Abstract
Distributed Kalman filtering aims at optimizing an estimate at a fusion center based on information that is gathered in a sensor network. Recently, an exact solution based on local estimation tracks has been proposed and an extension to cope with packet losses has been derived. In this contribution, we generalize both algorithms to packet delays. The key idea is to introduce augmented measurement vectors in the sensors that permit the optimization of local filter gains according to time-dependent measurement capabilities at the fusion center. In the most general form, the algorithm provides optimized estimates in sensor networks with packets delays and losses. The precision depends on the actual arrival patterns, and the results correspond to those of the centralized Kalman filter when specific assumptions about the measurement capability are satisfied.
Original language | English (US) |
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Title of host publication | FUSION 2014 - 17th International Conference on Information Fusion |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9788490123553 |
State | Published - Jan 1 2014 |
Event | 17th International Conference on Information Fusion, FUSION 2014 - Salamanca, Spain Duration: Jul 7 2014 → Jul 10 2014 |
Other
Other | 17th International Conference on Information Fusion, FUSION 2014 |
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Country | Spain |
City | Salamanca |
Period | 7/7/14 → 7/10/14 |
All Science Journal Classification (ASJC) codes
- Information Systems