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Velocity Aided, Correlated Noise Extended Kalman Filtering for Attitude Estimation: a Motorcycle Case Study

机译:速度辅助,相关噪声扩展卡尔曼滤波态度估计:摩托车案例研究

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Vehicle attitude estimation is nowadays essential for a wide range of applications, e.g. guidance of unmanned vehicles, robotics and automotive controls. In this paper, the attitude estimation problem is solved by means of a velocity-aided, Extended Kalman Filter with correlated noise (CEKF), exploiting the intrinsic correlation between sensor noise in a velocity-aided model. Reconstruction of a motorcycle attitude is considered as a use case. The problem is addressed in a simulation scenario under noisy measurements. Performance of the CEKF is compared to that of the classic EKF formulation by evaluating the RMS of the reconstruction error.
机译:现在,车辆姿态估计对于广泛的应用是必不可少的,例如, 无人驾驶车辆,机器人和汽车控制的指导。 在本文中,通过速度辅助的延伸卡尔曼滤波器解决了姿态估计问题,具有相关噪声(CEKF),利用速度辅助模型中的传感器噪声之间的内在相关性。 重建摩托车态度被认为是用例。 在噪声测量下的仿真方案中解决了问题。 通过评估重建误差的RMS来将CEKF的性能与经典EKF制定的性能进行比较。

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