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A New In-Flight Alignment Method with an Application to the Low-Cost SINS/GPS Integrated Navigation System.
Sensors ( IF 3.9 ) Pub Date : 2020-01-16 , DOI: 10.3390/s20020512
Zhenglong Lu 1 , Jie Li 1, 2 , Xi Zhang 3 , Kaiqiang Feng 1 , Xiaokai Wei 1 , Debiao Zhang 1 , Jing Mi 1 , Yang Liu 1
Affiliation  

The optimization-based alignment (OBA) methods, which are implemented by the optimal attitude estimation using vector observations-also called double-vectors-have proven to be effective at solving the in-flight alignment (IFA) problem. However, the traditional OBA methods are not applicable for the low-cost strap-down inertial navigation system (SINS) since the error of double-vectors will be accumulated over time due to the substantial drift of micro-electronic- mechanical system (MEMS) gyroscope. Moreover, the existing optimal estimation method is subject to a large computation burden, which results in a low alignment speed. To address these issues, in this article we propose a new fast IFA method based on modified double-vectors construction and the gradient descent method. To be specific, the modified construction method is implemented by reducing the integration interval and identifying the gyroscope bias during the construction procedure, which improves the accuracy of double-vectors and IFA; the gradient descent scheme is adopted to estimate the optimal attitude of alignment without complex matrix operation, which results in the improvement of alignment speed. The effect of different sizes of mini-batch on the performance of the gradient descent method is also discussed. Extensive simulations and vehicle experiments demonstrate that the proposed method has better accuracy and faster alignment speed than the related traditional methods for the low-cost SINS/global positioning system (GPS) integrated navigation system.

中文翻译:

一种新的空中对准方法及其在低成本SINS / GPS组合导航系统中的应用。

通过使用矢量观测值(也称为双矢量)进行最佳姿态估计来实现的基于优化的对准(OBA)方法已被证明可有效解决飞行中对准(IFA)问题。但是,传统的OBA方法不适用于低成本的捷联惯性导航系统(SINS),因为由于微机电系统(MEMS)的大幅漂移,双矢量的误差会随着时间的推移而累积。陀螺仪。此外,现有的最佳估计方法承受较大的计算负担,导致对准速度低。为了解决这些问题,在本文中,我们提出了一种基于改进的双矢量构造和梯度下降法的新型快速IFA方法。再具体一点,通过在构造过程中减小积分间隔并识别陀螺仪偏置来实现改进的构造方法,从而提高了双矢量和IFA的精度。在不进行复杂矩阵运算的情况下,采用梯度下降法估计最优的对准姿态,从而提高了对准速度。还讨论了不同大小的小批量处理对梯度下降法性能的影响。大量的仿真和车辆实验表明,与低成本SINS /全球定位系统(GPS)组合导航系统的相关传统方法相比,该方法具有更好的准确性和更快的对准速度。从而提高了双向量和IFA的准确性;采用梯度下降方案,无需复杂的矩阵运算就可以估算出最优的对准姿态,从而提高了对准速度。还讨论了不同大小的小批量处理对梯度下降法性能的影响。大量的仿真和车辆实验表明,与低成本SINS /全球定位系统(GPS)组合导航系统的相关传统方法相比,该方法具有更好的准确性和更快的对准速度。从而提高了双向量和IFA的准确性;采用梯度下降方案,无需复杂的矩阵运算就可以估算出最优的对准姿态,从而提高了对准速度。还讨论了不同大小的小批量处理对梯度下降法性能的影响。大量的仿真和车辆实验表明,与低成本SINS /全球定位系统(GPS)组合导航系统的相关传统方法相比,该方法具有更好的准确性和更快的对准速度。还讨论了不同大小的小批量处理对梯度下降法性能的影响。大量的仿真和车辆实验表明,与低成本SINS /全球定位系统(GPS)组合导航系统的相关传统方法相比,该方法具有更好的准确性和更快的对准速度。还讨论了不同大小的小批量处理对梯度下降法性能的影响。大量的仿真和车辆实验表明,与低成本SINS /全球定位系统(GPS)组合导航系统的相关传统方法相比,该方法具有更高的准确性和更快的对准速度。
更新日期:2020-01-16
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