Research On Underwater AUV Navigation Algorithm With Combining SINS And LBL Systems

Improving the accuracy and stability of underwater navigation and positioning is a major challenge.With the development of science and technology,underwater navigation and positioning technology has developed towards multi-disciplinary intersection and multi-sensor data fusion.Integrated navigation technology has become an inevitable direction for the future development of navigation technology.Therefore,it is of great significance to study the combined navigation technology of inertial navigation technology and acoustic positioning technology.This paper studies a kind of underwater navigation system based on tight combination SINS/LBL.And SINS,LBL,DVL,MCP are the main navigation sensors in this system.In addition,pressure sensors are used to modify the elevation.The whole system designed in this paper is composed of SINS,sonar,MCP,DVL,pressure sensor and long base hydrophone carrier.The main findings and conclusions are summarized below:First,taking SINS as reference navigation system and LBL,DVL,MCP as auxiliary navigation system are selected for the special environment of underwater navigation.And the algorithm and error model of navigation system are analyzed.Based on classical Kalman filtering,the SINS/LBL loose combination mode is studied,and the accuracy and reliability of SINS/LBL loose combination mode in many motion states is verified by design simulation experimentsSecond,the algorithm formula of SINS/LBL tight combination is derived and the oblique distance difference model based on LBL is established.And then the state equation and measurement equation based on tight combination are established Simulation experiments verify the accuracy and reliability of the SINS/LBL tight mode.Aiming at the unknown noise of the integrated navigation system,the adaptive integrated navigation algorithm is studied,and the experimental results show that the adaptive navigation algorithm can obviously improve the navigation accuracy.Meanwhile,considering the complex environment,it is difficult to maintain the base array of underwater hydrophone on the sea floor,and the problem of power supply is persistent.This paper brings forward two LBL intermittent modes of operation,and preliminarily verifies the high accuracy and high efficiency of mode two(LBL operating frequency is 0.2 Hz)through simulation experiments,which provides theoretical basis and reference for the selection of working mode of underwater integrated navigation.Third,the SINS/LBL/DVL/MCP integrated navigation system based on federal Kalman filtering is designed.Three sub-filters of the federal Kalman filter are established,which are SINS/LBL,SINS/DVL,SINS/MCP,and the state equation and measurement equation of each sub-filter are derived.The different combination modes based on federal kalman filtering are compared and analyzed via AUV dynamic simulation experiments.The results show that the tight combination can effectively reduce the dependence and limitation on the number of single sensors such as acoustic transponders compared with the loose combination,and its accuracy and reliability are higher,which is more suitable for multi-sensor integrated navigation and positioning in complex marine environmentFourth,The global optimality of the federated filtering is demonstrated,and the condition of the optimality is that the state dimension of each sub-filter is the same.Based on the theory of federal filtering,an improved federal Kalman filtering is proposed.This method expands the state dimension of the sub-filter of SINS/LBL/DVL/MCP integrated navigation system,and gives the improved state equation and measurement equation.A comparative analysis of centralized Kalman filtering,classical federal filtering and improved federal filtering is carried out through simulation experiments.the experimental results verify the global optimality of the improved federal filtering.