免姿态估计的GNSS与IMU集成方法
Attitude-Estimation-Free GNSS and IMU Integration
AI总结：
本研究提出一种免姿态估计的GNSS与IMU集成定位方法，利用加速度大小和陀螺仪角度变化两类约束，在仿真和真实实验中提升定位精度与鲁棒性。
摘要：
全球导航卫星系统（GNSS）是一种能够在地球固定坐标系中获取三维位置和速度的传感器，广泛应用于机器人和车辆在室外环境中的位置估计。为了提升GNSS定位的精度和可用性，研究者们提出了多种GNSS/惯性测量单元（IMU）集成方法。然而，所有这些方法都需要在估计状态中添加三维姿态信息以融合IMU数据。在本研究中，我们提出了一种新的基于优化的定位方法，用于结合GNSS和IMU，该方法无需进行姿态估计。所提出的方法利用两类约束：一类是利用加速度计观测到的三维加速度的大小来约束状态之间的关系，另一类是利用陀螺仪测量的角度变化来约束速度向量之间的夹角。基于仿真数据的评估结果表明，即使IMU安装位置误差增大，所提方法仍能保持位置估计精度，并且在GNSS观测包含多径误差或数据缺失时能够提升精度。在真实环境中获取的IMU进行的实验中，所提方法能够提高定位精度。
英文摘要：
A global navigation satellite system (GNSS) is a sensor that can acquire 3D position and velocity in an earth-fixed coordinate system and is widely used for outdoor position estimation of robots and vehicles. Various GNSS/inertial measurement unit (IMU) integration methods have been proposed to improve the accuracy and availability of GNSS positioning. However, all these methods require the addition of a 3D attitude to the estimated state to fuse the IMU data. In this study, we propose a new optimization-based positioning method for combining GNSS and IMU that does not require attitude estimation. The proposed method uses two types of constraints: one is a constraint between states using only the magnitude of the 3D acceleration observed by an accelerometer, and the other is a constraint on the angle between the velocity vectors using the angular change measured by a gyroscope. The evaluation results with the simulation data show that the proposed method maintains the position estimation accuracy even when the IMU mounting position error increases and improves the accuracy when the GNSS observations contain multipath errors or missing data. The proposed method could improve positioning accuracy in experiments using IMUs acquired in real environments.
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