Parameter Group Optimization by Combining CUBE with Surface Filtering and Its Application

doi:10.11947/j.JGGS.2020.0209

Abstract

Abstract:

Shallow water multi-beam echo sounders (MBESs) are characterized by their high resolution and high density, and MBES data processing is a hotspot in modern marine surveying. The Combined Uncertainty and Bathymetry Estimator (CUBE) is the mainstream MBES data processing algorithm, although little is known about its core theories and parameters. In this paper, the basic principle, mathematical model, key parameters, and main processing steps of CUBE are described systematically. A parameter group optimization method that combines CUBE with a surface filter is established. Additionally, an example is given that shows the steps for parameter group optimization, including selection of a typical area, parameter group testing, and comparative analysis, and the method is then applied to shallow water MBES data processing. The results show that the method can improve the accuracy and efficiency of automatic data processing effectively, and it is thus of engineering application value.

Key words: multi-beam echo sounder; CUBE; data processing; parameter optimization; algorithm principle

Dineng ZHAO,Ziyin WU,Jieqiong ZHOU,Mingwei WANG,Zhihao LIU,Jiabiao LI. Parameter Group Optimization by Combining CUBE with Surface Filtering and Its Application[J]. Journal of Geodesy and Geoinformation Science, 2020, 3(2): 81-92.

Figures/Tables 13

Fig.1

Fig.2

Tab.1

Four parameter groups of CUBE"

CUBE parameter groups	μ_captdistsca	μ_captdistmin	μ_hes	h_estimoff
CUBE Default	5	0.5	2.95	4
CUBE Deep	20	2	2.95	3
CUBE Shallow	4	0.4	0.5	2
CUBE NOAA	0.5	$G res 2$	1.96	4

