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 Estimat...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.展开更多
基金National Natural Science Foundation of China(Nos.4190606941830540)+1 种基金The Scientific Research Fund of the Second Institute of Oceanography,Ministry of Natural Resources(Nos.JG2005SZ2002)。
文摘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.
