Model-Aided Wind Estimation Method for a Tail-Sitter Aircraft

In this paper, we derive a modified IMM filter for jump Markov systems with unknown process and measurement noise covariances. Using the inverse-Wishart distribution as the conjugate prior of noise covariances, the system state together with the noise parameters for each mode are inferred by the variational Bayesian method. The mixing and output estimates are calculated according to the weighted Kullback-Leibler average of mode-conditioned estimates. Simulation results show the effectiveness of the proposed algorithm.