Parallel Kalman filter algorithm for state estimation in bilinear systems

In this paper an algorithm for the state estimation of a class of bilinear systems in the presence of noise is proposed. The systems considered are such that a suitable partition of the state vector into two parts allows a bilinear representation of the system. The proposed algorithm is obtained paralleling two Kalman filters: each of them estimates a part of the state, considering the other part as known time-varying parameters.<
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