基于贝叶斯估计噪声相关下的CKF设计  

Design of CKF with correlative noises based on Bayesian estimation

作　　者：钱华明[1] 葛磊[1] 黄蔚[1] 刘璇[2] 

机构地区：[1]哈尔滨工程大学自动化学院,黑龙江哈尔滨150001 [2]黑龙江科技学院电气与信息工程学院,黑龙江哈尔滨150029

出　　处：《系统工程与电子技术》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

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.

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 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]