电光与控制, 2019, 26 (4): 66, 网络出版: 2019-05-05
基于因子图的组合导航方法及其可行性研究
Integrated Navigation Based on Graph Optimization Method and Its Feasibility
惯性/卫星组合导航 图优化算法 高斯牛顿迭代法 数据融合 SINS/GNSS integrated navigation graph optimization algorithm Gauss-Newton iteration method information fusion
摘要
复杂环境下进行定位导航, 需要构建全源导航系统, 实现多传感器的即插即用和不同频率的数据融合。研究了一种基于因子图的数据融合方法, 该方法采用因子图法表示状态的递推与更新, 采用高斯牛顿迭代法求解优化方程完成组合导航中的数据融合任务。然后以惯性/卫星组合导航系统为例, 分析了因子图的原理内容, 设计了相应的信息融合框架。最后对该方法的可行性进行了仿真验证, 实验数据表明, 3轴位置的均方根误差值分别为1.53 m, 1.55 m, 1.53 m, 证明了该方法的可行性, 可以在此基础上扩展传感器, 构建全源导航系统。
Abstract
For the positioning and navigation in complex environment,a type of All-Source Positioning and Navigation (ASPN) system needs to be constructed to achieve multi-sensor plug-and-play and data fusion at different frequencies.This paper studies a data fusion method based on factor graphs.This method uses the factor graph method to represent the recursion and update of the state,and uses the Gauss-Newton iteration method to complete the data fusion task by solving the optimization equation in the integrated navigation.Then,taking the SINS/GNSS integrated navigation system as an example,the principle of the factor graph is analyzed and a corresponding information fusion framework is designed.Finally,the feasibility of the method is verified by simulation.The experimental data show that the three-axis position RMSE is 1.53 m,1.55 m and 1.53 m respectively,which proves the feasibility of the method.Based on this,the sensor can be extended to build an ASPN system.
朱晓晗, 陈帅, 蒋长辉, 张博雅, 韩林. 基于因子图的组合导航方法及其可行性研究[J]. 电光与控制, 2019, 26(4): 66. ZHU Xiao-han, CHEN Shuai, JIANG Chang-hui, ZHANG Bo-ya, HAN Lin. Integrated Navigation Based on Graph Optimization Method and Its Feasibility[J]. Electronics Optics & Control, 2019, 26(4): 66.