Event-Triggered State Estimation for Wireless Sensor Network Systems With Packet Losses and Correlated Noises

Peng Wu,Li Wang,Jiping Xu,Lu Jiang,Xiaoyi Wang

doi:10.1109/access.2020.3041596

Peng Wu, Li Wang + Show 3 more

Open Access

https://doi.org/10.1109/access.2020.3041596

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Journal: IEEE Access	Publication Date: Jan 1, 2020
Citations: 26	License type: CC BY 4.0

Affiliation: Beijing Technology and Business University

Abstract

In this article, an event-triggered state estimation problem for wireless sensor network systems affected by random packet losses and correlated noises is considered. A set of independent Bernoulli variables are used to describe the random packet losses in the measurement transmission. An event-triggered transmission strategy is introduced to decrease limited network bandwidth consumption, and the measurement noise is correlated with the process noises of the same moment and the previous moment. Event-triggered estimator of process noises under the linear minimum variance criterion is derived. Then, an event-triggered state estimation algorithm related to the packet loss rate, noise correlation coefficient and triggering threshold is designed. Sufficient conditions are provided to guarantee convergence of the estimation error covariances of the proposed estimator. Finally, comparative simulation verifies the effectiveness of our algorithm.

Highlights

In the past few years, due to its high accuracy, low cost, and flexible network settings, the state estimation of wireless sensor network systems (WSNs) has received extensive attention
Motivated by the above analysis, the purpose of this article is to solve the problem of event-triggered state estimation for bandwidth-constrained wireless sensor network systems subject to random transmission packet losses and correlated noises
The major contributions of this article are summarized as follows: (i) So as to avoid unnecessary data transmission, an event-triggered transmission mechanism is designed to determine whether measurements are transmitted to the estimator; VOLUME 8, 2020 (ii) Based on the above strategy and iterative estimation of process noise estimator, an event-triggered state estimation algorithm associate to packet loss rate, triggering threshold and noise correlation coefficient is proposed; (iii) Sufficient conditions associated to packet loss rate, event-triggered threshold and noise correlation coefficient are given to ensure the boundedness of the proposed algorithm

Summary

INTRODUCTION

In the past few years, due to its high accuracy, low cost, and flexible network settings, the state estimation of wireless sensor network systems (WSNs) has received extensive attention. Motivated by the above analysis, the purpose of this article is to solve the problem of event-triggered state estimation for bandwidth-constrained wireless sensor network systems subject to random transmission packet losses and correlated noises. (ii) Based on the above strategy and iterative estimation of process noise estimator, an event-triggered state estimation algorithm associate to packet loss rate, triggering threshold and noise correlation coefficient is proposed;. (iii) Sufficient conditions associated to packet loss rate, event-triggered threshold and noise correlation coefficient are given to ensure the boundedness of the proposed algorithm.

PROBLEM FORMULATION

STATE ESTIMATION ALGORITHM WITH

EVENT-TRIGGERED KALMAN FILTER WITH RANDOM PACKET LOSSES AND CORRELATED NOISES

SIMULATION

CONCLUSION