船载 GNSS/INS 集成导航系统的稳健因子图优化方法

IF 1.4 4区 管理学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC Iet Radar Sonar and Navigation Pub Date : 2023-12-09 DOI:10.1049/rsn2.12521
Yuan Hu, Haozheng Li, Wei Liu
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引用次数: 0

摘要

在基于因子图优化的综合导航系统中引入了稳健的全球导航卫星系统(GNSS)因子,以解决船舶导航过程中全球导航卫星系统(GNSS)信号被遮挡而导致定位结果误差增大的难题。为增强 GNSS 跟踪环路的鲁棒性,对接收器跟踪环路采用了矢量跟踪方法。然后,采用 Mahalanobis 距离评估伪距残差,并识别和剔除显示异常的信号。具体来说,伪距残差是根据 GNSS 接收机的预测伪距与测量伪距之间的差值计算得出的。利用窗口中的历史信息,构建了稳健的 GNSS 因子,供因子图使用。通过构建稳健的 GNSS 因子和惯性测量单元因子,实现了船载 GNSS/ 惯性导航系统集成导航系统的稳健因子图优化方法。实验结果证实,所提方法的定位精度优于因子图优化法和扩展卡尔曼滤波法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Robust factor graph optimisation method for shipborne GNSS/INS integrated navigation system

Robust Global Navigation Satellite System (GNSS) factors are introduced into a factor graph optimisation based integrated navigation system to address the challenge of occluded GNSS signals during ship navigation, which leads to increased errors in positioning results. To enhance the robustness of the GNSS tracking loop, a vector tracking method is applied to receiver tracking loop. Then, the Mahalanobis distance was employed to assess the pseudorange residual and identify and reject signals that exhibit anomalies. Specifically, the pseudorange residual is computed as the difference between the predicted pseudorange of the GNSS receiver and the measured pseudorange. Using the historical information in the window, robust GNSS factors were constructed for use in the factor graph. The robust factor graph optimisation method for a shipborne GNSS/Inertial Navigation System integrated navigation system was implemented by constructing robust GNSS factors and Inertial Measurement Unit factors. The experimental results confirm that the positioning accuracy of the proposed method is superior to those of the factor graph optimization and extended Kalman filter.

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来源期刊
Iet Radar Sonar and Navigation
Iet Radar Sonar and Navigation 工程技术-电信学
CiteScore
4.10
自引率
11.80%
发文量
137
审稿时长
3.4 months
期刊介绍: IET Radar, Sonar & Navigation covers the theory and practice of systems and signals for radar, sonar, radiolocation, navigation, and surveillance purposes, in aerospace and terrestrial applications. Examples include advances in waveform design, clutter and detection, electronic warfare, adaptive array and superresolution methods, tracking algorithms, synthetic aperture, and target recognition techniques.
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