Multi-Sensor Data Fusion between Radio Tomographic Imaging and Noise Radar

Abstract

Radio Tomographic Imaging (RTI) and noise radar are two proven surveillance technologies. The novelty of fusing data from RTI and noise radar is achieved with the derivation of a fusion technique utilizing Tikhonov regularization. Analyzing the results of the Tikhonov influenced techniques reveals up to a 100% error decrease in target pixel location, a 75% error decrease in target centroid location, a 28% size decrease in target pixel dispersion and a 72% improvement in an ideal solution comparison. Results provide the RTI and noise radar communities a proof of concept for the fusion of data from two disparate sensor technologies.

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Document Details

Document Type
Technical Report
Publication Date
Mar 21, 2019
Accession Number
AD1076589

Entities

People

  • Christopher Vergara

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Computer Programs
  • Computers
  • Electrical Engineering
  • Graphical User Interface
  • Inertial Navigation
  • Inertial Navigation Systems
  • Kalman Filtering
  • Kalman Filters
  • Operating Systems
  • Pattern Recognition
  • Radar Equipment
  • Three Dimensional
  • Two Dimensional
  • United States
  • United States Government
  • Wireless Sensor Networks

Readers

  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Radar Systems Engineering.
  • Sensor Fusion and Tracking Systems.