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Fusion of KLMS and blob based pre-screener for buried landmine detection using ground penetrating radar

  • Middle East Technical University
  • TFO, LLC

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

2 Alıntılar (Scopus)

Özet

In this paper, a decision level fusion using multiple pre-screener algorithms is proposed for the detection of buried landmines from Ground Penetrating Radar (GPR) data. The Kernel Least Mean Square (KLMS) and the Blob Filter pre-screeners are fused together to work in real time with less false alarms and higher true detection rates. The effect of the kernel variance is investigated for the KLMS algorithm. Also, the results of the KLMS and KLMS+Blob filter algorithms are compared to the LMS method in terms of processing time and false alarm rates. Proposed algorithm is tested on both simulated data and real data collected at the field of IPA Defence at METU, Ankara, Turkey.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıDetection and Sensing of Mines, Explosive Objects, and Obscured Targets XXI
EditörlerJason C. Isaacs, Steven S. Bishop
YayınlayanSPIE
ISBN (Elektronik)9781510600645
DOI'lar
Yayın durumuYayınlandı - 2016
EtkinlikDetection and Sensing of Mines, Explosive Objects, and Obscured Targets XXI - Baltimore, !!United States
Süre: 18 Nis 201621 Nis 2016

Yayın serisi

AdıProceedings of SPIE - The International Society for Optical Engineering
Hacim9823
ISSN (Basılı)0277-786X
ISSN (Elektronik)1996-756X

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???event.eventtypes.event.conference???Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXI
Ülke/Bölge!!United States
ŞehirBaltimore
Periyot18/04/1621/04/16

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