Tab.1

Fig.3

Tab.2

Fig.4

Fig.5

Tab.3

Tab.4

Fig.6

Fig.7

Fig.8

Fig.9

References 54

[1]	LI Jiabiao. Multibeam sounding principles, survey technologies and data processing methods[M]. Beijing: Ocean Press, 1999.
[2]	ZHAO Jianhu. Modern marine surveying and charting[M]. Wuhan: Wuhan University Press, 2008.
[3]	HUANG Chenhu, LU Xiuping, HUANG Motao, et al. Shallow water multibeam sounding tide correction technology [C]//Marine Surveying and Mapping Comprehensive Symposium. Jiujiang: Chinese Society of Geodesy, Photogrammetry and Cartography, 2007.
[4]	YANG Fanlin, LI Jiabiao, WU Ziyin, et al. The methods of removing instantaneous attitude errors for multibeam bathymetry data[J]. Acta Geodaetica et Cartographica Sinica, 2009,38(5):450-456. DOI: 10.3321/j.issn:1001-1595.2009.05.012.
[5]	ZHAO Dineng, WU Ziyin, ZHOU Jieqiong, et al. A method for streamlining and assessing sound velocity profiles based on improved D-P algorithm[J]. Acta Geodaetica et Cartographica Sinica, 2014,43(7):681-689.DOI: 10.13485/j.cnki.11-2089.2014.0132.
[6]	WU Ziyin, LI Jiabiao, YANG Fanlin, et al. An intergrated method for automatic identification of the foot point of slope[J]. Acta Geodaetica et Cartographica Sinica, 2014,43(2):170-177.DOI: 10.13485/j.cnki.11-2089.2014.0025.
[7]	ZHAO Jianhu, OUYANG Yongzhong, WANG Aixue. Status and development tendency for seafloor terrain measurement technology[J]. Acta Geodaetica et Cartographica Sinica, 2017,46(10):1786-1794.DOI: 10.11947/j.AGCS.2017.20170276.
[8]	WU Ziyin, JIN Xianglong, LI Jiabiao, et al. Linear sand ridges on the outer shelf of the east China Sea[J]. Chinese Science Bulletin, 2005,50(21):2517-2528. DOI: 10.1007/BF03183643. doi: 10.1007/BF03183643
[9]	ZHOU Jieqiong, WU Ziyin, ZHAO Dineng, et al. Giant sand waves on the Taiwan Banks, southern Taiwan Strait: Distribution, morphometric relationships, and hydrologic influence factors in a tide-dominated environment[J]. Marine Geology, 2020,427, 106238. DOI: 10.1016/j.margeo.2020.106238. doi: 10.1016/j.margeo.2020.106238
[10]	WU Ziyin, LI Jiabiao, JIN Xianglong, et al. Distribution, features, and influence factors of the submarine topographic boundaries of the Okinawa Trough[J]. Science China Earth Sciences, 2014,57(8):1885-1896. DOI: 10.1007/s11430-013-4810-3. doi: 10.1007/s11430-013-4810-3
[11]	WU Ziyin, JIN Xianglong, ZHOU Jieqiong, et al. Comparison of buried sand ridges and regressive sand ridges on the outer shelf of the East China Sea[J]. Marine Geophysical Research, 2017,38(1-2):187-198. DOI: 10.1007/s11001-016-9278-z. doi: 10.1007/s11001-016-9278-z
[12]	ZHOU Jieqiong, WU Ziyin, JIN Xianglong, et al. Observations and analysis of giant sand wave fields on the Taiwan Banks, Northern South China Sea[J]. Marine Geology, 2018,406(1):132-141. doi: 10.1016/j.margeo.2018.09.015
[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 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. doi: 10.1007/s11001-014-9228-6
[15]	WU Ziyin, YANG Fanlin, LUO Xiaowen, et al. High-resolution submarine topography-Theory and technology for surveying and post-processing[M]. Beijing: Science Press, 2017.
[16]	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.
[17]	WU Ziyin, YANG Fanlin, LI Shoujun, et al. High-resolution submarine topography-visual computation and scientific applications[M]. Beijing: China Science Press, 2017.
[18]	FARR H K. Multibeam bathymetric sonar:sea beam and hydro chart[J]. Marine Geodesy, 1980,4(2):77-93. DOI: 10.1080/15210608009379375. doi: 10.1080/15210608009379375
[19]	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. DOI: 10.3321/j.issn:1001-1595.2008.04.008.
[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. doi: 10.1080/01490419.2015.1121173
[21]	REZVANI M H, SABBAGH A, ARDALAN AA. 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. 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. doi: 10.1007/BF00286091
[23]	CARESS D W, CHAYES D N. Improved processing ofhydrosweep DS multibeam data on the R/V Maurice Ewing[J]. Marine Geophysical Researches, 1996,18(6):631-650. DOI: 10.1007/bf00313878. 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. 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. doi: 10.5194/hess-20-3207-2016
[29]	ZHANG Zhiheng, PENG Rencan, HUANG Wenqian, et al. An improved algorithm of tendency surface filtering in multi-beam bathymetric data considering the natural neighboring points influence field[J]. Acta Geodaetica et Cartographica Sinica, 2018,47(1):35-47. DOI: 10.11947/j.AGCS.2018.20160565.
[30]	DU Z, WELLS D, MAYER L. An approach to automatic detection of outliers inmultibeam echo sounding data[J]. Hydrographic Journal, 1996,79(1):19-25.
[31]	LADNER R W, ELMORE P, PERKINS A L, et al. Automated cleaning and uncertainty attribution of archival bathymetry based on a priori knowledge[J]. Marine Geophysical Research, 2017,38(3):291-301.DOI: 10.1007/s11001-017-9304-9. doi: 10.1007/s11001-017-9304-9
[32]	CANEPA G, BERGEM O, PACE N G. A new algorithm for automatic processing of bathymetric data[J]. IEEE Journal of Oceanic Engineering, 2003,28(1):62-77.DOI: 10.1109/joe.2002.808204. doi: 10.1109/JOE.2002.808204
[33]	SHAW S, ARNOLD J. Automated error detection inmultibeam bathymetry data [C]//Proceedings of IEEE OCEANS’93. Victoria, BC, Canada: IEEE, 1993: 89-94. DOI: 10.1109/OCEANS.1993.326072.
[34]	CALDER B R, WELLS D. CUBE usermanual[M]. [s.l.]: University of New Hampshire, 2004.
[35]	CALDER B R, MAYER L A. Robust automatic multi-beam bathymetric processing [C]//US Hydrographic Conference. Norfolk(VA): [s.n.], 2001: 1-20.
[36]	CALDER B R, MAYER L A. Automatic processing of high-rate, high-density multibeam echosounder data[J]. Geochemistry, Geophysics, Geosystems, 2003,4(6):1048. DOI: 10.1029/2002gc000486.
[37]	CALDER B R, SMITH S. A time comparison of computer-assisted and manual bathymetric processing[J]. International Hydrographic Review, 2004,5(1):10-23.
[38]	NOAA Field Procedures Manual[EB/OL].[2019-06-10].https://nauticalcharts.noaa.gov/publications/docs/standards-and-requirements/fpm/2014-fpm-final.pdf.
[39]	HOWLETT C. Considerations and advantages of accepting CUBE surfaces as survey deliverables [C]//Proceedings of the NSHC 29th Conference. Brest: [s.n.], 2010.
[40]	MALLACE D, GEE L. Multibeam processing-the end to manual editing?[J]. International Hydrographic Review, 2005,6(1):55-65.
[41]	MALLACE D, ROBERTSON P. Alternative use of CUBE: how to fit a square peg in a round hole [C]//US Hydrographic Conference 2007. Norfolk(VA): [s.n.], 2007: 1-12.
[42]	VÁSQUEZ M E, NICHOLS S, CLARKE J H. Tuning the CARIS implementation of CUBE forpatagonian waters[D]. Fredericton: University of New Brunswick, 2007.
[43]	PARK Y, JUNG N D, DO JANG N, et al. Performance validation of surface filter based on CUBE algorithm for eliminating outlier in multi beam echo sounding[EB/OL]. [2019-06-10].https://www.hydrographicsociety.org/documents/hydrographicsociety.org/downloads/ifhs_news_no_1_-_yosup_park_et_al.pdf.
[44]	WANG Degang, YE Yincan. The theory of CUBE algorithm and its application in the processing of multi-beam data[J]. Journal of Marine Sciences, 2008,26(2):82-88. DOI: 10.3969/j.issn.1001-909X.2008.02.012.
[45]	HUANG Chenhu, LU Xiuping, HOU Shixi, et al. Study on detecting outlier of multibeam sounding based on CUBE algorithm[J]. Hydrographic Surveying and Charting, 2010,30(3):1-5. DOI: 10.3969/j.issn.1671-3044.2010.03.001.
[46]	JIA Shuaidong, Zhang Lihua, CAO Hongbo. A method for eliminating outliers of multibeam echosounder data based on CUBE[J]. Science of Surveying and Mapping, 2010,35(S1):57-59, 94.
[47]	HUANG Motao, ZHAI Guojun, CHAI Hongzhou, et al. Analysis on the mathematical models of CUBE algorithm for the detection of abnormal data in multibeam echosounding[J]. Hydrographic Surveying and Charting, 2011,31(4):1-4. DOI: 10.3969/j.issn.1671-3044.2011.04.001.
[48]	WANG Haidong, CHAI Hongzhou. Research on multibeam bathymetry data automatic processing based on CUBE algorithm[J]. Marine Science Bulletin, 2011,30(3):246-251. DOI: 10.3969/j.issn.1001-6392.2011.03.002.90
[49]	HARE R, GODIN A, MAYER L A. Accuracy estimation ofcanadian swath (multibeam) and sweep (multitransducer) sounding systems[R]. Fredericton: Canadian Hydrographic Service, 1995.
[50]	HARE R. Error Budget Analysis for US Naval Oceanographic Office (NAVOCEANO) Hydrographic Survey Systems[EB/OL]. [2019-06-10].http://www.academia.edu/10086841/Error_Budget_Analysis_For_NAVO.
[51]	HARE R, EAKINS B, AMANTE C. Modelling bathymetric uncertainty[J]. International Hydrographic Review, 2011,6(1):31-42.
[52]	International Hydrographic Organization. IHO standards for hydrographic surveys[EB/OL].[2019-06-10].http://www.iho.int/iho_pubs/standard/S-44_5E.pdf.
[53]	CALDER B. Automatic statistical processing of multibeam echosounder data[J]. International Hydrographic Review, 2003,4(1):53-68.
[54]	Teledyne CARIS, Inc. CARIS HIPS and SIPS, Version: 10.2.2[EB/OL]. [2019-06-10]. http://www.teledynecaris.com/docs/4.4.11/hips%20and%20sips/index.html#page/CARIS%2520HIPS%2520and%2520SIPS%2520Help%2FA26A69.html%23.

