Distributed Covariance Intersection Fusion in Clustered Sensor Networks with Different Sampling Rates

被引：0

作者：

Song Haiyu ^{[1
,2
]}

Yu Li ^{[1
,2
]}

Zhang Wen-An ^{[1
,2
]}

机构：

[1] Zhejiang Univ Technol, Coll Informat Engn, Hangzhou 310023, Zhejiang, Peoples R China

[2] Zhejiang Prov United Key Lab Embedded Syst, Hangzhou 310023, Zhejiang, Peoples R China

来源：

2014 33RD CHINESE CONTROL CONFERENCE (CCC) | 2014年

关键词：

covariance intersection fusion; distributed fusion; clustered sensor networks; STATE-SPACE MODELS; FILTER;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper is concerned with the fusion estimation problem in clustered sensor networks (CSN). A set of sensors are divided into several clusters and independently observe outputs of a plant with different sampling rates. During each estimating interval, each local estimator collects sampled information from sensors in its area and generates a local estimate at the estimating instant. A fusion center (FC) is connected with all the estimators to fuse the local estimates by using the covariance intersection (CI) method. An illustrative example is provided to demonstrate the effectiveness of the proposed results.

引用

页码：7253 / 7257

页数：5

共 7 条

[1] Sequential covariance intersection fusion Kalman filter [J].