LTI系统中存在彩色噪声时SMIKF的实现

Fawad Ali, N. Khan, Muhammad Ali, Hamza Ahmad, Muhammad Haris Ikram
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引用次数: 0

摘要

当过程和观测值都考虑为高斯白噪声时,卡尔曼滤波(KF)技术的性能最合适。但是在实时应用程序中,这个假设并不总是正确的。本文研究了带彩色系统噪声(即过程噪声和观测噪声)的增广卡尔曼滤波和基于二阶矩信息的卡尔曼滤波两种卡尔曼滤波技术。简要分析了彩色测量噪声下的增强卡尔曼滤波(AKF)。针对有色过程和观测噪声,提出了改进的卡尔曼滤波方法。为了检验该系统的性能,考虑了一个具有彩色系统噪声的实时质量-弹簧阻尼系统。将该方案的计算量与AKF方案进行了比较。仿真结果验证了所提算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the implementation of SMIKF in LTI systems in the presence of colored noise
The performance of the Kalman Filter (KF) technique is most appropriate when both the process and observation are considered as white Gaussian noise. But in real time applications, this assumption is not always true. Two sorts of Kalman Filtering techniques i.e Augmented Kalman Filtering and Second Moment Information bases Kalman Filtering with colored system noise i.e (process noise and observation noise) are examined in this paper. Augmented Kalman Filtering (AKF) with colored measurement noise is shortly analyzed. Modified Kalman Filtering method (SMIKF) is proposed for colored process and observation noise. In order to check the performance of the system a real-time Mass-Spring Damper system having colored system noises is considered. The computational burdens of the proposed scheme is compared with AKF. The simulation results endorse the Performance of the suggested algorithm.
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