Robust Weighted Measurement Fusion Kalman Filter with Uncertain Parameters and Noise Variances

摘要：

　　For the multisensor time-invariant system with both the uncertainties noise variances and parameters,by introducing a fictitious white noise to compensate the uncertain parameters,based on the minimax robust estimation principle and the Lyapunov equation method,a robust weighted measurement fusion Kalman filter is presented.It is proved that for prescribed upper bound variance of fictitious noise,there exists a sufficiently small robust region of uncertain parameter perturbances,such that its actual filtering error variances are guaranteed to have a conservative upper bound.A simulation example shows how to search the robust region,and shows its good performances.

关键词： Uncertain parameters Uncertain noise variances Fictitious white noise Weighted measurement fusion Minimax robust Kalman filter

作者: Chunshan Yang Zili Deng

作者单位: Department of Automation,Heilongjiang University,XueFu Road 74,Heilongjiang University,Electronic an Department of Automation,Heilongjiang University,XueFu Road 74,Heilongjiang University,Electronic an

会议类型: 国际会议

会议名称: The 2015 Chinese Intelligent Automation Conference(2015中国智能自动化会议)

会议地点: 福州

会议语种:英文

页码: 33-41

在线出版日期: 2015-05-08（万方平台首次上网日期，不代表论文的发表时间）