Research On Multi-source Seamless Autonomous Navigation Method Of UUV

Unmanned underwater vehicle(UUV),as a kind of Marine equipment with high intelligence degree and strong autonomous navigation ability,plays an irreplaceable role in the exploration,development and utilization of Marine resources.Navigation system needs to provide high-precision navigation and positioning function to ensure that UUV can reach the operation position safely.However,due to the diversity and time variation of the underwater environment and the limitation of science and technology,the single navigation method can not meet the requirements of UUV for the accuracy of navigation system.Therefore,it is of great significance to design an integrated navigation system with high precision,good fault tolerance and strong robustness by making full use of navigation equipment carried by UUV In this paper,UUV navigation system is taken as the research object,and the integrated navigation system and multi-source information fusion algorithm are studied.The main research contents are as follows:First of all,the navigation coordinate system used in the process of UUV navigation and the transformation relationship between different coordinate systems are summarized,and the working principles of the strapdown inertial navigation system,Doppler velocimetry(DVL),magnetic compass(MCP)and terrain aided navigation system(TAN)used in this paper are analyzed.the errors of different navigation systems are analyzed.Then,the principle and limitations of discrete Kalman filter is studied.The working principle of extended Kalman filter and untraced Kalman filtering are expounded for the nonlinear system and the robust adaptive filter algorithm is studied for the inaccuracy of the mathematical model of the system noise.The Sage-Husa adaptive filter algorithm is introduced emphatically.Thirdly,the structure and algorithm of federated Kalman filter are analyzed for UUV integrated navigation system.The structure of integrated navigation system was built according to the navigation equipment carried by UUV.The framework of federated Kalman filter integrated navigation system was designed,and the mathematical model of multi-source information fusion navigation system was established.The information allocation problem of federated Kalman filter is studied.Three commonly used adaptive information allocation methods are introduced,and the advantages and disadvantages of the three methods are compared by simulation.Finally,an adaptive interactive multi-model algorithm is designed to solve the problem of system noise model change caused by underwater environment change.The algorithm consists of two parts.One is to adjust the parameters of the process noise covariance matrix by using the simplified Sage-Husa adaptive filtering method to solve the problem of process noise model uncertainty.In the other part,the interactive multi-model method is adopted to deal with the problem of measuring the noise of the system.Different models are organized into a set,and corresponding models or mixed models are selected from the model sets to describe the measuring noise.The seamless switching of system models is realized.In order to solve the problem of large amount of computation when covering various models in the interactive multimodel method,an adaptive interactive multi-model method was proposed,which solved the problem by establishing a set near the value after measuring noise estimation.Finally,the simulation results show that this method can effectively control the influence of system noise model uncertainty on navigation accuracy.