Fusion of KLMS and Blob Based Pre-Screener for Buried Landmine Detection Using Ground Penetrating Radar

Baydar B., AKAR G., YÜKSEL ERDEM S. E., Ozturk S.

Conference on Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXI, Maryland, United States Of America, 18 - 21 April 2016, vol.9823 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 9823
  • Doi Number: 10.1117/12.2223743
  • City: Maryland
  • Country: United States Of America
  • Hacettepe University Affiliated: Yes

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.