实孔径成像声纳在海底油气管线探测中的应用

利用成像声纳对油气管线进行探测,是重要的声学测量技术手段之一。侧扫声纳和环扫声纳是两种典型的实孔径成像声纳,介绍了这两种声纳的成像特点,分别从搭载平台、扫测特点、参数显示和声图特征等4个方面进行了比较,结合工程实例给出了两种声纳对海底油气管线探测的应用效果,分析比较了二者的优缺点。所得结论对于了解和掌握侧扫声纳和环扫声纳设备性能,进行海底油气管线检测和状态评估具有重要的工程实用意义。     

Fuzzy technology implemented in sonar systems

Applications of fuzzy algorithms in the domain of sonar systems that have been implemented in the latest generation of Atlas sonar equipment are introduced. The aim is to provide an insight into the solution of problems from an application-oriented point of view. Classification of DEMON spectra and automatic target tracking by means of fuzzy systems are introduced and demonstrated with examples. A short introduction to fuzzy technology is given to support the understanding of the algorithms presented     

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.     

青岛近岸海区海底地貌类型及声学特征

在对海岸带地貌发育主要影响因素进行讨论的基础上,根据实测数字声纳资料,对青岛海岸带近岸海区海底冲刷槽、潮流脊、侵蚀洼地、水下岸坡、潮滩、岛礁等地貌类型及次级微地貌声学特征进行了较详细的论述,通过对声图资料的精细解释,取得了对上述地貌特征的系统认识。     

一种基于MATLAB的声呐条带图像自动拼接算法

准确地实现侧扫声呐条带的拼接对于了解海底地形、提高对海床地物反映的准确度起着重要的作用,而相邻条带的配准是声呐条带拼接的重要前提.MATLAB以其强大的矩阵运算功能及具有丰富的图像处理函数等特点,在图像处理方面占据明显的优势.文中利用MATLAB的IPT工具箱实现了基于互信息方法的声呐条带图像的自动快速配准,通过实验验证了该配准方法的有效性.并用小波变换方法对配准好的条带图像进行融合,实现声呐条带图像的有效拼接和镶嵌.     

Spatial processing of signals received by platform mounted sonar

Acoustic signals received by platform mounted sonar arrays can be spatially processed to enhance the detection of targets in the presence of both ambient and platform generated (self) noise. Ambient noise in the ocean, such as that due to distant shipping or biological choruses, are known to be spatially correlated. The platform generated noise will be of near-field origin and may not be received by all elements in the array. In this paper we investigate the performance of the minimum variance distortionless response (MVDR) beamformer and the recently introduced Fourier integral method (FIM) and compare their performances with the conventional beamformer. Real passive sonar data, obtained from a platform mounted sparse linear array of hydrophones, is used to study the performance of the beamformers in a typical sonar environment. It is shown that in the absence of self noise, when the array is accurately calibrated the MVDR beamformer will perform very well, but when sensor gain or phase errors are present the performance of the MVDR beamformer is degraded. Further, the MVDR beamformer is unable to reject the self noise which is not "seen" by the entire array. FIM however seems to perform well and a modified version of FIM, which we call weighted FIM (WFIM), is shown to perform better and is at worst comparable to a well calibrated MVDR beamformer     

声相关海流剖面仪测速研究

声相关海流剖面仪(ACCP)适合深海测速,能够测得相对海底的绝对速度。文章在前人工作基础上,以声纳方程为基础,构造海底混响回波仿真模型,并对基于K irchhoff近似和利用微扰法的R ay le igh-R ice近似相结合的散射模型赋予新的物理意义,并将其应用到声相关测速仿真研究过程中,使仿真更加接近于海洋的实际环境。文章利用H ilbert变换进行包络检波来减小测速误差,并且根据接收信噪比得到了不同航速时能够达到最大底跟踪的距离,这与参考文献给出的结果是一致的。     

Improved time-delay estimates of underwater acoustic signals usingbeamforming and prefiltering techniques

Passive sonar systems that localize broadband sources of acoustic energy estimate the difference in arrival times (or time delays) of an acoustic wavefront at spatially separated hydrophones, The output amplitudes from a given pair of hydrophones are cross-correlated, and an estimate of the time delay is given by the time lag that maximizes the cross correlation function. Often the time-delay estimates are corrupted by the presence of noise. By replacing each of the omnidirectional hydrophones with an array of hydrophones, and then cross-correlating the beamformed outputs of the arrays, the author shows that the effect of noise on the time-delay estimation process is reduced greatly. Both conventional and adaptive beamforming methods are implemented in the frequency domain and the advantages of array beamforming (prior to cross-correlation) are highlighted using both simulated and real noise-field data. Further improvement in the performance of the broadband cross-correlation processor occurs when various prefiltering algorithms are invoked     

