Reflected Signal Analysis

Abstract

We present a framework for forensic identification of RF devices using specially designed probe signals. This framework applies to a broad range of devices and models. Probe signals, device models, feature selection, and classifier design are described. For the device model, we introduce a method for determining a nonlinearity based on a known diode model. Experimental results are given to verify our approach.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2010
Accession Number
ADA513228

Entities

People

  • Anthony F. Martone
  • Deen King-smith
  • Marc Ressler

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Aircrafts
  • Artificial Intelligence
  • Bandpass Filters
  • Dimensionality Reduction
  • Feature Selection
  • Filters
  • Frequency
  • Identification
  • Machine Learning
  • Measurement
  • Nonlinear Dynamics
  • Pattern Recognition
  • Power Spectra
  • Radio Frequency Devices
  • Supervised Machine Learning
  • Time Domain

Fields of Study

  • Computer science

Readers

  • