Event-triggered distributed fusion estimation for multisensor multirate systems with correlated noises and fading measurements

An event-triggered (ET) distributed fusion (DF) estimator is proposed for the multirate multisensor systems with uniform observation sampling rates, correlated noises and fading measurements. In the multirate sampling scheme, the state is updated uniformly and the state update rate is the positive integer multiple of the observation sampling rates. Moreover, the measurement noises of different sensors are correlated and also correlated with the process noise at the same time step. In order to improve the network resource utilization, a variance-based ET mechanism is adopted to determine whether the local estimates are transmitted to the remote fusion center. The matrix weighted optimal DF estimation algorithms is obtained based on the proposed local estimators and cross-covariance matrices. A simulation example is given to illustrate the effectiveness of the algorithm.