A Multi-Sensor Data Fusion Method by Combining Near-neighbor Method and Fuzzy Inference

DOI

10.2991/ammee-17.2017.159How to use a DOI?

Keywords

target tracking, accuracy, fuzzy inference, near-neighbor method.

Abstract

Aiming at the practical issue of multi-sensor data fusion in target tracking, this paper proved that the accuracy of multi-sensor data fusion is better than that of any one sensor in terms of accuracy definition. According to the proof method, we proposed a multi-sensor data fusion method by combinating the near-neighbor method and fuzzy inference. The method combines the near-neighbor method and weighted average of fusion inference method in engineering practice. This paper theoretically proved that, as the number of sensors increases, the accuracy of data fusion is higher rather than worse. Numerical examples show that, our method in this paper has better results than the only weighted average fusion method of fuzzy inference.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jianxing Liang
AU  - Yanting Wang
AU  - Hong Yin
AU  - Guolin Liu
PY  - 2017/06
DA  - 2017/06
TI  - A Multi-Sensor Data Fusion Method by Combining Near-neighbor Method and Fuzzy Inference
BT  - Proceedings of the Advances in Materials, Machinery, Electrical Engineering (AMMEE 2017)
PB  - Atlantis Press
SP  - 828
EP  - 833
SN  - 2352-5401
UR  - https://doi.org/10.2991/ammee-17.2017.159
DO  - 10.2991/ammee-17.2017.159
ID  - Liang2017/06
ER  -