Kalman filtering for linear systems with coefficients driven by a hidden Markov jump process

Abstract

We present an explicit algorithm for the solution of the nonlinear filtering problem concerning a linear, partially observed diffusion-type model, where the coefficients are driven by a hidden Markov jump process, of which one can observe the occurrence of a jump. The (recursive) filter is of a "branching" type with its (finite) dimension growing for each jump of the hidden Markov process. © 1997 Elsevier Science B.V.