行人GNSS/PDR组合导航优化估计方法

doi:10.12382/bgxb.2022.0557

摘要/Abstract

摘要：

基于全球卫星导航系统(GNSS)和行人航位推算(PDR)的组合导航系统是行人导航广泛采用的方案之一。为进一步提高GNSS/PDR组合导航系统的定位精度,提出一种基于图优化的GNSS/PDR组合导航方法。通过构建因子图表示状态和量测信息之间的概率依存关系,过去的所有状态都作为未知量在每一步进行迭代估计,通过最小化整体代价函数获取状态的最优估计。实际场景测试结果表明:与卡尔曼滤波算法相比,新方法能够进一步降低定位的平均误差,提高定位精度;两组实际场景测试的平均水平定位误差都降低了40%以上。实验结果证明了图优化算法可以有效地提高定位精度。

关键词: 行人导航, 组合导航, 卫星导航, 图优化

Abstract:

The integration of a navigation system based on the Global Navigation Satellite System (GNSS) and the Pedestrian Dead Reckoning (PDR) with inertial measurement data is a widely used and reliable navigation solution. To further improve the positioning accuracy of the GNSS/PDR integrated navigation system, we propose a GNSS/PDR integrated navigation method based on graph optimization. By constructing a factor graph to represent the probabilistic dependence between states and measurement information, all past states are iteratively estimated at each step as the unknowns, and the optimal estimation of the states is obtained by minimizing the global cost function. Compared with the KF algorithm, this new system can further reduce average positioning error and improve positioning accuracy. Results from two different real scene results show that, compared with KF, the average values of the horizontal positioning errors are reduced by more than 40%, verifying the algorithm’s effectiveness in improving the positioning accuracy.

Key words: pedestrian navigation, integrated navigation, global navigation satellite system, factor graph optimization

中图分类号:

TN96
TH89

朱建良, 王立雅, 薄煜明. 行人GNSS/PDR组合导航优化估计方法[J]. 兵工学报, 2023, 44(10): 3137-3145.

ZHU Jianliang, WANG Liya, BO Yuming. Pedestrian GNSS/PDR Integrated Navigation System with Graph Optimization[J]. Acta Armamentarii, 2023, 44(10): 3137-3145.

图/表 15

图1 航位推算位置更新原理

Fig.1 Principle diagram of position updating

图2 智能手机航位推算原理图

Fig.2 Principle diagram of pedestrian positioning based on smartphone function

图3 局部函数分解因子图

Fig.3 Factor graph of local function decomposition

图4 变量依存关系因子图

Fig.4 Factor graph of variable dependency relation

图5 FGO-GNSS/PDR组合导航方法

Fig.5 FGO-GNSS/PDR integrated navigation method

图6 求解过程流程图

Fig.6 Flow chart of the solving process

图7 数据采集装置

Fig.7 Dataset collecting equipment

图8 手持实验1水平位置误差和分布

Fig.8 Hand-held experimental 1 horizontal position errors and distribution

表1 手持实验1水平位置误差统计结果

Table 1 Hand-held experiment 1 statistical results of horizontal position errors

方法	误差均值/m	误差均方根/m
KF-GNSS/PDR	1.48	0.77
FGO-GNSS/PDR	0.83	0.50

图9 手持实验2水平位置误差和分布

Fig.9 Hand-held experiment 2 horizontal position errors and distribution

表2 手持实验2水平位置误差统计结果

Table 2 Hand-held experiment 2 statistical results of horizontal position errors

方法	误差均值/m	误差均方根/m
KF-GNSS/PDR	1.78	1.18
FGO-GNSS/PDR	1.00	0.61

图10 背包实验1水平位置误差和分布

Fig.10 Knapsack experiment 1 horizontal position errors and distribution

图11 背包实验2水平位置误差和分布

Fig.11 Knapsack experiment 2 horizontal position errors and distribution

表3 背包实验1水平位置误差统计结果

Table 3 Knapsack experiment 1 statistical results of horizontal position errors

方法	误差均值/m	误差均方根/m
KF-GNSS/PDR	1.21	0.84
FGO-GNSS/PDR	0.72	0.53

表4 背包实验2水平位置误差统计结果

Table 4 Knapsack experiment 2 statistical results of horizontal position errors

方法	误差均值/m	误差均方根/m
KF-GNSS/PDR	2.34	1.39
FGO-GNSS/PDR	1.03	0.71

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