CUBE(combined uncertainty and bathymetry estimator)算法是国际上主流的多波束测深异常值自动探测与处理算法,在国内外被广泛应用,但对其核心算法和参数知之甚少,不利于该项技术的国产化。本文详细阐述了CUBE算法的基本原理、数学模...CUBE(combined uncertainty and bathymetry estimator)算法是国际上主流的多波束测深异常值自动探测与处理算法,在国内外被广泛应用,但对其核心算法和参数知之甚少,不利于该项技术的国产化。本文详细阐述了CUBE算法的基本原理、数学模型、关键参数和处理步骤,进而建立了CUBE曲面滤波参数联合优选方法。通过选取典型地形区、参数试验、对比分析等步骤完成参数的联合优选,并用台湾浅滩实测数据进行了验证。结果表明,优化后的参数可有效提升多波束数据自动处理的精度和效率。本文成果可应用于国产多波束测深处理软件的深化研发以及多波束实测数据处理。展开更多
针对全球深海测深数据来源复杂、精度差异大、难以融合构建高精度数字水深模型(digital bathymetric model,DBM)的问题,提出一种适用于深水区多源水深数据融合的MF法(merge-fusion),并将其应用到马里亚纳海沟"挑战者深渊"的DB...针对全球深海测深数据来源复杂、精度差异大、难以融合构建高精度数字水深模型(digital bathymetric model,DBM)的问题,提出一种适用于深水区多源水深数据融合的MF法(merge-fusion),并将其应用到马里亚纳海沟"挑战者深渊"的DBM构建中。该方法通过"合并-融合"的技术路线,将多波束、单波束、电子海图数据与通用全球海洋地形数据(general bathymetric chart of the oceans,GEBCO)有机地融合在一起,在保留高分辨率地形细节特征的同时,合理填补了数据空白区。使用该方法构建"挑战者深渊"高精度DBM并与GEBCO数据进行对比,结果表明,该方法融合的DBM能更好地反映精细的地形特征信息,具有重要的实际应用价值。展开更多
On the basis of three geological models and several orebody boundaries, a method of grid subdivision and integral has been proposed to calculate and evaluate the resources of cobalt-rich crusts on the seamounts in the...On the basis of three geological models and several orebody boundaries, a method of grid subdivision and integral has been proposed to calculate and evaluate the resources of cobalt-rich crusts on the seamounts in the central Pacific Ocean. The formulas of this method are deduced and the interface of program module is designed. The method is carried out in the software ＂Auto mapping system of submarine topography and geomorphology MBChart＂. This method and program will possibly become a potential tool to calculate the resources of seamounts and determine the target diggings for China＇ s next Five-year Plan.展开更多
Real-time observations in the field and numerical simulations（with Delft3D） were combined to study the formation, distribution and the relevant influencing factors of turbidity maximum（TM） in the Zhujiang（Pearl R...Real-time observations in the field and numerical simulations（with Delft3D） were combined to study the formation, distribution and the relevant influencing factors of turbidity maximum（TM） in the Zhujiang（Pearl River） Estuary（ZE）. The spatial distribution pattern of the TM varies with the longitudinal distributions of salinity and suspended sediment concentration（SSC）. The SSC is enhanced and the TM is intensified during dry seasons,whereas the center of the TM moves upstream by a distance of 10 km during wet seasons. The formation of the TM is influenced by a complex combination of numerous factors, including tides, river discharges and topography, wherein sediment resuspension and vertical circulation dominate the formations and variability of the TM.展开更多
Environmental uncertainty represents the limiting factor in matched-field localization. Within a Bayesian framework, both the environmental parameters, and the source parameters are considered to be unknown variables....Environmental uncertainty represents the limiting factor in matched-field localization. Within a Bayesian framework, both the environmental parameters, and the source parameters are considered to be unknown variables. However, including environmental parameters in multiple-source localization greatly increases the complexity and computational demands of the inverse problem. In the paper, the closed-form maximumlikelihood expressions for source strengths and noise variance at each frequency allow these parameters to be sampled implicitly, substantially reducing the dimensionality and difficulty of the inversion. This paper compares two Bayesian-point-estimation methods： the maximum a posteriori（MAP） approach and the marginal posterior probability density（PPD） approach to source localization. The MAP approach determines the sources locations by maximizing the PPD over all source and environmental parameters. The marginal PPD approach integrates the PPD over the unknowns to obtain a sequence of marginal probability distribution over source range or depth.Monte Carlo analysis of the two approaches for a test case involving both geoacoustic and water-column uncertainties indicates that：（1） For sensitive parameters such as source range, water depth and water sound speed, the MAP solution is better than the marginal PPD solution.（2） For the less sensitive parameters, such as,bottom sound speed, bottom density, bottom attenuation and water sound speed, when the SNR is low, the marginal PPD solution can better smooth the noise, which leads to better performance than the MAP solution.Since the source range and depth are sensitive parameters, the research shows that the MAP approach provides a slightly more reliable method to locate multiple sources in an unknown environment.展开更多
