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Improvement of RTK-GNSS with Low-Cost Sensors Based on Accurate Vehicle Motion Estimation Using GNSS Doppler

机译:基于GNSS多普勒的精确​​车辆运动估计,利用低成本传感器的提高RTK-GNSS

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摘要

This study proposes a method for estimating the positions of vehicles in urban environments with high accuracy. We employ satellite positioning by GNSS for position estimation. Real-time kinematic-global navigation satellite systems (RTK-GNSS) with high precision in satellite positioning can estimate positions with centimeter-scale accuracy. However, in urban areas, the position estimation performance deteriorates owing to multipath errors. Therefore, we propose a method to improve the positioning results by increasing the robustness against multipath using vehicle trajectory. The vehicle trajectory estimates the travel route using the attitude angle and speed. Attitude angles are heading, pitching and slip angle. Trajectories can be generated with 0.5m error performance per 100m. In the proposed method, the trajectory is used as a constraint to solve the multipath of RTK-GNSS. In the evaluation test, the ratio of high-accuracy position estimation improved by up to approximately 30% compared to the conventional method. It is assumed that this method can enhance the development of self-driving cars, AGV control and SLAM technology by eliminating errors and calculating reliability.
机译:本研究提出了一种以高精度估算城市环境中车辆位置的方法。我们使用GNSS进行卫星定位进行位置估计。实时运动 - 全球导航卫星系统(RTK-GNSS)具有高精度的卫星定位可以估计厘米级精度的位置。然而,在城市地区,由于多径误差,位置估计性能恶化。因此,我们提出了一种方法来通过使用车辆轨迹增加对多径的鲁棒性来改善定位结果。车辆轨迹使用姿态角度和速度估计行驶路线。姿态角度是标题,俯仰和滑动角度。轨迹可以产生0.5米的0.5米误差每100米。在该方法中,轨迹用作解决RTK-GNSS的多径的约束。与传统方法相比,在评估测试中,高精度位置估计的比率高达约30%。假设该方法可以通过消除误差和计算可靠性来增强自动驾驶汽车,AGV控制和SLAM技术的开发。

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