共查询到20条相似文献，搜索用时 187 毫秒
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多波束反向散射强度数据应用广泛，但由于受到角度响应的影响，导致生成的多波束声呐图像质量偏低，且现有角度响应改正方法在复杂海底底质环境下适应性较差。为此本文对散射强度进行分析，给出了两种多波束反向散射强度数据归一化方法，分别为基于高斯拟合以及角度响应的散射强度改正方法，前者主要是基于散射强度的变化规律进行改正，而后者则是基于声波的散射机理进行改正。实验结果表明两种方法较传统改正方法精度均有约30%的提升，并且角度响应方法较高斯拟合方法改正精度更高，但计算效率有所下降。以上实验验证了两种方法的有效性，实现了散射强度数据的归一化，提升了多波束声呐图像的质量。 相似文献
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多波束声呐图像是进行海底底质分类的主要数据源之一,由于受海洋噪声、声波散射和混响、仪器设备等因素影响,其经各项常规改正后仍存在明显残差,突出表现在中央波束区和条带重叠区,难以形成高质量的声呐图像。文中分析了多波束声呐图像残差的成因及影响,提出了一种基于多条带最小二乘拟合的多波束声呐图像残差处理方法。首先,得到相邻声脉冲(ping)信号中央区域、重叠区域以及整体趋势的拟合函数;然后,通过拟合函数计算得到中央和重叠区域的残差改正系数;最后,通过改正系数进行残差改正。实验分析表明,该方法在保留原始细节的基础上,有效削弱了残差对声呐图像的影响,对多波束声呐图像处理具有参考和应用价值。 相似文献
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提出了一种基于Open GL可编程管线的海底浅层声学探测数据三维综合可视化方法。通过处理,将侧扫声呐影像、多波束数据和浅地层剖面在同一视图下显示,可以方便的对海底地质环境多种信息进行综合判读并进行多维数据的交互式提取。利用纹理缓冲区处理侧扫声呐影像数据,具有数据加载量大的优点,避免了实际应用中纹理数据反复切换带来的延迟;并且探讨了侧扫声呐影像和多波束数据分辨率不一致引起的纹理贴图问题。该方法在南海海底峡谷区域的海底地质环境综合显示和分析中进行了应用,结果表明,该方法能处理多种格式的侧扫声呐影像,不受侧扫声呐影像和多波束测深数据分辨率不一致的限制,数据加载量大、绘制速度快。 相似文献
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多波束水体数据对台西南盆地天然气水合物的揭示 总被引：1，自引：1，他引：0
在台西南盆地陆坡上进行了多波束测量，获取了海底地形数据和水体数据。对多波束数据进行处理，展示了多波束水体数据形成的声学水柱影像。研究表明：在台西南盆地天然气水合物富集区，多波束水柱影像异常，呈现羽状流特点，揭示了台西南盆地的天然气资源，多波束声呐系统为探测海底天然气水合物提供了精确高效的方法。 相似文献
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济州岛南部海域海底声呐图像分析与声学底质分类 总被引：2，自引：2，他引：0
东海北部外陆架靠近济州岛南部海域,是黄海槽向冲绳海槽延伸的部分,属于黑潮分支黄海暖流的通道入口,分布着脊槽相间的海底底形,对其海底声呐图像的处理分析及声学底质分类的分析研究,有助于了解该通道海底底形表层纹理特征及沉积物分布规律。基于在济州岛南部海域获取的多波束声呐数据,应用图像处理技术和方法,对数据进行了处理,获得了海底声呐影像图,并对其表层纹理特征进行了描述和分析;同时,基于多波束反向散射强度数据,结合19组海底地质取样数据,建立研究区海底反向散射强度与沉积物粒度特征之间的统计关系模型,并以改进的学习向量量化神经网络方法,实现对海底粉砂质砂、黏土质砂以及砂-粉砂-黏土3种底质类型的快速自动分类识别。 相似文献
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Processing of high-frequency multibeam echo sounder data for seafloor characterization 总被引：9，自引：0，他引：9
Processing simultaneous bathymetry and backscatter data, multibeam echosounders (MBESs) show promising abilities for remote seafloor characterization. High-frequency MBESs provide a good horizontal resolution, making it possible to distinguish fine details at the water-seafloor interface. However, in order to accurately measure the seafloor influence on the backscattered energy, the recorded sonar data must first be processed and cleared of various artifacts generated by the sonar system itself. Such a preprocessing correction procedure along with the assessment of its validity limits is presented and applied to a 95-kHz MBES (Simrad EM 1000) data set. Beam pattern effects, uneven array sensitivities, and inaccurate normalization of the ensonified area are removed to make possible further quantitative analysis of the corrected backscatter images. Unlike low-frequency data where the average backscattered energy proves to be the only relevant feature for discriminating the nature of the seafloor, high-frequency MBES backscatter images exhibit visible texture patterns. This additional information involves different statistical distributions of the backscattered amplitudes obtained from various seafloor types. Non-Rayleigh statistics such as K-distributions are shown to fit correctly the skewed distributions of experimental high-frequency data. Apart from the effect of the seafloor micro-roughness, a statistical model makes clear a correlation between the amplitude statistical distributions and the signal incidence angle made available by MBES bathymetric abilities. Moreover, the model enhances the effect of the first derivative of the seafloor backscattering strength upon statistical distributions near the nadir and at high incidence angles. The whole correction and analysis process is finally applied to a Simrad EM 1000 data set. 相似文献
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User expectations for multibeam echo sounders backscatter strength data-looking back into the future
