Optimal Parameter Estimation Under Controlled Communication Over Sensor Networks

被引:28
|
作者
Han, Duo [1 ]
You, Keyou [2 ]
Xie, Lihua [3 ]
Wu, Junfeng [4 ]
Shi, Ling [1 ]
机构
[1] Hong Kong Univ Sci & Technol, Elect & Comp Engn, Kowloon, Hong Kong, Peoples R China
[2] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
[3] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore
[4] Royal Inst Technol KTH, Dept Automat Control, SE-10044 Stockholm, Sweden
基金
新加坡国家研究基金会; 瑞典研究理事会;
关键词
Wireless sensor networks; maximum likelihood estimation; Cramer-Rao bounds; event-based communication; CONSTRAINED DISTRIBUTED ESTIMATION; IDENTIFICATION; INTERMITTENT; STABILITY;
D O I
10.1109/TSP.2015.2469639
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper considers parameter estimation of linear systems under sensor-to-estimator communication constraint. Due to the limited battery power and the traffic congestion over a large sensor network, each sensor is required to reduce the rate of communication between the estimator and itself. We propose an observation-driven sensor scheduling policy such that the sensor transmits only the important measurements to the estimator. Unlike the existing deterministic scheduler, our stochastic scheduling is smartly designed to well compensate for the loss of the Gaussianity of the system. This results in a nice feature that the maximum-likelihood estimator (MLE) is still able to be recursively computed in a closed form, and the resulting estimation performance can be explicitly evaluated. Moreover, an optimization problem is formulated and solved to obtain the best parameters of the scheduling policy under which the estimation performance becomes comparable to the standard MLE with full measurements under a moderate transmission rate. Finally, simulations are included to validate the theoretical results.
引用
收藏
页码:6473 / 6485
页数:13
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