State Estimation via a Serial Network with Different Transmission Periods

This paper considers an estimation problem, where sensors are connected through a serial network and sensor data are sent to the estimation board periodically. A rate monotonic scheduling is used for sensor data packets scheduling. Given the bandwidth, the design parameter affecting estimation error is the transmission period of each sensor. A new optimization algorithm to determine transmission period of each sensor is proposed so that the overall estimation error covariance is small in the Kalman filter framework. The computed transmission period is depending on system models and noise covariances. The proposed algorithm is verified through a numerical simulation