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Dynamic initial alignment of the MEMS-based low-cost SINS for AUV based on unscented Kalman filter

机译:基于无味卡尔曼滤波器的用于AUV的基于MEMS的低成本SINS的动态初始对准

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For the high-speed and light Autonomous Underwater Vehicle (AUV), it is moving freely, and the speed and attitude are in dynamic movement. And for the micro electromechanical system (MEMS) technology based low-cost strapdown inertial navigation system (SINS), over too large bias drift errors not only made the system functions nonlinear, but also made the estimation for misalignment angle converge to a false value. Therefore, this paper concerns the MEMS-based low-cost SINS initial alignment under the dynamic movement with large initial error. A nonlinear mathematics model of SINS initial alignment has been derived. The nonlinear filter unscented Kalman filter (UKF) is investigated in the nonlinear system to estimate the initial attitude and the MEMS sensor biases simultaneously. The simulation indicated that the algorithm is suitable for initial alignment.
机译:对于高速轻型自主水下航行器(AUV),它可以自由移动,并且速度和姿态处于动态运动中。对于基于微机电系统(MEMS)技术的低成本捷联惯性导航系统(SINS),过大的偏置漂移误差不仅会使系统功能变为非线性,而且会使偏心角的估计收敛到错误的值。因此,本文涉及具有大初始误差的动态运动下基于MEMS的低成本SINS初始对准。推导了捷联惯导初始对准的非线性数学模型。在非线性系统中研究了非线性滤波器无味卡尔曼滤波器(UKF),以同时估计初始姿态和MEMS传感器偏置。仿真表明该算法适用于初始比对。

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