A wavelet-based multi-sensor data fusion algorithm

被引：0

作者：

Xu, LJ ^{[1
]}

Zhang, JQ ^{[1
]}

Yan, Y ^{[1
]}

机构：

[1] Univ Greenwich, Ctr Adv Instrumentat & Control, Sch Engn, Chatham ME4 4TB, Kent, England

来源：

IMTC/O3: PROCEEDINGS OF THE 20TH IEEE INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE, VOLS 1 AND 2 | 2003年

关键词：

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 presents a wavelet transform-based data fusion algorithm for multi-sensor systems. With this algorithm the optimum estimate of a measurand can be obtained in terms of Minimum Mean Square Error. The variance of the optimum estimate is not only smaller than that of each observation sequence but also smaller than the arithmetic average estimate. To implement this algorithm, the variance of each observation sequence is estimated using wavelet transform and the optimum weighting factor to each observation is obtained accordingly. Since the variance of each observation sequence is estimated only from its most recent data of a predetermined length, the algorithm is self-adaptive. This algorithm is applicable to both static and dynamic systems including time-invariant and time-variant processes. The effectiveness of the algorithm is demonstrated using a piecewise-smooth signal and a time-varying flow signal.

引用

页码：452 / 457

页数：6

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