Research Of Filtering Algorithm Based On The SINS/Beidou Integrated Navigation With High Performance

The integrated navigation system's location accuracy and reliability both are better than that of a single navigation system,thus it will become one of the main directions of future navigation research.Information fusion technology is the core of the integrated navigation system and will directly affect the accuracy and reliability of the system.Nowaday,satellite navigation technology is a symbol of a country's overall national strength.Therefore,researching the data fusion technology between the BeiDou satellite navigation system and the Strapdown Inertial Navigation System(SINS)is of great significance.In this paper,it proposes a fuzzy adaptive Square-root embedded-volume Kalman filter algorithm based on Square-root Embedded Cubature Kalman Filter to solve the uncertainty of the statistical characteristics of the measurement noise in the integrated navigation system,which based on the research of the existing integrated navigation nonlinear filtering algorithm in the SINS/BeiDou tightly integrated navigation system.The new algorithm continuously adjusts the weight coefficient of the measurement noise covariance matrix through the principle of fuzzy inference and the adaptive filtering algorithm,so that the measured noise of the model gradually approaches the real noise,thereby improving the accuracy of the system.In this paper,it simulates the scenes of flight trajectory generator,inertial measurement components and Beidou satellite navigation constellation,and establishes the SINS/BeiDou tightly integrated navigation model,in order to verify the application performance of Adaptive Fuzzy Square-root Embedded Cubature Kalman Filter algorithm in SINS/BeiDou tightly integrated navigation system.The Embedded Cubature Kalman Filter,Square-root Embedded Cubature Kalman Filter and Adaptive Fuzzy Square-root Embedded Cubature Kalman Filter are applied to the SINS/Beibu tightly integrated navigation system to vertify the performance of the algorithm in integrated navigation data fusion filtering by the simulations.The simulation results show that the fuzzy adaptive root mean square embedded Kalman filter algorithm is adaptive to the time-variable noise measurement,which effectively improves the SINS/BeiDoufusion accuracy compared to the other algorithms.And the new algorithm is an effective and feasible integrated navigation information fusion algorithm.