Research On SINS/BDS Ultra-tight Integrated Navigation Method Based On CKF Algorithm

Nowadays,satellite navigation technology plays a pivotal role in various fields,and countries all over the world are vigorously developing and building satellite navigation systems.Since the single navigation system has some limitations and its reliability is low in high dynamic environment,the combined navigation system has become a hot research topic.Among the combination of combined navigation systems,the super tight combination has the advantages of high positioning accuracy and good dynamic performance compared with the loose and tight combination.Therefore,in this paper,we investigate the filtering algorithm based on the ultra-tight integrated navigation system of Strap-down Inertial Navigation System(SINS)and Beidou Navigation System(BDS).In this paper,three commonly used nonlinear filtering methods,Extended Kalman Filter(EKF),Unscented Kalman Filter(UKF),and Cubature Kalman Filter(CKF),are compared and analyzed for the strong nonlinear characteristics of the ultra-tight combined navigation system.The CKF algorithm has a rigorous mathematical inference process and the best filtering effect.However,in the recursive process,the covariance array tends to lose symmetric positivity and cannot be decomposed,and it is still sensitive to changes in the conditional environment.To address this problem,this paper proposes the Fuzzy Adaptive Strong Tracking Cubature Kalman filter(FASTCKF)based on the traditional CKF algorithm,which introduces a suboptimal asymptotic elimination factor to make the residual sequence always satisfy the positivity,and by This algorithm introduces a suboptimal fading factor so that the residual sequence always satisfies the positive characterization,and improves the filtering accuracy through adaptive and fuzzy inference criteria so that the measurement noise continuously approximates the real noise.In order to verify the effectiveness of the proposed algorithm in the ultra-tight integrated navigation system,this paper also builds a BDS/SINS ultra-tight integrated navigation system simulation platform,designs a carrier trajectory generator,SINS system simulator,BDS receiver simulator and integrated navigation filter,and constructs BDS/SINS ultra-tight integrated navigation mathematical model.The Cubature Kalman filter algorithm,Strong Tracking Cubature Kalman filter algorithm and Fuzzy Adaptive Strong Tracking Cubature Kalman filter algorithm are also added into the simulation platform.The simulation results show that the Fuzzy Adaptive Strong Tracking Cubature Kalman filtering algorithm proposed in this paper has good adaptivity and tracking ability compared with the other two algorithms,and effectively improves the filtering accuracy in the ultra-tight integrated navigation system,which is a feasible and effective filtering algorithm.