多波束回波强度数据记录方式比较

分析了三种不同多波束测深系统回波强度的记录方式及数据结构,基于各自生成声纳图像的特点规律的差异,按其声纳图像不同用途对多波束测深系统进行了归类,其结果可为用户结合自身需求,正确购置多波束测深系统及合理应用声纳图像提供参考.     

The practical implementation of electronic stabilization for sectorscanning sonar displays

The natural motion of a ship at sea produces undesirable effects on sonar displays. To overcome this problem some form of stabilization is desirable. A practical sonar display system, which uses image processing techniques to stabilize the displayed sonar image against rotational motion is described. The stabilization method provides the capability of image enhancement as well as improved image interpretation due to an increased area of view and a geometrically correct conversion to polar display. Details of the three processing stages required in the system are provided. These processes are ship motion analysis, image integration, and polar display conversion. Stabilized results are given for simulated ship motion     

西沙北部海域海洋环境噪声频谱特性

Ambient noise is very important in the prediction system of a sonar performance, because it determines the detection ranges always in a passive sonar and usually in an active sonar. In the uncertainty issue for the so-nar performance, it is necessary to know this factor＇s statistical characteristics that are only obtained by data processing from the underwater ambient noise measurements. Broad-band ambient noise signals from 16 hydrophones were amplified and recorded for 2 min every 1 h. The results show that the ambient noise is essentially depth independent. The cross correlation of the ambient noise levels （1, 6 and 12 h average） with a wind speed is presented. It was found that the correlation is excellent on the upper frequency band and the noise levels correlate better with high wind speed than with low wind speed.     

Fifth generation digital sonar signal processing

This paper discusses the evolutionary development, which has taken place over the last decade, in digital sonar systems architecture with the application of first, second, and third generation computers as system controllers for sonar systems. It is the opinion of the authors that, with the arrival of microprocessors, the system controller tasks in real time digital sonars will diminish. We present, as the "fourth generation," the present systems which still have a relatively large CPU, assisted by an array of microprocessors under their control for several subtasks which can be handled, more efficiently, locally in the systems. The "fifth generation" concept is postulated as a further development of this concept. A distributed processing scheme is presented in which the processing elements are actually highly functionally distributed themselves at the lowest level of architecture; consequently, the user views them as uniprocessors within the tightly coupled network. This approach should result in relatively high throughput utilizing a fairly small repertoire of modular hardware components and requiring minimal software effort by implementing, via firmware, very high level macros. This concept allows adaptive system architecture for the various advanced sonar data processing requirements for multielement linear, spatial, or blanket type array systems postulated for the future.     

高分辨率多波束声纳系统海底目标物检测技术

结合近几年出现的高分辨率多波束测深系统的性能特点,通过检测实例,介绍其在海底管道(尤其是裸露管道)检测中的相关技术及及检测成果。结果证实,高分辨率多波束测深系统可以准确检测海底小尺寸目标物,为其新特性的推广应用提供技术参考。     

Transient sonar signal classification using hidden Markov modelsand neural nets

In ocean surveillance, a number of different types of transient signals are observed. These sonar signals are waveforms in one dimension (1-D). The hidden Markov model (HMM) is well suited to classification of 1-D signals such as speech. In HMM methodology, the signal is divided into a sequence of frames, and each frame is represented by a feature vector. This sequence of feature vectors is then modeled by one HMM. Thus, the HMM methodology is highly suitable for classifying the patterns that are made of concatenated sequences of micro patterns. The sonar transient signals often display an evolutionary pattern over the time scale. Following this intuition, the application of HMM's to sonar transient classification is proposed and discussed in this paper. Toward this goal, three different feature vectors based on an autoregressive (AR) model, Fourier power spectra, and wavelet transforms are considered in our work. In our implementation, one HMM is developed for each class of signals. During testing, the signal to be recognized is matched against all models. The best matched model identifies the signal class. The neural net (NN) classifier has been successfully used previously for sonar transient classification. The same set of features as mentioned above is then used with a multilayer perceptron NN classifier. Some experimental results using “DARPA standard data set I” with HMM and MLP-NN classification schemes are presented. A combined NN/HMM classifier is proposed, and its performance is evaluated with respect to individual classifiers     

