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Frontiers of Information Technology & Electronic Engineering >> 2021, Volume 22, Issue 1 doi: 10.1631/FITEE.2000206

Freshness constraints of an age of information based event-triggered Kalman consensus filter algorithm over a wireless sensor network

Affiliation(s): College of Information Engineering and Automation, Civil Aviation University of China, Tianjin 300300, China; Department of Mechanical, Industrial and Aerospace Engineering, Concordia University, Montreal, Quebec H3G 1M8, Canada; less

Received: 2020-04-30 Accepted: 2021-01-11 Available online: 2021-01-11

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Abstract

This paper presents the design of a new event-triggered Kalman consensus filter (ET-KCF) algorithm for use over a wireless sensor network (WSN). This algorithm is based on information freshness, which is calculated as the of the sampled data. The proposed algorithm integrates the traditional , information freshness calculation method, and Kalman consensus filter (KCF) algorithm to estimate the concentrations of pollutants in the aircraft more efficiently. The proposed method also considers the influence of data packet loss and the aircraft’s loss of communication path over the WSN, and presents an AoI-freshness-based threshold selection method for the ET-KCF algorithm, which compares the packet AoI to the minimum average AoI of the system. This method can obviously reduce the energy consumption because the transmission of expired information is reduced. Finally, the convergence of the algorithm is proved using the Lyapunov stability theory and matrix theory. Simulation results show that this algorithm has better fault tolerance compared to the existing KCF and lower power consumption than other ET-KCFs.

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