Combined Uncertainty Multibeam Bathymetry Estimation And Seafloor Terrain Mapping Technique

As a major component of marine environment, the seafloor terrain is important in theocean exploration. The Multi-beam bathymetric technique has become an up-to-datetechnology in contemporary seafloor topography survey and also plays a major part in oceanmonitoring and the investigation of seabed resources. It has been widely applied in manyfields, such as the hydrographic survey, the seabed resources investigation, the underwatertarget detection and the navigation, etc. With the development of science and technology, themultibeam bathymetry system has achieved super wide coverage measurement and highresolution measurement. Moreover, the amount of high-density bathymetric data collected hasreached the magnitude of one million, ten millions and even more. The automatic signalprocessing and the seafloor mapping on large amount of bathymetric data are importanttechniques in multibeam bathymetric data post-processing, which is an important and reliableapplication of the data and has been a hot yet a difficult research issue for a long time. Tomeet the demand of developing the wide-coverage multibeam bathymetry sonar in shallowwater in the country and also to follow the recent development of the techniques world widelyin multibeam bathymetric data post-processing, this thesis is devoted to four research aspects,namely the algorithm to automatically detect and eliminate the outliers in multibeambathymetric data, the multibeam bathymetry estimation based on the combined uncertainty,the modeling and visualization techniques in the seafloor digital terrain with large amount ofdata and the fast generation of the iso-depth contours. More specific contents are as follows.The first part of the thesis is devoted to developing the algorithm in automaticallydetecting and eliminating outlier in bathymetric data. After analyzing and the existing threemethods and comparing their advantages and disadvantages respectively, a robust automaticoutlier detection and elimination algorithm based on the trimmed least squares estimation isproposed. The detection performance of the algorithm for discrete outliers and the clusters hasbeen proved by computer simulation. According to the distribution characteristics ofmultibeam bathymetric data points, a dynamic threshold associated with the global and thelocal variance is proposed as the threshold for outlier detection, the applicability andefficiency of this dynamic threshold have been verified by computer simulations. After that,the outlier detection and elimination have been carried out using real multibeam bathymetricdata in the thesis and the results have confirmed this newly proposed method is effective andapplicable. The second part of this thesis has been devoted to the multibeam bathymetry estimationbased on the combined uncertainty. Various factors affecting the uncertainty of multibeambathymetric data are analyzed. Then, in order to obtain the horizontal and vertical uncertaintyof actual multibeam bathymetric data, the propagation models for multibeam bathymetricuncertainty are established. After that, the multibeam bathymetry estimation based on thecombined uncertainty is discussed using the horizontal and vertical uncertainty of each ofsounding. Following that, a node depth prediction method based on the local surface fitting isproposed to give the correct depth estimations for the nodes on the slopes. Moreover, in theend of this part of the thesis, the multiple estimation tracking are discussed and a robustoptimal estimation selecting rule is proposed based on the local average depth optimum. Theprocessing results using the data from sea trials have confirmed the robustness andeffectiveness of multibeam bathymetry estimation based on the combined uncertainty.The third part of the thesis is devoted to the fast modeling and visualization of theseafloor terrain. A dynamic block dividing and merging mechanism is proposed based on theincomplete binary tree after studying the fast modeling of the seafloor terrain using largeamount of multibeam bathymetric data. By firstly dividing the large amount of data in thesurvey area into several blocks and then constructing Delaunay triangulations in eachsub-block individually, the subtriangulations are merged in a regressive order to form aintegrated triangulation mesh. To deal with the low efficiency and low robustness oftriangulation procedure caused by both the uncertain distribution of sounding points and thecomplexity of the merging algorithm during the subtriangulation merging, towards the end ofthis part of the thesis, a bidirectional sew algorithm is proposed associated with the crossvector product test. The processing results of actual bathymetric data has confirmed that thebidirectional sew algorithm is effective and robust.The final part of the thesis is devoted to the fast algorithm in generating the iso-depthcontours in the seafloor. To efficiently generate the contours from large amount of seafloorterrain data, a fast algorithm of contours generation is proposed based on the indexingsequence of iso-depth values. The algorithm transforms the original triangulation net of floatdepth values to integer indexes. Following that, a fast decision-making method based on0/1exclusive-OR is proposed for telling the contour alignment, which finally accomplishescontours tracing and their fast generation. Moreover, the cubic B-spline function method isadopted for contour smoothing after the comparison with the cubic Bezier function method.By processing actual multibeam bathymetric data, the contours generation based on theindexing sequence of iso-depth values is proved to be effective and robust and the Cubic B-spline function method to be applicable.