On Line Calibration Technique Of Strapdown Inertial Navigation System Based On Strong Tracking CKF

With the development of science and technology, the exploration of the ocean is also constantly improving, the requirements of the maritime navigation system is also increasingly stringent. This paper mainly adopts the research methods of theoretical analysis and computer simulation of combining the strapdown inertial navigation system based on the calibration of online, shipborne FOG Strapdown Inertial Navigation calibration by winds, currents and so on many interference factors in the ship cruise, will cause the system to model uncertain and unpredictable noise, to solve these problems, this paper will study the principle of strong tracking filter and CKF filter,based on CKF filtering and strong tracking filtering algorithm,design a system can overcome the uncertainty of the model, the noise can not be predicted the disadvantages in the system can reach a stable state can own strong tracking filtering algorithm for tracking CKF mutation state. And the strong tracking volume Calman filter is applied to the on-line calibration of nonlinear strapdown inertial navigation system. The specific work of this paper includes:First of all, this paper introduces the background of the subject and the significance of the research. The development of on-line calibration technology and the research status of nonlinear filter at home and abroad are introduced briefly in this paper. The error model of the inertial navigation system is analyzed, and the nonlinear error equation of the strapdown inertial navigation system under the linear error equations and dynamic conditions is established.Secondly, the details of the cubature Kalman filter technology, analysis of the spherical-radial cubature criteria and derivation of the cubature Kalman filtering algorithm,next CKF is derived based on the strong tracking CKF algorithm and strong tracking filtering,and through a series of nonlinear simulation model and compared the results of CKF and strong tracking cubature Kalman filtering. The simulation results show that, under the same simulation conditions and initial state, strong tracking CKF is higher than the cubature Kalman filtering precision, is a kind of nonlinear filtering of CKF is better than to illustrate the advantages of strong tracking CKF. The filtering model of nonlinear SINS navigation system based on largeazimuth misalignment angle is established. The global observability analysis of inertial device error observability, and then choose the optimal incentive path calibration for ship design methods.The paper finally, from the theoretical analysis, based on setting up the output error model of inertial device, the error equation based on the rotation scheme of fiber optic gyro strapdown inertial navigation system and analysising observability, select reasonable state variables and measured variables; simulation analysis is carried out on the basis of the above research, in different misalignment conditions, respectively, using EKF, CKF and CKF strong tracking filtering method for parameter estimation, comparing the three filtering methods of filtering effect. The experimental results verify the superiority of the strong tracking CKF filtering algorithm, and verify the online calibration scheme and the accuracy of the filter algorithm.