Performance analysis of state estimation problem over network applying event-based sampling scheme

This paper is concerned with the networked estimation problem in which sensor data are transmitted over the network. In the event-based sampling scheme known as level-crossing or send-on-delta, sensor data are transmitted to the estimator node if the difference between the current sensor value and the last transmitted one is greater than a given threshold. The event-based sampling has been shown to be more efficient than the time-triggered method in some situations, especially in the bandwidth improvement for networks. Motivated by this advantage, we propose a novel sampling method where the sensor node transmits data using event-based sampling scheme but the estimator node estimates the system states periodically. We then formulate a state estimation problem and analyze the estimation performance applying the proposed sampling scheme. Through theoretical analysis and simulation results, we show that the proposed method introduces a better estimation performance than the multirate filter under the same network bandwidth. Therefore, when the proposed sampling scheme is applied, we get benefits from the network bandwidth improvement.