Vanessa Lucieer Marc Roche Koen Degrendele Mashkoor Malik Margaret Dolan Geoffroy Lamarche 《Marine Geophysical Researches》2018,39(1-2):23-40
With the ability of multibeam echo sounders (MBES) to measure backscatter strength (BS) as a function of true angle of insonification across the seafloor, came a new recognition of the potential of backscatter measurements to remotely characterize the properties of the seafloor. Advances in transducer design, digital electronics, signal processing capabilities, navigation, and graphic display devices, have improved the resolution and particularly the dynamic range available to sonar and processing software manufacturers. Alongside these improvements the expectations of what the data can deliver has also grown. In this paper, we identify these user-expectations and explore how MBES backscatter is utilized by different communities involved in marine seabed research at present, and the aspirations that these communities have for the data in the future. The results presented here are based on a user survey conducted by the GeoHab (Marine Geological and Biological Habitat Mapping) association. This paper summarises the different processing procedures employed to extract useful information from MBES backscatter data and the various intentions for which the user community collect the data. We show how a range of backscatter output products are generated from the different processing procedures, and how these results are taken up by different scientific disciplines, and also identify common constraints in handling MBES BS data. Finally, we outline our expectations for the future of this unique and important data source for seafloor mapping and characterisation. 相似文献
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Alexandre C. G. Schimel Jonathan Beaudoin Iain M. Parnum Tim Le Bas Val Schmidt Gordon Keith Daniel Ierodiaconou 《Marine Geophysical Researches》2018,39(1-2):121-137
Multibeam sonar systems now routinely record seafloor backscatter data, which are processed into backscatter mosaics and angular responses, both of which can assist in identifying seafloor types and morphology. Those data products are obtained from the multibeam sonar raw data files through a sequence of data processing stages that follows a basic plan, but the implementation of which varies greatly between sonar systems and software. In this article, we provide a comprehensive review of this backscatter data processing chain, with a focus on the variability in the possible implementation of each processing stage. Our objective for undertaking this task is twofold: (1) to provide an overview of backscatter data processing for the consideration of the general user and (2) to provide suggestions to multibeam sonar manufacturers, software providers and the operators of these systems and software for eventually reducing the lack of control, uncertainty and variability associated with current data processing implementations and the resulting backscatter data products. One such suggestion is the adoption of a nomenclature for increasingly refined levels of processing, akin to the nomenclature adopted for satellite remote-sensing data deliverables. 相似文献
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Remote estimation of surficial seafloor properties through the application Angular Range Analysis to multibeam sonar data 总被引：2，自引：2，他引：2
The variation of the backscatter strength with the angle of incidence is an intrinsic property of the seafloor, which can
be used in methods for acoustic seafloor characterization. Although multibeam sonars acquire backscatter over a wide range
of incidence angles, the angular information is normally neglected during standard backscatter processing and mosaicking.
