Timestamp-Free Clock Parameters Tracking Using Extended Kalman Filtering in Wireless Sensor Networks

Abstract

Clock synchronization is crucial for applications in wireless sensor networks, such as event scheduling and data fusion. In practical wireless networks, environmental changes cause the oscillator to be imperfect. Thus, it is necessary to track the nonlinear varying clock dynamically. In this paper, we propose a timestamp-free clock skew (frequency difference) and offset (time difference) joint tracking algorithm based on extended Kalman filter (EKF), which can be embedded into the general network data flow to achieve long-term synchronization without additional communication overhead. To further improve energy efficiency of clock synchronization, this paper develops an EKF clock skew tracking algorithm for silent nodes in receiver-only synchronization. For the situation that silent node overhears synchronization information from multiple active nodes, we present multi-information timestamp-free synchronization and multi-observation clock skew fusion scheme for silent nodes. Simulation results show the effectiveness of the proposed tracking algorithms.