Journal
INTERNATIONAL JOURNAL OF GENERAL SYSTEMS
Volume 46, Issue 7, Pages 752-771Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/03081079.2017.1341501
Keywords
Distributed and centralized fusion filters; covariance information; random measurement matrices; random delays and losses
Categories
Funding
- Ministerio de Economia y Competitividad
- Fondo Europeo de Desarrollo Regional FEDER [MTM2014-52291-P]
Ask authors/readers for more resources
The distributed and centralized fusion filtering problems for multisensor networked systems with transmission random one-step delays and non-consecutivepacket losses are addressed. The signal evolution model is not required, as only covariance information is used. The measurements of individual sensors, subject to uncertainties modeled by random matrices and correlated noises, are transmitted to local processors through different communication channels and, due to random transmission failures, some of the data packets may be delayed or even definitely lost. The random transmission delays and non-consecutive packet losses are modeled by sequences of Bernoulli variables with different probabilities. By an innovation approach, local least squares linear filtering estimators are obtained by recursive algorithms; the distributed fusion framework is then used to obtain the optimal matrix-weighted combination of the local filters, using the mean squared error as optimality criterion. Also, a recursive least squares linear estimation algorithm is designed within the centralized fusion framework.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available