Quantifying the Benefit of Airborne and Ground Sensor Fusion for Target Detection

Abstract

In this paper, a study involving the detection of buried objects by fusing airborne Multi-Spectral Imagery (MSI) and ground-based Ground Penetrating Radar (GPR) data is investigated. The benefit of using the airborne sensor to cue the GPR, which will then search the area indicated by the MSI, is investigated and compared to results obtained via a purely ground-based system. State-of-the-art existing algorithms, such as hidden Markov models will be applied to the GPR data both in queued and non-queued modes. In addition, the ability to measure disturbed earth with the GPR sensor will be investigated. Furthermore, state-of-the-art algorithms for the MSI system will be described. These algorithms require very high detection rates with acceptable false alarm rates in order to serve as an acceptable system. Results will be presented on data collected at outdoor testing and evaluation sites.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2010
Accession Number
ADA633587

Entities

People

  • Alina Zare
  • Miranda Silvious
  • Paul Gader
  • Ryan Close

Organizations

  • University of Florida

Tags

DTIC Thesaurus Topics

  • Airborne
  • Algorithms
  • Anomaly Detection
  • Change Detection
  • Detection
  • False Alarms
  • Ground Based
  • Ground Penetrating Radar
  • Hidden Markov Models
  • Images
  • Land Mines
  • Markov Models
  • Mathematics
  • Probability
  • Vehicle Tracks
  • Warning Systems

Readers

  • Computer Vision.
  • Radar Systems Engineering.
  • Sensor Fusion and Tracking Systems.