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 per-rurbances, 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.