imaging technique along with expressions for relevant system- and image-related parameters. Synthetic-aperture sonar is discussed, and the limitations imposed by the speed of sound in the ocean environment are identified. A specific side-look system (SeaMARC I) is presented under two configurations and comparable SAS designs are proposed. Based on the examples provided by the SeaMARC I system and the hypothetical SAS designs, it is shown that single-beam SAS systems can be designed to achieve area coverage rates comparable to single-beam side-scan systems, yet with improved azimuth resolution     

小波函数对侧扫声纳图像滤波效果的影响分析

侧扫声纳技术应用日益广泛,已成为海洋测量的重要工具,而去除噪声处理是对侧扫声纳图像进行正确判读的前提。利用小波函数滤波处理的方法,分别采用Haar、Daubechies、Coiflets、Symlets、Discrete Meyer、Biorthogonal、Reverse Biorthogonal等小波函数与中值滤波函数对侧扫声纳图像进行处理,并以平滑指数和边缘保持指数为评价指标,对滤波效果进行定量比较。试验表明,小波函数可以有效地平滑声纳图像,并能保持其较好的边缘效果。     

基于DIDSON的未知海域覆盖规划算法

针对自主水下机器人的路径规划问题,提出一种基于双频识别侧扫声呐(DIDSON)的全局路径规划算法。根据双频识别侧扫声呐的物理特性对AUV进行数学建模,根据声呐的工作频率不同,将AUV分为高频、低频两种工作模式。高频模式下成像精度高,低频模式下成像范围大。文中提出了一种D2-CPP算法,根据声呐返回的识别结果,算法会自主切换AUV的工作模式,并动态规划出对应的路径点,直到覆盖所有区域。通过与割草机算法的仿真对比,证明了算法的有效性,近海实验证明了算法的可靠性。     

XTF格式侧扫声纳数据质量评价

通过深入分析XTF格式侧扫声纳数据结构,选取了XTF格式侧扫声纳数据中的定位信息、时间信息、信号强度、船速、测线平直度及数据完整性6个要素作为质量评价指标,开发了XTF格式侧扫声纳数据质量评价软件系统,实现了对批量XTF格式侧扫声纳数据的计算机自动质量评价,具有较强的实用性。     

基于CT非线性模型的水下目标跟踪算法比较

针对水下目标跟踪非线性跟踪精度问题,假设目标机动模型为恒转速运动模型,贝叶斯框架下,因扩展卡尔曼滤波跟踪方法进行模型在估计点的泰勒展开,忽略一阶以上高阶项,存在模型误差,比较了扩展卡尔曼滤波、无迹卡尔曼滤波、容积卡尔曼滤波在高斯噪声干扰下滤波误差均方根,以及3种方法运行时间。仿真证明,非线性系统下状态维度为5,容积卡尔曼滤波跟踪的精度高于无迹卡尔曼滤波,无迹卡尔曼滤波高于扩展卡尔曼滤波。该研究为海上目标非线性测量系统提供仿真实例,为进一步滤波算法改进提供基础。     

Curvelet变换域侧扫声纳图像增强算法

针对海底侧扫声纳图像对比度低、纹理弱、噪声严重等问题,提出了一种基于第二代Curvelet变换的声纳图像增强算法。首先对原始声纳图像进行多尺度、多方向的Curvelet变换分解,得到低频子带和高频子带;然后引入非线性S型函数对低频系数进行处理,提高图像整体的对比度;采用一种可以避免过度增强的新型非线性函数对各尺度的高频子带系数进行处理,提高图像整体的对比度,增强图像边缘和纹理细节,并通过估计噪声水平设定阈值进行阈值降噪。最后经Curvelet逆变换得到增强图像。实验表明,该方法不仅改善了海底侧扫声纳图像对比度低的问题,而且降低了噪声,突出了声纳图像的边缘和纹理细节。     

Automatic Registration of TOBI Side-Scan Sonar and Multi-Beam Bathymetry Images for Improved Data Fusion

Deep towed side-scan sonar vehicles such as TOBI acquire high quality imagery of the seafloor with very high spatial resolution but poor locational accuracy. Fusion of the side-scan sonar data with bathymetry data from an independent source is often desirable to reduce ambiguity in geological interpretations, to aid in slant-range correction and to enhance seafloor representation. The main obstacle to fusion is accurate registration of the two datasets.The application of hierarchical chamfer matching to the registration of TOBI side-scan sonar images and multi-beam swath bathymetry is described. This matches low level features such as edges in the TOBI image, with corresponding features in a synthetic TOBI image created by simulating the flight of the TOBI vehicle through the bathymetry. The method is completely automatic, relatively fast and robust, and much easier than manual registration. It allows accurate positioning of the TOBI vehicle, enhancing its usefulness as a research tool. The method is illustrated by automatic registration of TOBI and multi-beam bathymetry data from the Mid-Atlantic Ridge.     

基于K-means聚类与数学形态学的侧扫声呐图像目标轮廓自动提取方法

针对侧扫声呐图像斑点噪声强、背景海底散射干扰严重,海底目标轮廓自动提取困难的问题,提出了一种基于K-means聚类与数学形态学相结合的海底目标轮廓自动提取算法。为克服噪声干扰,该算法首先利用中值滤波去除侧扫声呐图像中的强斑点噪声;然后采用K-means聚类算法对侧扫声呐灰度图像进行分割,并二值化,除去大部分海底背景噪声,初步提取出目标;接着利用数学形态学运算去除提取结果中的孤立噪点,并填充目标内部孔洞,得到连续化、圆滑的目标边缘;最后对处理后的侧扫声呐图像进行边缘检测,提取出目标轮廓。实验结果表明:该算法思想简单易行,具有很强的克服背景噪声的能力,自动提取的目标轮廓连续性较好,结果准确可靠。目前,在侧扫声呐图像目标轮廓提取过程中,主要采用人工方式,自动性较差,效率较低。本文算法可以实现目标轮廓的自动提取,提高效率,具有较强的实用价值。