摘要
针对常规容积卡尔曼滤波(cubature Kalman filter,CKF)要求系统噪声和量测噪声必须互不相关的局限性,提出了一种带相关噪声的非线性离散系统CKF设计方法。基于贝叶斯估计准则,给出了系统噪声和量测噪声相关时CKF滤波递推公式,并采用三阶球面-相径容积规则来近似计算系统状态的后验均值和协方差。当系统噪声和量测噪声相关时,常规CKF不适用,本文设计的噪声相关下的CKF可以有效地对状态进行估计,拓展了CKF的应用范围。数值仿真验证了算法的有效性。
According to the limitation that the conventional cubature Kalman filter （CKF） requires system and measurement noise to be uncorrelated, a novel CKF with correlative noises for nonlinear discrete-time Gaussian systems is designed. A set of recursive filtering equations of CKF with correlative noises are derived based on Bayesian estimation rule, and the third-order spherical-radial cubature rule is utilized to approximate the postrior mean and covariance of the state. The proposed method can estimate the state as a conventional CKF is unavailable when the system and measurement noise are correlative Gaussian white noises, which expends the application of CKF. The effectiveness of the proposed method is verified by a numerical simulation example.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2012年第11期2214-2218,共5页
Systems Engineering and Electronics
基金
国家自然科学基金(61104036)资助课题
关键词
非线性高斯系统
噪声相关的容积卡尔曼滤波
贝叶斯估计
三阶球面-相径容积规则
nonlinear Gaussian system
cubature Kalman filter （CKF） with correlative noises
Bayesian estimation
third order spherical-radial cuhature rule
