Abstract:

In order to balance the contradiction between the communication rate and the filtering precision of the networked nonlinear filtering system, two kinds of event-triggered mechanisms based on stochastic event-triggered and detected event-triggered were proposed respectively. The framework of cubature Kalman filter (CKF) was designed under two kinds of event driving mechanisms on account of nonlinear of system, and the mathematical description of the update process was deduced. Two algorithms of detected event-triggered CKF (DECKF) and stochastic event-triggered CKF (SECKF) were obtained. Finally, ECKF was applied to the space-based spatial target localization to examine the performance of itself. The results show that the position and velocity tracking accuracy of DECKF are 5.50% and 7.74% lower than traditional CKF when the communication rate had declined by 20.64%. On the other hand, the accuracy of the DECKF was above 40% higher than the SECKF under the same communication rate, which demonstrated the effectiveness of the DECKF.

Key words:

networked state estimation, stochastic event-triggered; detected event-triggered, cubature Kalman filter, spatial target tracking