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- W2893171598 abstract "I266 order to improve the accuracy and reliability of ship dynamic positioning system, a nonlinear state estimation algorithm for dynamic positioning control system based on unscented Kalman filter (UKF) and particle filter (PF) is designed. The algorithm uses PF as its framework, and uses UKF as the recommended density function to optimize the particle state and guide particle sampling. The low frequency state of the ship is estimated according to the weight distribution of each particle. The simulation results show that the nonlinear observer can effectively separate the low frequency motion of ship from the integrated motion with high frequency and noise disturbance. The simulation results verify the effectiveness of the proposed algorithm." @default.
- W2893171598 created "2018-10-05" @default.
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- W2893171598 date "2018-05-01" @default.
- W2893171598 modified "2023-10-17" @default.
- W2893171598 title "A Nonlinear Sate Estimate for Dynamic Positioning Based on Improved Particle Filter" @default.
- W2893171598 cites W2017075731 @default.
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- W2893171598 doi "https://doi.org/10.1109/imcec.2018.8469693" @default.
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