Fuzzy Sensor Fusion for Mine Detection

Zakarya Zyada; Yasuhiro Kawai; Takayuki Matsuno; Toshio Fukuda

doi:10.14864/softscis.2006.0.349.0

SCIS & ISIS 2006

Session ID : TH-E3-2

DOI https://doi.org/10.14864/softscis.2006.0.349.0

Conference information

Host: Japan SOciety for Fuzzy Theory and intelligent informatics

Co-host: The Korea Fuzzy Logic and Intelligent Systems Society, IEEE Computational Intelligence Society, The International Fuzzy Systems Association, 21th Century COE Program "Creation of Agent-Based Social Systems Sciences"

TH-E3 Machine Learning & Evolutionary Optimization (1)

Fuzzy Sensor Fusion for Mine Detection

*Zakarya Zyada, Yasuhiro Kawai, Takayuki Matsuno, Toshio Fukuda

Author information

Keywords: Sensor Fusion, Humanitarian Demining, Fuzzy Learning

CONFERENCE PROCEEDINGS FREE ACCESS

Details

Abstract

In this paper, one of soft computing techniques, fuzzy, is applied for automatic detection of a humanitarian land mind. A ""feature in-decision out"" fuzzy sensor fusion algorithm for a ground penetrating radar, (GPR), and a metal detector, (MD), for mine detection is introduced. The inputs to the fuzzy fusion system are features extracted from both GPR and MD measurements. The output from the fuzzy fusion system is a decision if there is a landmine and at what depth it would be. Fuzzy fusion rules are extracted from training data through a fuzzy learning algorithm. Experimetal test results are presented to demonstrate the validity of the proposed fuzzy fusion algorithm and hence its influence in minimizing the false alarm rate for mine detection.

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