Real-Time Graph-Based Optimization for GNSS-Doppler Integrated RTK-GNSS/IMU/DR Positioning System in Urban Area
Real-Time Graph-Based Optimization for GNSS-Doppler Integrated RTK-GNSS/IMU/DR Positioning System in Urban Area
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DOI：
10.1109/iv55152.2023.10186672
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发表时间：
2023-06
期刊：
影响因子：
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通讯作者：
Aoki Takanose;E. Takeuchi;Alexander Carballo;J. Meguro;K. Takeda
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文献类型：
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作者：
Aoki Takanose;E. Takeuchi;Alexander Carballo;J. Meguro;K. Takeda
车辆和机器人的自动驾驶需要高度精确的位置信息，RTK-GNSS有望用于这一目的。本文通过将图优化引入到RTK-GNSS/IMU组合方法中，提出了一种鲁棒的实时运算方法。所提出的方法是使用车辆轨迹的方法的扩展，该方法即使在城市地区也可以估计具有车道级精度的位置。通过从几百米的车辆轨迹的形状中去除GNSS多路径并对剩余的GNSS结果求平均来估计位置。这种方法没有考虑车辆轨迹的误差，不能充分利用RTK-GNSS的高精度定位解决方案。为了解决这个问题，我们引入图优化的基本方法，它把错误状态作为一个概率模型。然而，一般的图优化方法具有处理时间和离群点消除的问题。该方法通过限制待优化的时间序列数据和使用两步优化结构来解决这些问题。实验结果表明，该方法能满足实时性要求，且与传统方法相比，提高了精度。
Autonomous driving of vehicles and robots requires highly accurate position information, and RTK-GNSS is expected to be utilized for this purpose. In this paper, we propose a robust and real-time operation method by introducing graph optimization into the integrated RTK-GNSS/IMU method. The proposed method is an extension of a method using vehicle trajectories that can estimate positions with lane-level accuracy even in urban areas. The position is estimated by removing GNSS multipaths from the shape of a vehicle trajectory of several hundred meters and averaging the remaining GNSS results. This method does not take into account the errors in the vehicle trajectory and cannot fully benefit from the high accuracy positioning solution of RTK-GNSS. To solve this problem, we introduce graph optimization to the base method, which treats the error state as a probabilistic model. However, general graph optimization methods have problems with processing time and outlier elimination. The proposed method solves these problems by restricting the time series data to be optimized and using a two-step optimization structure. Evaluations show that the proposed method is effective because it satisfies the requirements for real-time operation and improves accuracy compared to conventional methods.