改进的Unscented Kalman滤波算法  

An Improved Unscented Kalman Filter Algorithm

作　　者：申文斌[1] 裴海龙[1] 

机构地区：[1]华南理工大学自动化科学与工程学院,广东广州510640

出　　处：《计算机工程与科学》2011年第4期192-197,共6页Computer Engineering & Science

基　　金：国家自然科学基金资助项目(60574004);国家自然科学基金资助重点项目(60736024);教育部科技创新工程重大项目培育资金项目(708069)

摘　　要：为了提高UKF的运算效率,本文分析了UKF中各参数对滤波效果的影响,给出了一种系统状态转移矩阵为线性变换时UKF的优化算法,并证明了本算法的正确性。针对野值影响UKF精度的缺陷,本文提出了使用新息判断野值是否存在的检测方法。对于野值存在的情况首先剔除野值,然后根据已经得到的滤波状态应用最小二乘法对当前状态进行预测估计,对于野值不存在的情况直接使用UKF滤波,最后推导了使用最小二乘法拟合野值存在时估计的合理性,从而证明了这种方法可以极大地提高UKF抗野值的能力。本文最后用具体的仿真实例说明了最小二乘法与UKF相结合算法消除野值的有效性。In order to improve the operational efficiency of UKF（Unscented Kalman Filter）,this paper analyzes the effect affected by the parameters in UKF,and then proposes an optimization algorithm of UKF while the state transition matrix of the system is linear,and shows the correctness of the algorithm via the proof.Concerning the defect that the outliers affect the accuracy of UKF,this paper proposes a test method by using the innovation to judge whether the outliers exist or not.When there are some outliers,the algorithm in this paper firstly gets rid of them,and then uses the least square method to estimate the current states based on the states obtained.However,this algorithm directly uses UKF when there is not any outlier,and finally it deduces the rationality of using the least square method to fit the estimates when there are some outliers,so this paper proves that the method improves the ability of UKF to resist the outliers greatly.Finally,this paper presents a concrete simulative example to show the validity of the algorithm,which combines the least square method and UKF.

关 键 词：优化算法 野值 新息 最小二乘法 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]