NDLI: Distributed filtering in sensor networks with hybrid communication constraints

Content Provider	IEEE Xplore Digital Library
Author	Chi Huang Ho, D.W.C. Jianquan Lu Zidong Wang
Copyright Year	2012
Description	Author affiliation: Department of Mathematics, Southeast University, Nanjing, Jiangsu, China (Jianquan Lu) \|\| Department of Mathematics, City University of Hong Kong, Hong Kong, China (Chi Huang; Ho, D.W.C.) \|\| Department of Information Systems and Computing, Brunel University, Uxbridge, United Kingdom (Zidong Wang)
Abstract	This paper is concerned with the distributed H filtering problem for a class of sensor networks with hybrid communication constraints. Three kinds of communications constraints are considered during the process of information transmission among the sensors: (i) the estimation of sensors needs to be sampled before transmitting; (ii) at each sampling instant, the packet dropouts would happen to the sampled data of sensors; (iii) the noise and disturbance exist. It should be noted that the constraints of sampled information and data packet dropouts would lead that less information can be employed for each sensor, which makes the filtering problem in sensor networks more challenging and practical. Some criteria concerning the connection gains are derived and used to design efficient distributed H filter to achieve the following objectives: (i) the filtering error system is exponentially mean-square stable in the absence of disturbance and noise; (ii) the prescribed H performance constraint is satisfied. A numerical example is utilized to illustrate the effectiveness of the theoretical results.
Starting Page	36
Ending Page	41
File Size	170946
Page Count	6
File Format	PDF
ISBN	9781467318716
e-ISBN	9781467318723
e-ISBN	9781467318709
DOI	10.1109/ICARCV.2012.6485130
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-05
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robot sensing systems Noise Symmetric matrices Estimation Educational institutions Protocols
Content Type	Text
Resource Type	Article

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