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Study on the observability degree of integrated inertial navigation system of autonomous underwater vehicle

机译:自主水下车集成惯性导航系统可观察性程度研究

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摘要

Strapdown inertial navigation system (SINS) initial alignment error model is presented under moving base. SINS navigation error models and the integrated navigation error models are proposed. The state observability during the initial alignment under moving base was thoroughly studied according to the piece-wise constant system method and singular value decomposition method. Simulation experiments were carried out under different vehicle movements with same integration and different integration with same vehicle movements respectively. Simulation experiments show that the observability degree of states variables can be improved under linear or rotation movement, furthermore, the outer measurements aided SINS can also improve the observability degree of system state variables accordingly. The observability degree increases of state variables improve the accuracy of estimation and the speed of convergence of Kalman filter applied in the integrated inertial navigation system.
机译:挂机惯性导航系统(SINS)初始对准误差模型在移动基座下呈现。 SINS导航错误模型和集成导航错误模型。 根据截面恒定的系统方法和奇异值分解方法,彻底研究了在移动基座下初始对准期间的状态可观察性。 在不同的车辆运动下进行模拟实验,分别具有相同的集成和与相同的车辆运动的不同集成。 仿真实验表明,在线性或旋转运动中可以改善状态变量的可观察性程度,此外,外部测量辅助源也可以提高系统状态变量的可观察性程度。 状态变量的可观察性程度增加提高了集成惯性导航系统中应用的卡尔曼滤波器的估计准确性和加密。

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