Distributed Kalman consensus filter with event-triggered communication: Formulation and stability analysis

This paper deals with the distributed estimation problem for networked sensing system with event-triggered communication schedules on both sensor-to-estimator channel and estimator-to-estimator chan-nel. Firstly, an optimal event-triggered Kalman consensus filter (KCF) is derived by minimizing the mean squared error of each estimator based on the send-on-delta triggered protocol. Then, the subop-timal event-triggered KCF is proposed in order to reduce the computational complexity in covariance propagation. Moreover, the formal stability analysis of the estimation error is provided by using the Lyapunov-based approach. Finally, simulation results are presented to demonstrate the effectiveness of the proposed filter. (C) 2017 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.