On Kalman filter for stochastic system with correlated noises based on event-triggered sampling
Chenghan Xie, Yunji Li, Yun Xie, Hao Henry Wang, Li Peng · 2016
In this paper, an event-triggered sensor data transmission scheme for Kalman filtering, whose goal is to guarantee a good trade off between estimation quality and transmission rate, is considered in a linear stochastic system with correlated process and measurement noise. We prove an upper bound on system performance to design this transmission strategy which decides the transfer time of the data packet in detail. A numerical example is given to verify the potential and effectiveness of the theoretical results.