Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › Рецензирование
Optimal data encoding and fusion in sensor networks. / Zherlitsyn, Gleb; Matveev, Alexey.
2009 IEEE International Conference on Control Applications, CCA '09. 2009. стр. 666-670 5280723 (Proceedings of the IEEE International Conference on Control Applications).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › Рецензирование
}
TY - GEN
T1 - Optimal data encoding and fusion in sensor networks
AU - Zherlitsyn, Gleb
AU - Matveev, Alexey
PY - 2009/12/1
Y1 - 2009/12/1
N2 - The paper considers the sensor network whose sensors observe a common quantity and are affected by arbitrary additive bounded noises with a known upper bound. During the experiment, any sensor can communicate only a finite and given number of bits of information to the decision center. The contributions of the particular sensors, the rules of data encoding, decoding, and fusion, as well as the estimation scheme should be designed to achieve the best overall performance in estimation of the observed quantity by the decision center. The optimal algorithm is obtained that minimizes the maximal feasible error. It is shown that it considerably over-performs a 'natural' algorithm proposed in recent papers in the area and examined only in the idealized case of noiseless sensors. This analysis highlights the need for special decentralized data encoding rules that are robust against the sensor noises in the context of networked cooperative observation. Such a rule is the core of the proposed optimal algorithm.
AB - The paper considers the sensor network whose sensors observe a common quantity and are affected by arbitrary additive bounded noises with a known upper bound. During the experiment, any sensor can communicate only a finite and given number of bits of information to the decision center. The contributions of the particular sensors, the rules of data encoding, decoding, and fusion, as well as the estimation scheme should be designed to achieve the best overall performance in estimation of the observed quantity by the decision center. The optimal algorithm is obtained that minimizes the maximal feasible error. It is shown that it considerably over-performs a 'natural' algorithm proposed in recent papers in the area and examined only in the idealized case of noiseless sensors. This analysis highlights the need for special decentralized data encoding rules that are robust against the sensor noises in the context of networked cooperative observation. Such a rule is the core of the proposed optimal algorithm.
UR - http://www.scopus.com/inward/record.url?scp=74049094380&partnerID=8YFLogxK
U2 - 10.1109/CCA.2009.5280723
DO - 10.1109/CCA.2009.5280723
M3 - Conference contribution
AN - SCOPUS:74049094380
SN - 9781424446025
T3 - Proceedings of the IEEE International Conference on Control Applications
SP - 666
EP - 670
BT - 2009 IEEE International Conference on Control Applications, CCA '09
T2 - 2009 IEEE International Conference on Control Applications, CCA '09
Y2 - 8 July 2009 through 10 July 2009
ER -
ID: 50906731