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Gaussian mixture model UKF for BDS/INS navigation system

DAI Qing;SUI Lifen;WANG Lingxuan;ZENG Tian;TIAN Yuan;Institute of Geospatial Information,Information Engineering University;Chongqing Water Resources and Electric Engineering College;  
To improve the performance of unscented kalman filter(UKF)algorithm in BDS/SINS navigation system,on the background of non-Gaussian distribution in the navigation system model an improved Gaussian mixture model unscented kalman filter(GM-UKF)is discussed in this paper.The new algorithm is based on Singular Value Decomposition(SVD)to alternative covariance square root calculation in sigma point production.And to end the rapidly increase number of Gaussian distributions,pdf re-approximation is conducted in the new algorithm.In principle the efficiency algorithm proposed here can achieve higher computational speed compared with GM-UKF.And the simulation experiment results show that,compared with the UKF and GM-UKF algorithm,the new algorithm implemented in BDS and SINS tightly integrated navigation system is suitable for handling non-linear non-Gaussian filter calculation problem,for its low computational complexity with high accuracy.
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