Distributed Kalman filtering in the presence of packet delays and losses

Marc Reinhardt, Benjamin Noack, Sanjeev Kulkarni, Uwe D. Hanebeck

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


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 languageEnglish (US)
Title of host publicationFUSION 2014 - 17th International Conference on Information Fusion
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9788490123553
StatePublished - Jan 1 2014
Event17th International Conference on Information Fusion, FUSION 2014 - Salamanca, Spain
Duration: Jul 7 2014Jul 10 2014


Other17th International Conference on Information Fusion, FUSION 2014

All Science Journal Classification (ASJC) codes

  • Information Systems


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