Multi-Source Fusion for Explosive Hazard Detection in Forward Looking Sensors

Abstract

This proposal is in response to sections 5.2 and 4.3 in the U.S. Army BAA W911NF-12-R-0012. The aim of this research is to improve the U.S. Army's ability to detect landmines and explosive hazards in different scenarios using multiple forward looking (FL) sensors, namely infrared (IR), forward looking ground penetrating radar (FLGPR) and visual spectrum (aka color). This is a real problem that has direct impact on the mobility of the U.S. Army and on the safety of our troops. Scientific advancements will come in the form of novel signal and image processing, data fusion and discrimination (pattern recognition) algorithms for multi-CPU and graphics processor unit (GPU) hardware to autonomously process data from different sensors on various platforms. This research is supported by the U.S. Army Night Vision and Electronic Sensors Directorate (NVESD) countermine division interms of sensors, platforms, data collection and discussions regarding project findings if/when appropriate.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2016
Accession Number
AD1051300

Entities

People

  • Derek T. Anderson

Organizations

  • Mississippi State University

Tags

Communities of Interest

  • Autonomy
  • Counter IED
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Computer Vision
  • Deep Learning
  • Detection
  • Detectors
  • Dimensionality Reduction
  • Feature Extraction
  • Frequency Domain
  • Image Processing
  • Information Science
  • Machine Learning
  • Pattern Recognition
  • Signal Processing
  • Supervised Machine Learning
  • United States

Readers

  • Parallel and Distributed Computing.
  • Sensor Fusion and Tracking Systems.
  • Technical Research and Report Writing.

Technology Areas

  • AI & ML
  • Microelectronics
  • Microelectronics - Microelectromechanical Systems