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In-motion initial alignment method for DVL-aided SINS under wave disturbance for AUV

机译:用于AUV波干下的DVL辅助SIN的动作初始对准方法

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This work discusses the implementation of inertial navigation system aided by Doppler Velocity Log (DVL) for the Autonomous Underwater Vehicles (AUV) applications. Due to disturbance from waves, the complicated underwater environment, to achieve Strapdown Inertial Navigation System (SINS) alignment accuracy within a short period of time is still a challenging problem. The difficulty for underwater SINS alignment is in designing the process covariance matrix and measurement noise covariance matrix, worse still, in most practical applications the process covariance matrix R, and measurement noise covariance matrix will change in the process of alignment. This paper highlights the use of fuzzy logic techniques to the adaptation of R, and we introduce the output of DVL as a reference of the change of external environment. And simulation experiment has been designed to evaluate our proposed algorithms, and results show that in our approach the Kalman filter needs less time to converge and has higher precision.
机译:这项工作讨论了用于自主水下车辆(AUV)应用的多普勒速度日志(DVL)辅助的惯性导航系统的实现。由于波浪的干扰,复杂的水下环境,实现截头惯性导航系统(SINS)对准精度在短时间内仍然是一个具有挑战性的问题。水下SINS对准的难度在设计过程协方差矩阵和测量噪声协方差矩阵,更差,在大多数实际应用中,过程协方差矩阵R和测量噪声协方差矩阵将在对齐过程中改变。本文突出了模糊逻辑技术对R的适应,我们将DVL的输出引入外部环境变化的参考。和仿真实验旨在评估我们所提出的算法,结果表明,在我们的方法中,卡尔曼滤波器需要更少的时间来收敛和具有更高的精度。

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