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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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationDetection and Sensing of Mines, Explosive Objects, and Obscured Targets XXI
EditorsJason C. Isaacs, Steven S. Bishop
PublisherSPIE
ISBN (Electronic)9781510600645
DOIs
Publication statusPublished - 2016
EventDetection and Sensing of Mines, Explosive Objects, and Obscured Targets XXI - Baltimore, United States
Duration: 18 Apr 201621 Apr 2016

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume9823
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceDetection and Sensing of Mines, Explosive Objects, and Obscured Targets XXI
Country/TerritoryUnited States
CityBaltimore
Period18/04/1621/04/16

Keywords

  • Adaptive signal processing
  • GPR
  • IED
  • Landmine
  • Signal processing

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