文章基本信息

标题：Nonlinear Gaussian Filter with Multi-Step Colored Noise
本地全文：下载
作者：Yidi Teng ; Shouzhao Sheng ; Yubin Zheng 等
期刊名称：Actuators
电子版ISSN：2076-0825
出版年度：2022
卷号：11
期号：4
页码：103
DOI：10.3390/act11040103
语种：English
出版社：MDPI Publishing
摘要：Color noise is a special kind of noise often occurring in localization systems, and it is more suitable than the general Gaussian white noise to model time dependence due to time delay or high-frequency sampling. This paper derives a nonlinear Gaussian filtering framework for multi-step colored noise systems using noise whitening techniques and Bayes rule. Meanwhile, the cubature rule is used to solve the Gaussian-weighted integral in the proposed Gaussian filtering framework, resulting in an analytic form of posterior state estimate. Compared with the existing nonlinear filtering algorithms, the proposed method has obvious advantages in colored noise systems because it fully takes into account the time dependence of colored noise. Finally, the effectiveness and advantages of the proposed algorithm are verified with a classical target tracking system.