Event-triggered Kalman Consensus Filter with Intermittent Measurements and Its Application to the Electro-optical Sensor Network

doi:10.3969/j.issn.1000-1093.2018.04.001

Abstract

Abstract: This paper focuses on the problem of the too much communication amount of the Kalman consensus filtering (KCF) algorithm in the distributed state estimation. An event-triggered mechanism is proposed to decrease the communication amount among nodes, meanwhile ensuring the estimation accuracy and the consensus of estimated values of each node. The corresponding estimation algorithm is derived. The boundedness of estimated error of the proposed algorithm is also proven. The proposed algorithm is tested in an electro-optical sensor network with intermittent measurements. The result shows that, compared with the classical Kalman consensus filtering algorithm, the proposed algorithm can save the network’s communication resources and ensure the estimation accuracy of each node in the network. Key

Key words: electro-opticalsensornetwork, distributedestimationalgorithm, intermittentmeasurement, event-triggeredmechanism, Kalmanconsensusfilter

CLC Number:

CHEN Ye, SHENG An-dong, QI Guo-qing, LI Yin-ya. Event-triggered Kalman Consensus Filter with Intermittent Measurements and Its Application to the Electro-optical Sensor Network[J]. Acta Armamentarii, 2018, 39(4): 625-634.

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第39卷
第4期2018 年4月兵工学报ACTA
ARMAMENTARIIVol.39No.4Apr.2018

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