Research On Underwater Positioning Technology Based On The Data Fusion Of Electric Field And Magnetic Field

This paper studies the improvement and innovative methods of underwater non-acoustic positioning technology.Underwater non-acoustic positioning methods include underwater electric field positioning,underwater magnetic field positioning,underwater thermal imaging positioning,etc.Different from traditional underwater acoustic and visual perception signal positioning methods,non-acoustic positioning systems can accurately locate targets in muddy and dark underwater environments.Electric field and magnetic field data fusion positioning technology also belongs to non-acoustic positioning.The related achievements and systems of this technology can be applied to the positioning and tracking of underwater submarines,underwater rescue and salvage,underwater precision docking,marine resource exploration and mining,marine life protection and tracking,and locating illegal electric fishing boats.There are two improvements in this article,namely:An optimization algorithm for fusion positioning of underwater electric field and magnetic field data is proposed;improved Elman neural network training method to train a nonlinear electromagnetic parameter positioning model.The research content mainly includes the theoretical analysis of the volatilization models of electric and magnetic field excitation sources,the study of electric field and magnetic field data fusion positioning methods,and the design of three aspects of the positioning system.First,the forward model of electric field positioning and magnetic field positioning is theoretically analyzed,the electric field and magnetic field volatilization models and scatter laws of the target source are studied,and the electric field and magnetic field hybrid sensor array is designed.Then,on the basis of the traditional Gauss-Newton iterative algorithm,aiming at the problem of insufficient characteristic information of electric field positioning method,an electric and magnetic field data fusion locating algorithm and improved algorithm of electromagnetic fusion based on Elastic Net Regression.The positioning scheme is designed through CST,and the performance and feasibility of the positioning algorithm are analyzed.the simulation positioning accuracy of the electric field positioning algorithm is 0.170mm,the positioning accuracy of the magnetic field positioning algorithm is 0.336mm,and the positioning accuracy of the electric field and magnetic field data fusion positioning algorithm is 0.087mm in every 1000m~3 positioning area.The magnetic field data fusion positioning algorithm improves the positioning accuracy of the underwater positioning system.The calculation speed of the electric field and magnetic field data fusion positioning algorithm is 4times that of the electric field(magnetic field)positioning algorithm.Research the method of nonlinear neural network(BP neural network and Elman neural network)training multi-parameter positioning model to enhance the self-adjust feature and stability of locating system.An enhanced way for training the locating model with mixed parameters of electric and magnetic field is deduced,and experiment verifys that this way can validly enhance the stability of the device.Finally,finish the devise and implementation of an underwater target locating device based on the fusion of electric and magnetic field data.The positioning system achieves fast array operation and high-accuracy positioning,can track the target trajectory,and meets the design requirements of the electromagnetic positioning system.Realize the electric field and magnetic field fusion positioning system based on nonlinear neural network,complete the positioning and tracking functions.Finally,the design and implementation of the underwater target positioning system based on the fusion of electric field and magnetic field data is completed.The algorithm positioning system is realized,including fast array operation,high-precision positioning and tracking of target trajectory.In the 27000cm~3 positioning area,the positioning accuracy of the algorithm positioning mode is 1.63cm,which meets the design requirements of the electromagnetic positioning system.The electric field and magnetic field fusion positioning system based on nonlinear neural network is realized,and the positioning and tracking functions are completed.Within 27000cm~3 positioning areas,the positioning accuracy of the neural network positioning mode is 1.61cm.The results show that in the laboratory environment,the electric field and magnetic field data fusion positioning technology studied in this paper can improve the positioning accuracy,anti-interference ability and real-time data processing ability of the underwater positioning system.