Research On The Technology Of Online Calibration For Strapdown Inertial Navigation System

At present,the discrete calibration and systematic calibration of SINS have been very muture,but the scheme of online calibration has not been so effective.The technology of online calibraion for SINS is researched in order to realize the high precision autonomous navigation and provide the theoretical basis and method reference for improving navigation accuracy with marine FOG SINS.The main work is as follows:Firstly,the discrete calibration and systematic calibration is studied.To begin with,the discrete calibration is presented,including the models of inertial sensors and the principle of 24-postion experiment and rate experiment.Then,the systematic calibration is presented,including the error models and the principle of transfer arrangement.As well,the results of mathematic simulation verify that the nine-postion systematic calibration can improve the precision of SINS effectively.Finally,the advantages and disadvantages of calibration methods are compared.Secondly,according to the principle of online calibration and model predictive filtering,an adaptive model predictive combinatorial filtering algorithm for online calibration is proposed to improve the residual error of the inertial sensors.First of all,an online calibration scheme is designed for the specific application object,and the Kalman filter state equation and measurement equation are established.Then,using the observability analysis method based on singular value decompostion,the obsercability of inertial sensers' errors under different maneuvering modes is studied and the simulation experiments are carried out.After that,an adaptive model predictive combination filtering algorithm is designed for the problem that Gaussian white noise is assumed for both model error and system noise,and the priciple and process are presented.Finally,a variety of general trajectory simulation experiments and online calibration simulation experiments are designed.The experimental results indicate that the designed algorithm is better than conventional Kalman filtering algorithm under the same maneuvering path.The calibration effects of IMU under different maneuvering path schemes are also analyzed.Thirdly,the principle of FOG SINS online calibration are carried out.Firstly,the process of online calibration algorithm is designed,and the online calibration combined scheme which is based on velocity and heading information is presented.Secondly,three-axis turntable experiments are provided to test and verify the correctness and universal applicability of the discrete calibration and systematic calibration.At last,according to the applicability of the online caliration,the semi-physical simulation experiments are carried out.Through analysis of the results,the correctness,effectiveness and practicality of the online calibration algorithm based on velocity and heading information is further verified.