TY - GEN
T1 - Stochastic sensor scheduling for centralized state estimation
AU - Yang, Chao
AU - Yang, Wen
AU - Zheng, Jiangying
AU - Shi, Hongbo
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2018/1/18
Y1 - 2018/1/18
N2 - A stochastic sensor scheduling problem is studied 1 in this paper. A group of sensors take measurements of the states of a process and send the data to a remote estimator. Each sensor communicates with the estimator randomly and the communication is determined by a Bernoulli random variable. Meanwhile, the sensors have limited power resources for communication. The design of the communication rates which optimizes the estimation performance under the limited communication resources is studied in this paper. This optimization problem is relaxed and solved by tractable numerical algorithms. Examples show that satisfactory performance is obtained.
AB - A stochastic sensor scheduling problem is studied 1 in this paper. A group of sensors take measurements of the states of a process and send the data to a remote estimator. Each sensor communicates with the estimator randomly and the communication is determined by a Bernoulli random variable. Meanwhile, the sensors have limited power resources for communication. The design of the communication rates which optimizes the estimation performance under the limited communication resources is studied in this paper. This optimization problem is relaxed and solved by tractable numerical algorithms. Examples show that satisfactory performance is obtained.
UR - https://www.scopus.com/pages/publications/85046292340
U2 - 10.1109/CDC.2017.8264066
DO - 10.1109/CDC.2017.8264066
M3 - 会议稿件
AN - SCOPUS:85046292340
T3 - 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
SP - 2801
EP - 2806
BT - 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 56th IEEE Annual Conference on Decision and Control, CDC 2017
Y2 - 12 December 2017 through 15 December 2017
ER -