Gyroscope-Aided Odometry Navigation Using a Highly-Precise Automotive MEMS IMU Complemented by a Low-Cost Sensor Array

Lukas Blocher, W. Mayer, Miloš Vujadinović, J. Haack, Johannes Hofele, Dusan Radovic, T. Hiller, J. Gerlach, O. Bringmann
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引用次数: 1

Abstract

This paper examines vehicle navigation employing a redundant array of two different types of MEMS inertial sensors in combination with wheel speed sensors. We compare the position precision of a purely inertial strap-down algorithm with motion-constraints (SMC, [1]) to gyroscope-aided odometry navigation (GAO). An RTK-corrected GNSS was used in parallel to generate the reference trajectory. Initial heading of both methods was determined by a dual-antenna GNSS moving baseline setup. Across five repeated experiments with a traveled distance of 1600 m over 275 s each, GAO delivered a mean RMSE of 4.36 m, whereas SMC resulted in errors of 634 m. For GAO, we show that initial heading error was dominant compared to the influences of gyroscope noise. Determining accurate initial heading is therefore deemed crucial for applications with prolonged GNSS outages.
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利用高精度汽车MEMS IMU辅以低成本传感器阵列的陀螺仪辅助里程计导航
本文研究了采用两种不同类型的MEMS惯性传感器的冗余阵列与轮速传感器相结合的车辆导航。我们比较了带有运动约束的纯惯性捷联算法(SMC,[1])与陀螺仪辅助里程导航(GAO)的位置精度。并行使用rtk校正的GNSS生成参考弹道。两种方法的初始航向均通过双天线GNSS移动基线设置确定。在5次重复实验中,GAO的平均RMSE为4.36 m,而SMC的误差为634 m,每次实验距离为1600 m,每次实验时间为275 s。对于GAO,我们发现初始航向误差比陀螺仪噪声的影响更重要。因此,确定准确的初始航向对于GNSS长时间中断的应用至关重要。
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