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A fast initial alignment for SINS based on disturbance observer and Kalman filter

机译:基于干扰观测器和卡尔曼滤波器的捷联惯导快速初始对准

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Initial alignment for a strap-down inertial navigation system (SINS) plays an important role in the following navigation and positioning operation. Initial alignment incorporates two stages: coarse and fine. This paper mainly investigates fine alignment for SINS under static base. A new fast SINS initial alignment scheme, a disturbance observer-based Kalman filter (DOBKF), is proposed to estimate the misalignment angles. As the name implies, the DOBKF is composed of a Kalman filter and a disturbance observer (DO). The Kalman filter is used to estimate horizontal misalignment angles, and the DO is applied to estimate the azimuth misalignment angle. In addition, when the estimations from the Kalman filter reach a steady state, they will be used as input for designing the DO. Compared with traditional filters, such as a Kalman filter used in initial alignment, the filter proposed by this paper not only greatly hastens the overall initial alignment process, but has comparable accuracy. Comparing simulation results shows that the proposed filter satisfies the requirement of SINS alignment.
机译:捷联惯性导航系统(SINS)的初始对准在随后的导航和定位操作中起着重要作用。初始对齐包括两个阶段:粗略和精细。本文主要研究静态基础下捷联惯导系统的精细对准。提出了一种新的快速捷联惯导初始对准方案,即基于干扰观测器的卡尔曼滤波器(DOBKF)来估计失准角。顾名思义,DOBKF由卡尔曼滤波器和干扰观测器(DO)组成。卡尔曼滤波器用于估计水平偏心角,而DO用于估计方位偏心角。另外,当来自卡尔曼滤波器的估计达到稳态时,它们将用作设计DO的输入。与传统的滤波器(例如用于初始对准的卡尔曼滤波器)相比,本文提出的滤波器不仅大大加快了整个初始对准过程,而且具有相当的精度。仿真结果比较表明,所提出的滤波器满足SINS对准的要求。

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