基于 EM 估计的多模型车载组合导航算法
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TN967. 2

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国家自然科学基金(51807086)、甘肃省教育厅青年博士基金(2021QB047)项目资助


A multi-model vehicle integrated navigation algorithm based on EM estimation
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    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% 。

    Abstract:

    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.

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朱东琴,王红茹,岳敬轩.基于 EM 估计的多模型车载组合导航算法[J].仪器仪表学报,2022,43(7):239-246

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  • 在线发布日期: 2023-02-06
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