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Odometer Velocity and Acceleration Estimation Based on Tracking Differentiator Filter for 3D-Reduced Inertial Sensor System

机译:基于跟踪微分滤波器的里程表速度和加速度估计用于减少3D的惯性传感器系统

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摘要

Velocity information from the odometer is the key information in a reduced inertial sensor system (RISS), and is prone to noise corruption. In order to improve the navigation accuracy and reliability of a 3D RISS, a method based on a tracking differentiator (TD) filter was proposed to track odometer velocity and acceleration. With the TD filter, an input signal and its differential signal are estimated fast and accurately to avoid the noise amplification that is brought by the conventional differential method. The TD filter does not depend on an object model, and has less computational complexity. Moreover, the filter phase lag is decreased by the prediction process with the differential signal of the TD filter. In this study, the numerical simulation experiments indicate that the TD filter can achieve a better performance on random noises and outliers than traditional numerical differentiation. The effectiveness of the TD filter on a 3D RISS is demonstrated using a group of offline data that were obtained from an actual vehicle experiment. We conclude that the TD filter can not only quickly and correctly filter velocity and estimate acceleration from the odometer velocity for a 3D RISS, but can also improve the reliability of the 3D RISS.
机译:来自里程表的速度信息是简化惯性传感器系统(RISS)中的关键信息,并且容易造成噪声破坏。为了提高3D RISS的导航精度和可靠性,提出了一种基于跟踪微分(TD)滤波器的里程表速度和加速度跟踪方法。使用TD滤波器,可以快速,准确地估算输入信号及其差分信号,从而避免了常规差分方法带来的噪声放大。 TD滤波器不依赖于对象模型,并且具有较低的计算复杂度。此外,利用TD滤波器的差分信号,通过预测处理来减小滤波器相位滞后。在这项研究中,数值模拟实验表明,TD滤波器在随机噪声和离群值方面比传统的数值微分方法具有更好的性能。 TD滤波器在3D RISS上的有效性通过使用一组从实际车辆实验中获得的离线数据进行了演示。我们得出的结论是,TD滤波器不仅可以快速,正确地过滤速度并根据3D RISS的里程表速度估算加速度,而且还可以提高3D RISS的可靠性。

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