Real-time algorithms for estimating jerk signals from noisy acceleration data
Real-time algorithms for estimating jerk signals from noisy acceleration data
复制标题
用于从噪声加速度数据估计加加速度信号的实时算法
DOI：
10.3233/jae-2003-282
复制
发表时间：
2003
影响因子：
0.6
通讯作者：
H. Inooka
中科院分区：
文献类型：
--
作者：
S. Nakazawa;T. Ishihara;H. Inooka
The time derivative of acceleration, sometimes called a jerk, plays an important role in vibration control, ride comfort evaluation and so on. It is usually required to estimate a jerk from a noisy acceleration signal. Simple numerical differentiation of a filtered acceleration signal often fails to give satisfactory result. A model-based estimation technique is proposed in this paper. Behavior of a jerk signal is modeled by a random walk process. Then the problem of estimating the jerk is formulated as a state estimation problem. On the assumption that the observation noise has a colored noise component, a Kalman filter and an filter are derived for estimating the jerk. The performances of both estimators are compared by simulation. Although both filters provide comparable performances for ideal case, the filter with appropriate use of a priori information has better robustness than the Kalman filter and is more useful in real applications.
