Sensor fusion based fuzzy rules learning for humanitarian mine detection

Zakarya Zyada, Yasuhiro Kawai, Takayuki Matsuno, Toshio Fukuda

研究成果

3 被引用数 (Scopus)

抄録

In this paper, a sensor fusion based fuzzy rules for humanitarian demining are presented. A fuzzy learning algorithm for extracting fuzzy fusion rules from experimental data of robot-manipulated ground penetrating radar (GPR) and metal detector (MD) is presented. The inputs to the fuzzy learning algorithm are features extracted from both a GPR and an MD while its output is a set of fuzzy rules. Applying the learnt fuzzy fusion rules and knowing GPR and the MD features of a given scan, it is possible to decide if there is a land mine and its approximate depth underground. The features chosen for this fusion algorithm are the peak amplitude of a processed GPR output signal and the peak value of the cumulative sum of amplitudes of MD output signal for the same scanned area. Experimental test results are presented for verifying the validity of the proposed learnt fuzzy fusion rule base.

本文言語English
ホスト出版物のタイトル2006 SICE-ICASE International Joint Conference
ページ1860-1865
ページ数6
DOI
出版ステータスPublished - 12月 1 2006
外部発表はい
イベント2006 SICE-ICASE International Joint Conference - Busan
継続期間: 10月 18 200610月 21 2006

出版物シリーズ

名前2006 SICE-ICASE International Joint Conference

Other

Other2006 SICE-ICASE International Joint Conference
国/地域Korea, Republic of
CityBusan
Period10/18/0610/21/06

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • 制御およびシステム工学
  • 電子工学および電気工学

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