National Key Laboratory for Electronic Measurement Technology, North University of China, Taiyuan 030051, China.
Key Laboratory of Instrumentation Science & Dynamic Measurement, North University of China, Taiyuan 030051, China.
Sensors (Basel). 2020 Jan 16;20(2):512. doi: 10.3390/s20020512.
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.
基于优化的对准（OBA）方法通过使用矢量观测的最佳姿态估计来实现，也称为双矢量，已被证明在解决飞行中对准（IFA）问题方面非常有效。然而，由于微机电系统（MEMS）陀螺仪的大量漂移，传统的 OBA 方法不适用于低成本捷联惯性导航系统（SINS），因为双矢量的误差会随时间累积。此外，现有的最优估计方法计算负担较大，导致对准速度较慢。为了解决这些问题，本文提出了一种新的基于改进双矢量构建和梯度下降法的快速 IFA 方法。具体来说，改进的构建方法通过减少积分间隔和在构建过程中识别陀螺仪偏差来实现，从而提高了双矢量和 IFA 的精度；采用梯度下降方案来估计对准的最优姿态，而无需复杂的矩阵运算，从而提高了对准速度。还讨论了不同大小的小批量对梯度下降法性能的影响。大量的仿真和车辆实验表明，与相关的传统方法相比，该方法在低成本 SINS/GPS 组合导航系统中具有更好的精度和更快的对准速度。
