Missile-borne BDS/SINS deep integration self-adaptive CKF filtering method

Abstract

The invention discloses a missile-borne BDS / SINS deep integration self-adaptive CKF filtering method. The method comprises the following steps: firstly, setting a flight path of a ballistic missile and generating IMU data by a path generator; secondly, generating instant medium-frequency data by using the flight path of the ballistic missile through a satellite signal simulator, providing the instant medium-frequency data to a software receiver for satellite navigation solution and carrying out strap-down inertial navigation solution on the generated IMU data; thirdly, establishing a BDS / SINSdeep integration navigation system model under an emission inertial system; finally, introducing a multiple suboptimal fading factor into a standard volume Kalman filter to form a self-adaptive volumeKalman filter; and outputting correction information of the system through optimal estimation of the self-adaptive volume Kalman filter. The missile-borne BDS / SINS deep integration self-adaptive CKFfiltering method disclosed by the invention has the advantages that a better tracking effect on the rapidly-changed system state is realized, and navigation precision and robustness of the BDS / SINS deep integration navigation system in the high dynamic and strong interference environment are improved.

Description

technical field [0001] The invention relates to the field of BDS / SINS integrated navigation, in particular to a missile-borne BDS / SINS deep combined adaptive CKF filtering method. Background technique [0002] The deep integrated navigation of BDS and SINS is a deeper integrated navigation method. In addition to the processing of loose or tight combination, it also uses the original measurement information or navigation information of INS to assist the signal tracking loop of the receiver. The state of the navigation filter is updated by sampling in the in-phase or quadrature BDS receiver channel. The carrier controller and code generator receive the output correction from the navigation filter, which can obtain higher carrier phase tracking bandwidth and anti-corrosion. Interference ability. The deep integrated navigation system is used in the high dynamic and strong interference carrier motion environment, and the drastic changes in the angular rate and linear motion of t...

AI Technical Summary

Problems solved by technology

The CKF filtering algorithm is based on the accurate system mathematical model and noise characteristic information. In the actual environment, the accuracy of the system mathematical model and noise characteristic information is low, and the high dynamic and strong nonlinear characteristics of ballistic missiles make it necessary to To solve the navigation performance of CKF when the model and noise characteristics are inaccurate, it is necessary to study the adaptive filtering algorithm and apply it to CKF

At present, the inaccurate CKF filter model and noise characteristics of ballistic missiles in high dynamic and strong interference environments will have an impact on the system, resulting in low positioning accuracy and poor robustness of the system

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