Consensus-based unscented Kalman filter for sensor networks with sensor saturations
Wangyan Li, Guoliang Wei, Fei Han · 2014
In this paper, we devote to investigating the consensus-based unscented Kalman filtering problem for a certain kind of sensor networks with sensor saturations. The communication status among sensors is represented by a connected undirect graph. Saturation phenomenon exists both in the state of the system and individual sensors. Moreover, a distributed unscented Kalman filtering algorithm based on CI (consensus on information) consensus approach is developed to estimate the ture state of interest. Finally, the effectiveness of the proposed consensus-based unscented Kalman filtering scheme is validated through a simulation example.