摘要
针对行车过程中车载全球卫星导航系统受遮挡产生多径效应、可见星数量少等影响,造成的定位精度差的问题,提出了一种基于期望最大化(EM)的交互式多模型车载组合导航算法。本文采用了混合高斯分布模型描述GNSS多径效应误差分布,提出了基于EM的SINS/GNSS子系统组合导航信息融合方法,实现多径效应偏置误差的估计。建立了基于零速约束的SINS/OD组合导航模型,同时利用交互式多模型算法实现了在GNSS信号丢失情况下的导航模型交互融合,提高了车载组合导航系统精度。车载实验结果表明在GNSS多径效应及信息丢失条件下,本文所提出算法能有效提高导航精度,多径效应的混合高斯模型偏置为10 m条件下,偏置估计误差小于0.5 m,水平最大定位误差为2 m,比传统交互式多模型算法定位误差降低84.62%。
The multi-path effect caused by occlusion and small number of visible stars in the vehicle global satellite navigation system during driving result in poor positioning accuracy, an interactive multi model vehicle integrated navigation algorithm based on EM is proposed. In this article, the mixed Gaussian distribution model is used to describe the error distribution of GNSS multipath effect, and the SINS/GNSS integrated navigation subsystem information fusion method based on EM is proposed to estimate the offset error of multipath effect. The SINS/OD integrated navigation model based on zero speed constraint is formulated. Meanwhile, the interactive multi model algorithm is utilized to realize the interactive fusion of navigation models in the case of GNSS signal loss, which improves the accuracy of the vehicle integrated navigation system. Vehicle experiment results show that the proposed algorithm can effectively improve the navigation accuracy under the conditions of GNSS multipath effect and information loss. When the offset of Gaussian mixture model of multipath effect is 10 m, the offset estimation error is less than 0.5 m, and the maximum horizontal positioning error is 2 m, which is 84.62% lower than that of traditional interactive multi model algorithm.
作者
朱东琴
王红茹
岳敬轩
Zhu Dongqin;Wang Hongru;Yue Jingxuan(School of Information and Communication Engineering,Harbin Engineering University,Harbin 150001,China)
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2022年第7期239-246,共8页
Chinese Journal of Scientific Instrument
关键词
EM
车载组合导航
交互式多模型
多径效应
EM
vehicle integrated navigation
interactive multi model
multipath effect
