DocumentCode
2036595
Title
Distributed Kalman filtering and Network Tracking Capacity
Author
Das, S. ; Moura, Jose M. F.
Author_Institution
Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA
fYear
2013
fDate
3-6 Nov. 2013
Firstpage
629
Lastpage
633
Abstract
We propose and study a new distributed Kalman filter algorithm that can track unstable dynamics with bounded mean-squared error (MSE). The Network Tracking Capacity (NTC) of this algorithm depends only on the diffusion rate of the network and is independent of the local observation patterns, only requiring global observability. We analyze and compare the NTC for different network models.
Keywords
Kalman filters; mean square error methods; object tracking; observability; MSE; NTC; bounded mean-squared error; distributed Kalman filter algorithm; global observability; network tracking capacity; observation patterns; Heuristic algorithms; Kalman filters; Noise; State estimation; Symmetric matrices; Technological innovation;
fLanguage
English
Publisher
ieee
Conference_Titel
Signals, Systems and Computers, 2013 Asilomar Conference on
Conference_Location
Pacific Grove, CA
Print_ISBN
978-1-4799-2388-5
Type
conf
DOI
10.1109/ACSSC.2013.6810357
Filename
6810357
Link To Document