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首页> 外文期刊>The Journal of Navigation >In-motion Alignment for Low-cost SINS/GPS under Random Misalignment Angles
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In-motion Alignment for Low-cost SINS/GPS under Random Misalignment Angles

机译：随机未对准角度下低成本SINS / GPS的运动中对准

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摘要

This paper presents a reliable in-motion alignment algorithm for a low cost Strapdown Inertial Navigation System/Global Positioning System (SINS/GPS) combination under random misalignment angles, which transforms attitude alignment into an attitude estimation problem. Based on Rodrigues parameters, an alignment model with a linear state-space equation and a second order nonlinear measurement equation is established. Furthermore, by employing a Taylor expansion on the nonlinear measurement equation, we implement a second order Extended Kalman Filter (EKF2). The proposed method uses a single filter that can not only determine the initial attitude, but also estimate the sensor errors. In addition, a scheme is given for avoiding singularity, which makes the algorithm more widely suitable for random misalignment angles. Experimental ground tests are performed with a low-cost Micro-Electromechanical System (MEMS) SINS, which validates the efficacy of the proposed method. The performance compared to the traditional alignment algorithm is also given.
机译：本文针对随机失准角下的低成本捷联惯性导航系统/全球定位系统（SINS / GPS）组合提出了一种可靠的运动对准算法，该算法将姿态对准转化为姿态估计问题。基于罗德里格斯参数，建立了具有线性状态空间方程和二阶非线性测量方程的对准模型。此外，通过对非线性测量方程采用泰勒展开，我们实现了二阶扩展卡尔曼滤波器（EKF2）。所提出的方法使用单个滤波器，该滤波器不仅可以确定初始姿态，而且可以估计传感器误差。另外，给出了避免奇异性的方案，这使得该算法更广泛地适用于随机未对准角度。使用低成本的微机电系统（MEMS）SINS进行了实验性地面测试，验证了所提出方法的有效性。还给出了与传统对齐算法相比的性能。

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