Paper Info
Title
Distributed Filtering for Multi-sensor Systems with Missing Data
Abstract
•Missing data from measurements of sensor itself and estimates of neighbor nodes.•Three distributed Kalman filter algorithms: ODKF, SDKF, and PDKF are designed.•Kalman filter gain and multi-consensus filter gains are designed in LUMV sense.•Mean boundedness of ODKF and steady-state properties of SDKF and PDKF.•Relationship of estimation accuracy of three distributed Kalman filters.
Year
DOI
Venue
2022
10.1016/j.inffus.2022.06.007
Information Fusion
Keywords
DocType
Volume
Distributed Kalman filter,Missing data,Multi-sensor system,LUMV,Steady-state property
Journal
86-87
ISSN
Citations 
PageRank 
1566-2535
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Hao Jin100.34
Shuli Sun273452.41