Distributed Unscented Kalman Filtering for Nonlinear Complex Networks Over Energy Harvesting Full-Duplex Relay Channels

This work investigates the unscented Kalman filtering for discrete-time nonlinear complex networks with full-duplex relays and binary encoding schemes. To ensure reliable signal transmission in long-range communication scenarios with limited resources and challenging maintenance conditions, an energy-harvesting full-duplex relay is introduced between the sensor and the filter. A self-interference cancellation technique is further applied to suppress the interference generated inside the relay. A binary encoding scheme is employed to save bandwidth, with Bernoulli random variables characterizing the random bit-flip behavior. An improved distributed unscented Kalman filter is developed to minimize the supremum of the filtering error covariance. Furthermore, a sufficient condition is derived to guarantee that the filtering error is exponentially bounded in the mean-square sense. Finally, several numerical examples demonstrate the effectiveness and feasibility of the developed approach.