Instrument	Model	Accuracy
Multi-beam Sonar	Reson Seabat 7125	Depth accuracy: 6mm
Positioning	NavCom SF-3050	<0.1m
Heading	—	±0.1° seclat RMS
Heave	IXBlue Octans III	±5cm or 5% RMS
Roll, pitch	—	±0.01° RMS
Tide level	RBRduo T.D\|tide	±0.05% full scale
Surface sound velocity	Reson SVP 70	±0.05m/s
Sound velocity profile	RBR concerto C.T.D	±0.2m/s

No.	CUBE parameter groups	μ_filter	S.A. (%)						G.A./m N.D.
No.	CUBE parameter groups	μ_filter	MACA	MACR	MRCA	MRCR	MACA+ MRCR	MRCA+ MRCR	G.A./m N.D.
1	Default	1.5×Std	94.72	0.831	4.063	0.383	95.10	4.894	0.08
2	Default	2.5×Std	95.37	0.182	4.071	0.375	95.75	4.253	0.06
3	Default	3.5×Std	94.51	0.195	4.915	0.381	94.89	5.110	0.12
4	Deep	2.5×Std	94.93	0.742	3.939	0.385	95.32	4.681	0.09
5	Shallow	2.5×Std	95.85	0.114	3.537	0.502	96.35	3.651	0.03
6	NOAA	2.5×Std	95.98	0.102	3.385	0.532	96.51	3.487	0.03

Parameters	Optimal parameter	Parameter range	Step
μ_captdistsca	0.5	0.1-20	0.25
μ_captdistmin	0.71	0-2	0.1
μ_hes	1.96	0.05-5	0.25
h_estimoff	4	0.1-10	0.5
μ_filter(×Std)	2.5	0.5-5	0.5