Research On Integrated Navigation Algorithm Based On Inertial System And Short Baseline Positioning System

As one of the major tools of exploring ocean,the Autonomous Underwater Vehicle(AUV)has great potentials in military and civilian applications due to its small size and underwater concealment.Therefore,increasing the investment in the field of AUVS is of great importance to the expansion of Chinese military power in the sea.Underwater navigation is an important technology to AUVs.It is one of the necessary requirements for autonomous and intelligent operations of AUVs.The inertial navigation system has always been the primary choice for underwater navigation systems due to its autonomy,small size,and comprehensive output parameters.However,because of its positioning errors that can accumulate over time,it can only provide high-precision information in a short amount of time.It needs to be combined with other auxiliary navigation systems.GPS cannot be used for underwater positioning due to serious attenuation of electromagnetic wave signals in underwater propagation,so the underwater navigation system usually uses acoustic positioning systems to aid inertial navigation systems.The short baseline positioning system is widely used in the integrated navigation and positioning system of micro and small underwater vehicles due to its small array size,relatively simple layout,and high positioning accuracy within a certain range.The thesis is to study the integrated navigation and positioning algorithms to improve navigation accuracy on an existing Remote Operated Vehicle(ROV)equipped with an inertial navigation system and a set of short baseline underwater acoustic positioning equipment.The main research contents of the thesis are as follows1.The principles of the inertial navigation system and the acoustic positioning system are introduced.The error sources of the two types of navigation systems are analyzed,and then the inertial navigation system algorithm used in this thesis is derived.The inertial measurement unit and short baseline positioning systems used in this thesis are introduced The error model of the inertial measurement unit is derived and the noise calibration is performed.Finally,the error model parameters of the inertial measurement unit are determined,and the error compensation is performed by noise calibration.2.The principles of extended Kalman filtering algorithm and unscented Kalman filtering algorithm are introduced.The state of the system is determined based on the combination of inertial navigation system and short baseline positioning system,and two filtering algorithms are derived.Finally,the advantages and disadvantages of the two algorithms are compared and analyzed.3.The detailed implementation of the two algorithms and the selection of the parameters are introduced.Simulation experiments of two algorithms are performed in MATLAB software.The simulation results verify the feasibility of the algorithms and compare the performance of the algorithms.4.The test platform hardware framework and software framework of the integrated navigation system are introduced.The integrated navigation algorithms used in this thesis are verified on the test ROV.The feasibility of the algorithms is verified by analyzing the results of data collected in the lake experiments.