Pulse-length-tolerant features and detectors for sector-scan sonar imagery

This paper presents a neural-network-based system to detect small man-made objects in sequences of sector-scan sonar images created using signals of various pulse lengths. The detection of such objects is considered out to ranges of 150 m by using an experimental sector-scan sonar system mounted on a vessel. The sonar system considered in this investigation has three modes of operation to create images over ranges of 200, 400, and 800 m from the vessel using acoustic pulses of a different duration for each mode. After an initial cleaning operation performed by compensating for the motion of the vessel, the imagery is segmented to extract objects for analysis. A set of 31 features extracted from each object is examined. These features consist of basic object size and contrast features, shape moment-based features, moment invariants, and features extracted from the second-order histogram of each object. Optimal sets of 15 features are then selected for each mode and over all modes using sequential forward selection (SFS) and sequential backward selection (SBS). These features are then used to train neural networks to detect man-made objects in each sonar mode. By the addition of a feature describing the sonar's mode of operation, a neural network is trained to detect man-made objects in any of the three sonar modes. The multimode detector is shown to perform very well when compared with detectors trained specifically for each sonar mode setting. The proposed detector is also shown to perform well when compared to a number of statistical detectors based on the same set of features. The proposed detector achieves a 92.4% probability of detection at a mean false-alarm rate of 10 per image, averaged over all sonar mode settings.     

The Impact of Multipath on High-Resolution SAS Image Statistics

As with traditional sonar, synthetic aperture sonar (SAS) is susceptible to multipath contamination, reducing the quality and also modifying the statistics of the image. Such multipath contaminants may either be environmentally induced, as is often the case when attempting to image ranges greater than the water depth resulting in returns from the boundaries, or may be induced by the system's supporting structure itself. A clear understanding of such statistical impact is necessary to advance synthetic aperture formation algorithms and for predicting system performance. Broadband acoustic data suitable for SAS processing collected with a rail-mounted mobile-tower as part of the U.S. Office of Naval Research (ONR)-funded Sediment Acoustics eXperiment 2004 (SAX04) are analyzed in this paper. Analysis focused on both system structure and environmentally induced multipath using the $K$ -distribution shape parameter as a metric. High-resolution sonar imagery often exhibited significantly non-Rayleigh, heavy-tailed envelope statistics, characterized by a low equivalent $K$-distribution shape parameter. Analysis showed a clear and significant increase in the estimated shape parameter in the presence of multipath, representing a trend toward a Rayleigh-distributed envelope. A model for reverberation is presented to provide bounds of the statistical impact using observable image intensity level increases in synthetic-aperture-formed images caused by multipath contamination. This model further shows potential for statistical impact when multipath arrivals are of similar level as the direct path even when not observable in the image (e.g., within 10 dB).      

基于MRF与引导滤波的声纳图像去噪方法

声纳具有对大范围水下场景探测的能力,一直以来都是水下设备感知外界环境的重要手段,但由于声纳图像分辨率低,海洋环境噪声干扰较为复杂,所以在诸多方面的应用都受到了限制。文中提出了一种基于马尔可夫随机场和引导滤波的声纳图像去噪与增强方法,使用马尔可夫随机场对声纳图像进行预分割,然后采用中值滤波方法对原始图像进行简单滤波处理,最后将该图像作为引导图像对马尔可夫随机场(Markov Random Field,MRF)分割后的图像进行引导滤波实现了对声纳图像的去噪与增强。该方法有效地去除了背景和影子内的噪声,对目标区域内部噪声起到了很好的抑制作用,消除了MRF分割产生的伪轮廓效应,具有较好的边界保持和增强效果。     

Deep-towed side-scan survey of the United Nations Rise, eastern Mediterranean

 A newly discovered area of mud volcanism, about 170 km south of Crete, in the central–eastern part of the Mediterranean Ridge, was named the “United Nations Rise” (UNR). A survey of the UNR area with the deep-towed ORE tech side-scan sonar equipped with a subbottom profiler revealed the presence of some mud volcanoes and also showed various other sea-floor features, including slumps, escarpments and pockmark-type depressions. Several of our interpretations were ground-truthed by coring. The UNR area appears to belong to the Inner deformation front of the Mediterranean Ridge.