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Optimal information fusion Kalman filtering for WSNs with multiplicative noise

The optimal information fusion Kalman filter for wireless sensor network systems is studied. There are two subsystems, and the corresponding measurements are from two different wireless channels, where the system is corrupted by multiplicative noises. Based on the probability method and the scalar weighting optimal information fusion criterion in the minimum variance sense, the information fusion Kalman filter for wireless sensor networks with packet loss and multiplicative noises is given.