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This note studies the problem of distributed estimation for jump Markov nonlinear systems (JMNLSs) in a not fully connected sensor network. Based on the consensus theory, a distributed unscented Kalman filter (UKF) is first derived for nonlinear systems without jumping parameters and then it is extended to develop a distributed multiple model UKF for JMNLSs. The proposed filtering algorithm is illustrated via a simulation example involving tracking a maneuvering target.
Li et al. (Wed,) studied this question.