Research On The Application Of Robust CKF Algorithm In Integrated Navigation

With the development of science and technology,the application of global satellite navigation system has covered aerospace,navigation,communication,personnel tracking,real-time monitoring and management of vehicles,car navigation and information services.Although the single satellite navigation system has high accuracy and stability in practical applications,it has the disadvantages of signal occlusion,poor anti-interference ability,and low data output frequency.In order to overcome the shortcomings of the single navigation system and achieve complementary performance,this paper combines the BeiDou Navigation Satellite System(BDS)and the Strap-down Inertial Navigation System(SINS).The BDS/SINS integrated navigation system has the advantages of improving system accuracy,strong anti-interference ability,and reducing the requirement for inertial navigation performance.On this basis,the problems of volume Kalman filter algorithm in the initial alignment of inertial navigation,and the strong nonlinearity and observation error of the integrated navigation system lead to the study of covariance matrix negative and filter divergence.In view of this,this paper carried out the following research:(1)For the harsh engineering environment,the initial alignment error model has been unable to meet the demand,and the SINS-based robust SRCKF(resistance square root volume Kalman filter)error model is established.In the actual engineering,the system model noise is uncertain,the standard CKF may have divergence problem,and the robust SRCKF algorithm is used for filtering.The robust SRCKF algorithm can guarantee the numerical calculation stability and eliminate the gross error to the volume Kalman filter(CKF),there by suppressing the divergence of the filter,further improving the stability of the filter.(2)Based on the research of the anti-difference CKF algorithm in the initial alignment of inertial navigation,in order to further study the effectiveness of the improved CKF algorithm in the integrated navigation system,it is necessary to design the carrier trajectory generator to complete the relevant simulation data.The generation,through the Kalman filter,completes the design of the integrated navigation system.The results show that the integrated navigation system can further apply the anti-difference CKF to the integrated navigation based on the application of the anti-difference CKF to the initial alignment of the inertial navigation.(3)Under the influence of observation error and dynamic model error,the precision of the standard CKF algorithm in integrated navigation decreases or even diverges.The robust adaptive SRCKF algorithm is proposed,which improves the stability of numerical calculation.For observation error and matrix positive definite Sexual problem,by introducing the M estimation theory,the Huber method is used to solve the equivalence weight matrix;for the dynamic model error problem,the selection of the adaptive factor is solved.Simulation results show the effectiveness of the improved algorithm.The improved algorithm in this paper improves the robustness and navigation accuracy of the integrated navigation system.