Improved Detection and False Alarm Rejection Using FLGPR and Color Imagery in a Forward-Looking System

Abstract

Forward-looking ground-penetrating radar (FLGPR) has received a significant amount of attention for use in explosive-hazards detection. A drawback to FLGPR is that it results in an excessive number of false detections. This paper presents our analysis of the explosive-hazards detection system tested by the U.S. Army Night Vision and Electronic Sensors Directorate (NVESD). The NVESD system combines an FLGPR with a visible-spectrum color camera. We present a target detection algorithm that uses a locally-adaptive detection scheme with spectrum-based features. The remaining FLGPR detections are then projected into the camera imagery and image-based features are collected. A one-class classifier is then used to reduce the number of false detections. We show that our proposed FLGPR target detection algorithm, coupled with our camera-based false alarm (FA) reduction method, is effective at reducing the number of FAs in test data collected at a US Army test facility.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2010
Accession Number
ADA545172

Entities

People

  • Christopher J. Spain
  • David C. Wong
  • James M. Keller
  • K. C. Ho
  • Mehrdad Soumekh
  • Timothy C Havens
  • Tuan T. Ton

Tags

Communities of Interest

  • Counter IED
  • Human Systems
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Detection
  • Detectors
  • Electrical Engineering
  • Engineering
  • False Alarms
  • Feature Selection
  • Ground Penetrating Radar
  • Machine Learning
  • Radar
  • Sensor Fusion
  • Spectra
  • Standards
  • Synthetic Aperture Radar
  • Target Detection
  • Two Dimensional
  • Warning Systems

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • Microelectronics
  • Microelectronics - Microelectromechanical Systems