Abstract
In this research work, we study on the Cubature Particle filter (CPF) algorithm to calculate the estimate value of GPS/INS integrated navigation system. The error model of the GPS/INS integrated navigation system is nonlinear. CPF is the algorithm built on Cubature Kalman filter (CKF) and Particle filter (PF), which has the advantages of both. CPF may therefore provide a systematic solution for high-dimensional nonlinear filter problems. CPF is presented for simulation. Simulation results show the superior performance of this approach when compared with suboptimal techniques such as Cubature Kalman filter (CKF) in cases of large initial misalignment. The results of simulation demonstrate the improved performance of the CPF over conventional nonlinear filters. The research provides theoretical support for engineering design and modification.
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Acknowledgements
This paper is supported by the National Natural Science Foundation of China (Grant No. 60834005 and 60775001) and the International Exchange Program of Harbin Engineering University for Innovation-oriented Talents Cultivation.
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Li, Q., Sun, F. (2014). Cubature Particle Filter Algorithm Base on Integrated Navigation System. In: Wang, W. (eds) Mechatronics and Automatic Control Systems. Lecture Notes in Electrical Engineering, vol 237. Springer, Cham. https://doi.org/10.1007/978-3-319-01273-5_28
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DOI: https://doi.org/10.1007/978-3-319-01273-5_28
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