Research On AUV Intergrated Navigation Technology Based On SINS/LBL Tightly Coupled Algorithm

High precision navigation is one of the main technical challenges for the underwater vehicle, with the underwater navigation technology developing towards multi-technique and multiple information fusion, research on integrated navigation of SINS and underwater acoustic positioning technology is of great significance. Aimed at the shortages of the existing SINS/LBL integrated navigation technology, this paper researches an AUV underwater integrated navigation system based on SINS/LBL tightly coupled algorithm, the whole navigation system is composed of SINS installed on the carrier, the sound source. DVL. MCP and LBL acoustic positioning array, and in order to achieve the AUV underwater high precision, high reliability and stability navigation. This paper mainly includes five aspects as follows:Firstly, according to the requirements of the design of the underwater integrated navigation system, the general structure scheme of underwater integrated navigation system which with SINS as the main part and LBL, DVL, MCP as complementary was designed.Secondly, in order to solve the fuzzy correlation peaks problem caused by underwater propagation multipath of LBL sound signal, combined with the characteristics of the underwater integrated navigation system, a SINS-assisted LBL method to search the optimal TDOA was proposed. Using the BELLHOP software to build underwater acoustic propagation model, and verify the SINS-assisted LBL method to search the optimal TDOA algorithm, the simulation results show that the algorithm solves interference of multipath effect to the optimum TDOA estimation and has higher TDOA calculation accuracy.Thirdly, a SINS/LBL tightly coupled algorithm was proposed. This algorithm used slant-range difference as an observation variable for filtering, could effectively and regularly compensate the AUV underwater navigation position cumulative error. Moreover, this tightly coupled algorithm still could provide accurate location information when there are fewer than four available hydrophones (or within the signal receiving range). Therefore, effective positional calibration area of tightly coupled system based on LBL array is wider and has higher reliability and fault tolerance than loosely coupled.Fourthly, considering the diversity of information and high dimension, this paper designed an information fusion algorithm for underwater navigation system based on federated Kalman filter, and the state and measurement equations for SINS/LBL, SINS/DVL and SINS/MCP sub-system were established. The simulation results show that the underwater navigation system based on federated filters has higher accuracy and better fault tolerance.At last, the influence of nonlinear measurement equations of SINS/LBL tightly coupled system to the accuracy of filter studied. The fundamental theory of EKF and UKF were analysed, and the nonlinear measurement equations for EKF and UKF were established. Finally, compared the positioning accuracy between Kalman filter, EKF and UKF, and the results show that UKF has higher accuracy than EKF and Kalman filter, EKF and Kalman filter are equivalent under conditions of weak nonlinear measurement equation.