CUBE曲面滤波参数联合优选关键技术及应用
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摘要
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。
CUBE(combined uncertainty and bathymetry estimator) is a widespread algorithm in the world to automatically detect and process multi-beam sounding outliers. While, little is known about its core algorithms and parameters, which is not good for the localization of this technology. In this paper, the basic principle, mathematical model, key parameters and processing steps of CUBE algorithm are elaborated. Then a method of parameter optimization selection combining CUBE and surface filter is established. And an example is presented, in which optimized parameters are selected by choosing typical bathymetric area, parameter test, comparative analysis and etc. And the optimized parameters are verified with the observed data in the Taiwan Banks. The results show that the optimized parameters can effectively improve the accuracy and efficiency of automatic processing of multi-beam data. The technology in this paper can provide reference for deepening research and development of domestic multi-beam sounding processing software and multi-beam data processing.
CUBE(combined uncertainty and bathymetry estimator) is a widespread algorithm in the world to automatically detect and process multi-beam sounding outliers. While, little is known about its core algorithms and parameters, which is not good for the localization of this technology. In this paper, the basic principle, mathematical model, key parameters and processing steps of CUBE algorithm are elaborated. Then a method of parameter optimization selection combining CUBE and surface filter is established. And an example is presented, in which optimized parameters are selected by choosing typical bathymetric area, parameter test, comparative analysis and etc. And the optimized parameters are verified with the observed data in the Taiwan Banks. The results show that the optimized parameters can effectively improve the accuracy and efficiency of automatic processing of multi-beam data. The technology in this paper can provide reference for deepening research and development of domestic multi-beam sounding processing software and multi-beam data processing.
引文
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[13] ZHAO Jianhu, MENG Junxia, ZHANG Hongmei, et al. A new method for acquisition of high-resolution seabed topography by matching seabed classification images[J]. Remote Sensing, 2017, 9(12): 1214. DOI: 10.3390/rs9121214.
[14] ZHAO Jianhu, YAN Jun, ZHANG Hongmei, et al. A new method for weakening the combined effect of residual errors on multibeam bathymetric data[J]. Marine Geophysical Research, 2014, 35(4): 379-394. DOI: 10.1007/s11001-014-9228-6.
[15] 吴自银, 阳凡林, 罗孝文, 等. 高分辨率海底地形地貌——探测处理理论与技术[M]. 北京: 科学出版社, 2017. WU Ziyin, YANG Fanlin, LUO Xiaowen, et al. High resolution submarine geomorphology[M]. Beijing: Science Press, 2017.
[16] 赵建虎, 王爱学. 精密海洋测量与数据处理技术及其应用进展[J]. 海洋测绘, 2015, 35(6): 1-7. DOI: 10.3969/j.issn.1671-3044.2015.06.001. ZHAO Jianhu, WANG Aixue. Precise marine surveying and data processing technology and their progress of application[J]. Hydrographic Surveying and Charting, 2015, 35(6): 1-7. DOI: 10.3969/j.issn.1671-3044.2015.06.001.
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[19] 阳凡林, 李家彪, 吴自银, 等. 浅水多波束勘测数据精细处理方法[J]. 测绘学报, 2008, 37(4): 444-450, 457. YANG Fanlin, LI Jiabiao, WU Ziyin, et al. The methods of high quality post-processing for shallow multibeam data[J]. Acta Geodaetica et Cartographica Sinica, 2008, 37(4): 444-450, 457.
[20] LUCIEER V, HUANG Zhi, SIWABESSY J. Analyzing uncertainty in multibeam bathymetric data and the impact on derived seafloor attributes[J]. Marine Geodesy, 2016, 39(1): 32-52. DOI: 10.1080/01490419.2015.1121173.
[21] REZVANI M H, SABBAGH A, ARDALAN A A. Robust automatic reduction of multibeam bathymetric data based on M-estimators[J]. Marine Geodesy, 2015, 38(4): 327-344. DOI: 10.1080/01490419.2015.1053639.
[22] BOURILLET J F, EDY C, RAMBERT F, et al. Swath mapping system processing: bathymetry and cartography[J]. Marine Geophysical Researches, 1996, 18(2-4): 487-506. DOI: 10.1007/bf00286091.
[23] CARESS D W, CHAYES D N. Improved processing of hydrosweep DS multibeam data on the R/V Maurice Ewing[J]. Marine Geophysical Researches, 1996, 18(6): 631-650. DOI: 10.1007/bf00313878.
[24] PEREDA GARCíA R, PINA GARCíA F, DE LUIS RUIZ J M, et al. Model for the processing and estimation of dual frequency echo sounder observations in detailed bathymetries[J]. Marine Geodesy, 2016, 39(3-4): 305-320. DOI: 10.1080/01490419.2016.1193577.
[25] EEG J. On the identification of spikes in soundings[J]. International Hydrographic Review, 1995, 72(1): 33-41.
[26] DEBESE N. Use of a robust estimator for automatic detection of isolated errors appearing in the bathymetry data[J]. International Hydrographic Review, 2001, 2(2): 32-44.
[27] DEBESE N. Multibeam echosounder data cleaning through an adaptive surface-based approach[C]//Proceedings of the US Hydrographic Conference. Norfolk: [s.n.], 2007: 1-18.
[28] LECOURS V, DOLAN M F J, MICALLEF A, et al. A review of marine geomorphometry, the quantitative study of the seafloor[J]. Hydrology and Earth System Sciences, 2016, 20(8): 3207-3244. DOI: 10.5194/hess-20-3207-2016.
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