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一种低成本车载GPS辅助惯性导航系统

2020-12-07 13:45:06 ai52learn

本文为瑞典皇家理工学院(作者:ISAAC SKOG)的硕士论文,共49页。

 

本文介绍了一种GPS与惯性导航系统(INS)的集成方法。推导了以地球为中心的地球固定惯性导航系统的连续时间导航和误差方程。采用零阶保持采样,将方程组离散化。推导了GPS与INS闭环积分的扩展卡尔曼滤波器。滤波器对误差状态进行传播和估计,并将误差状态反馈给惯性导航系统进行内部导航状态校正。该算法在上位机上实现,上位机通过串口接收来自定制硬件平台的GPS和惯性测量值,并对其进行了简要讨论。最后给出了系统的仿真结果。

 

In this report an approach for integration between GPS and inertial navigation systems (INS) is described. The continuous-time navigation and error equations for an earth-centered earth-fixed INS system are derived. Using zero order hold sampling, the set of equations is discretized. An extended Kalman filter for closed loop integration between the GPS and INS is derived. The filter propagates and estimates the error states, which are fed back to the INS for correction of the internal navigation states. The integration algorithm is implemented on a host PC, which receives the GPS and inertial measurements via the serial port from a tailor made hardware platform, which is briefly discussed. Simulation results of the system are presented.

 

1.  引言

2.  坐标系统

3.  惯性导航方程

4.  离散化

5.  GPS与INS的集成

6.  硬件

7.  仿真结果

8.  结论与展望

附录A卡尔曼滤波器

 

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https://update.blog.csdn.net/article/details/110792237