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Attitude Estimation for Vehicles With Partial Inertial Measurement

机译:带有部分惯性测量的车辆的姿态估计

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摘要

In this paper, a novel method for the estimation of the attitude of an automotive vehicle is presented. The algorithm uses low-cost sensors, namely, a Global Positioning System (GPS) receiver and a three-axis accelerometer. It employs a kinematic model of the vehicle, which is augmented by unknown parameters of the system. An extended Kalman filter (EKF) is employed, which produces estimates of the vehicle attitude, as well as the installation angles of the sensor unit with respect to the vehicle. Compared with existing approaches, it does not require knowledge of the road tilt angle, and it automatically compensates for different installation angles. It is therefore particularly well suited for applications where there is no control over how the unit is installed in the vehicles, as is the case with personal navigation assistants. The method is numerically robust by using nonsingular attitude parametrization; results are given for simulations and real-world experiments.
机译:本文提出了一种估计汽车姿态的新方法。该算法使用低成本传感器,即全球定位系统(GPS)接收器和三轴加速度计。它采用了车辆的运动学模型,该模型通过系统的未知参数得到增强。采用扩展的卡尔曼滤波器(EKF),可产生车辆姿态的估计值,以及传感器单元相对于车辆的安装角度。与现有方法相比,它不需要了解道路倾斜角,并且可以自动补偿不同的安装角度。因此,它特别适用于无法控制单元在车辆中的安装方式的应用,例如个人导航助手。通过使用非奇异的姿态参数化,该方法在数值上是鲁棒的。给出了用于仿真和实际实验的结果。

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