Energy-Efficient Weighted Observation Fusion Kalman Filtering with Randomly Delayed Measurements

被引：4

作者：

Chen, Jian ^{[1
]}

Chen, Bo ^{[2
]}

Hong, Zhen ^{[3
]}

机构：

[1] Zhejiang Tech Inst Econ, Digital Informat Technol Dept, Hangzhou 310018, Zhejiang, Peoples R China

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

[3] Zhejiang Sci Tech Univ, Fac Mech Engn & Automat, Hangzhou 310018, Zhejiang, Peoples R China

来源：

CIRCUITS SYSTEMS AND SIGNAL PROCESSING | 2014年 / 33卷 / 10期

基金：

中国国家自然科学基金;

关键词：

Weighted observation fusion Kalman filter (WOFKF); Random measurement delays; Energy constraints; DECENTRALIZED ESTIMATION; DISTRIBUTED ESTIMATION; SYSTEMS; BANDWIDTH;

D O I：

10.1007/s00034-014-9790-9

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 is concerned with the weighted observation fusion Kalman filtering problem for a class of multi-sensor fusion systems with random measurement delays and energy constraints. To reduce the energy consumptions, each sensor intermittently sends information to the fusion center in a random way. By using the full rank decomposition approach, the observation fusion equation is derived. Without resorting to the augmentation technique, optimal weighted observation fusion Kalman filter (WOFKF) is given, and it is proved that the performance of the WOFKF is equivalent to that of the centralized fusion Kalman filter. Simulations show the effectiveness of the proposed fusion methods.

引用

页码：3299 / 3316

页数：18

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