文摘CUBE(combined uncertainty and bathymetry estimator)算法是国际上主流的多波束测深异常值自动探测与处理算法,在国内外被广泛应用,但对其核心算法和参数知之甚少,不利于该项技术的国产化。本文详细阐述了CUBE算法的基本原理、数学模型、关键参数和处理步骤,进而建立了CUBE曲面滤波参数联合优选方法。通过选取典型地形区、参数试验、对比分析等步骤完成参数的联合优选,并用台湾浅滩实测数据进行了验证。结果表明,优化后的参数可有效提升多波束数据自动处理的精度和效率。本文成果可应用于国产多波束测深处理软件的深化研发以及多波束实测数据处理。
文摘针对全球深海测深数据来源复杂、精度差异大、难以融合构建高精度数字水深模型(digital bathymetric model,DBM)的问题,提出一种适用于深水区多源水深数据融合的MF法(merge-fusion),并将其应用到马里亚纳海沟"挑战者深渊"的DBM构建中。该方法通过"合并-融合"的技术路线,将多波束、单波束、电子海图数据与通用全球海洋地形数据(general bathymetric chart of the oceans,GEBCO)有机地融合在一起,在保留高分辨率地形细节特征的同时,合理填补了数据空白区。使用该方法构建"挑战者深渊"高精度DBM并与GEBCO数据进行对比,结果表明,该方法融合的DBM能更好地反映精细的地形特征信息,具有重要的实际应用价值。
基金This study was supported by Projects under contract Nos DY105 China's 0cean-03-01-01 and DY105-03-01-07the National Natural Science Foundation of China under contract No.40506017the Youth Foundation of Marine High-tech Project of China under contract No.2002AA616010.
文摘On the basis of three geological models and several orebody boundaries, a method of grid subdivision and integral has been proposed to calculate and evaluate the resources of cobalt-rich crusts on the seamounts in the central Pacific Ocean. The formulas of this method are deduced and the interface of program module is designed. The method is carried out in the software ＂Auto mapping system of submarine topography and geomorphology MBChart＂. This method and program will possibly become a potential tool to calculate the resources of seamounts and determine the target diggings for China＇ s next Five-year Plan.
基金The Ocean Special Funds for Scientific Research on Public Causes under contract No.201105001-2the National Basic Research Program(973 Program)of China under contract No.2013CB956502the National Natural Science Foundation of China under contract Nos 41376044,41276083 and 41476049
文摘Real-time observations in the field and numerical simulations（with Delft3D） were combined to study the formation, distribution and the relevant influencing factors of turbidity maximum（TM） in the Zhujiang（Pearl River） Estuary（ZE）. The spatial distribution pattern of the TM varies with the longitudinal distributions of salinity and suspended sediment concentration（SSC）. The SSC is enhanced and the TM is intensified during dry seasons,whereas the center of the TM moves upstream by a distance of 10 km during wet seasons. The formation of the TM is influenced by a complex combination of numerous factors, including tides, river discharges and topography, wherein sediment resuspension and vertical circulation dominate the formations and variability of the TM.
基金The National Natural Science Foundation of China under contract No.11704225the Shandong Provincial Natural Science Foundation under contract No.ZR2016AQ23+1 种基金the State Key Laboratory of Acoustics of Chinese Academy of Sciences under contract No.SKLA201704the National Programe on Global Change and Air-Sea Interaction
文摘Environmental uncertainty represents the limiting factor in matched-field localization. Within a Bayesian framework, both the environmental parameters, and the source parameters are considered to be unknown variables. However, including environmental parameters in multiple-source localization greatly increases the complexity and computational demands of the inverse problem. In the paper, the closed-form maximumlikelihood expressions for source strengths and noise variance at each frequency allow these parameters to be sampled implicitly, substantially reducing the dimensionality and difficulty of the inversion. This paper compares two Bayesian-point-estimation methods： the maximum a posteriori（MAP） approach and the marginal posterior probability density（PPD） approach to source localization. The MAP approach determines the sources locations by maximizing the PPD over all source and environmental parameters. The marginal PPD approach integrates the PPD over the unknowns to obtain a sequence of marginal probability distribution over source range or depth.Monte Carlo analysis of the two approaches for a test case involving both geoacoustic and water-column uncertainties indicates that：（1） For sensitive parameters such as source range, water depth and water sound speed, the MAP solution is better than the marginal PPD solution.（2） For the less sensitive parameters, such as,bottom sound speed, bottom density, bottom attenuation and water sound speed, when the SNR is low, the marginal PPD solution can better smooth the noise, which leads to better performance than the MAP solution.Since the source range and depth are sensitive parameters, the research shows that the MAP approach provides a slightly more reliable method to locate multiple sources in an unknown environment.