An approach called Angular Range Analysis has been developed to preserve the backscatter angular information, and use it for
remote estimation of seafloor properties. Angular Range Analysis starts with the beam-by-beam time-series of acoustic backscatter
provided by the multibeam sonar and then corrects the backscatter for seafloor slope, beam pattern, time varying and angle
varying gains, and area of insonification. Subsequently a series of parameters are calculated from the stacking of consecutive
time series over a spatial scale that approximates half of the swath width. Based on these calculated parameters and the inversion
of an acoustic backscatter model, we estimate the acoustic impedance and the roughness of the insonified area on the seafloor.
In the process of this inversion, the behavior of the model parameters is constrained by established inter-property relationships.
The approach has been tested using a 300 kHz Simrad EM3000 multibeam sonar in Little Bay, NH. Impedance estimates are compared
to in situ measurements of sound speed. The comparison shows a very good correlation, indicating the potential of this approach for
robust seafloor characterization. 相似文献
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A new highly precise source of data has recently become available using multibeam sonar systems in hydrography. Multibeam sonar systems can provide hydrographic quality depth data as well as high-resolution seafloor sonar images. We utilize the seafloor backscatter strength data of each beam from multibeam sonar and the automatic classification technology so that we can get the seafloor type identification maps. In this article, analyzing all kinds of error effects in backscatter strength, data are based on the relationship between backscatter strength and seafloor types. We emphasize particularly analyzing the influences of local bottom slope and near nadir reflection in backscatter strength data. We also give the correction algorithms and results of these two influent factors. After processing the raw backscatter strength data and correcting error effects, we can get processed backscatter strength data which reflect the features of seafloor types only. Applying the processed backscatter strength data and mosaicked seafloor sonar images, we engage in seafloor classification and geomorphy interpretation in future research. 相似文献
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Processing Multibeam Backscatter Data 总被引：1，自引：0，他引：1
A new highly precise source of data has recently become available using multibeam sonar systems in hydrography. Multibeam sonar systems can provide hydrographic quality depth data as well as high-resolution seafloor sonar images. We utilize the seafloor backscatter strength data of each beam from multibeam sonar and the automatic classification technology so that we can get the seafloor type identification maps. In this article, analyzing all kinds of error effects in backscatter strength, data are based on the relationship between backscatter strength and seafloor types. We emphasize particularly analyzing the influences of local bottom slope and near nadir reflection in backscatter strength data. We also give the correction algorithms and results of these two influent factors. After processing the raw backscatter strength data and correcting error effects, we can get processed backscatter strength data which reflect the features of seafloor types only. Applying the processed backscatter strength data and mosaicked seafloor sonar images, we engage in seafloor classification and geomorphy interpretation in future research. 相似文献
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Jess I. T. Hillman Geoffroy Lamarche Arne Pallentin Ingo A. Pecher Andrew R. Gorman Jens Schneider von Deimling 《Marine Geophysical Researches》2018,39(1-2):205-227
Using automated supervised segmentation of multibeam backscatter data to delineate seafloor substrates is a relatively novel technique. Low-frequency multibeam echosounders (MBES), such as the 12-kHz EM120, present particular difficulties since the signal can penetrate several metres into the seafloor, depending on substrate type. We present a case study illustrating how a non-targeted dataset may be used to derive information from multibeam backscatter data regarding distribution of substrate types. The results allow us to assess limitations associated with low frequency MBES where sub-bottom layering is present, and test the accuracy of automated supervised segmentation performed using SonarScope® software. This is done through comparison of predicted and observed substrate from backscatter facies-derived classes and substrate data, reinforced using quantitative statistical analysis based on a confusion matrix. We use sediment samples, video transects and sub-bottom profiles acquired on the Chatham Rise, east of New Zealand. Inferences on the substrate types are made using the Generic Seafloor Acoustic Backscatter (GSAB) model, and the extents of the backscatter classes are delineated by automated supervised segmentation. Correlating substrate data to backscatter classes revealed that backscatter amplitude may correspond to lithologies up to 4 m below the seafloor. Our results emphasise several issues related to substrate characterisation using backscatter classification, primarily because the GSAB model does not only relate to grain size and roughness properties of substrate, but also accounts for other parameters that influence backscatter. Better understanding these limitations allows us to derive first-order interpretations of sediment properties from automated supervised segmentation. 相似文献