面向跟踪系统的多传感器信息融合鲁棒保性能协方差交叉Kalman估计方法  

Tracking System-Oriented Multi-Sensor Information Fusion Robust Guaranteed Cost Covariance Intersection Kalman Estimation Method

作　　者：杨智博[1,2] 杨春山[1] 邓自立[1] 

机构地区：[1]黑龙江大学自动化系,黑龙江哈尔滨150080 [2]北华大学,吉林吉林132021

出　　处：《电子学报》2017年第7期1627-1636,共10页Acta Electronica Sinica

基　　金：国家自然科学基金(No.NSFC-60874063;No.NSFC-60374026)

摘　　要：对带不确定方差线性相关白噪声的多传感器系统,根据极大极小鲁棒估计原理,用Lyapunov方程方法,基于不确定噪声方差扰动的参数化表示法提出两类鲁棒保性能协方差交叉(CI)融合Kalman估值器(预报器、滤波器和平滑器),给出其精度偏差的最大下界和最小上界.证明了保性能CI融合器的鲁棒精度高于原始CI融合器的鲁棒精度,且高于每个局部估值器的鲁棒精度,并用协方差椭圆给出精度关系的几何解释.一个跟踪系统的仿真例子验证了所提方法的正确性和有效性.For the multi-sensor systems with uncertain-variance linearly correlated white noises,according to the minimax robust estimation principle,and by the Lyapunov equation approach,the two classes of guaranteed cost robust covariance intersection（ CI） fusion Kalman estimators（ predictor,filter,smoother） are presented based on the parameterization representation of the uncertain noise variance perturbations. Both the minimal upper bound and the maximal lower bound of the accuracy deviations are given. It is proved the robust accuracy of the guaranteed cost CI fuser is higher than that of the original CI fuser,and is higher than that of each local estimator,and the geometric interpretation of accuracy relation is given by the covariance ellipses. A simulation example applied to tracking system verifies the correctness and effectiveness of the proposed method.

关 键 词：不确定噪声方差 线性相关噪声 协方差交叉融合 Lyapunov方程方法 跟踪系统 

分 类 号：O211.64[理学—概率论与数理统计]