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
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;
Conference_Titel :
Signals, Systems and Computers, 2013 Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
978-1-4799-2388-5
DOI :
10.1109/ACSSC.2013.6810357
