SENSOR VALIDATION FOR FLIGHT CONTROL BY PARTICLE FILTERING (ThuAmOR5)

Author(s) : Tao Wei (The University of Texas at San Antonio, United States) Yufei Huang (The University of Texas at San Antonio, United States) Philip Chen (The University of Texas at San Antonio, United States)

Abstract : In this paper, we address the problem of adaptive sensor validation for flight control. The model-based approaches are developed, where the sensor system is modeled by a Markov switch dynamic state-space model. To handle the nonlinearity of the problem, two different particle filters: mixture Kalman filter (MKF) and stochastic M-algorithm (SMA) were proposed. Simulation results are presented to compare the effectiveness and complexity of MKF and SMA methods.

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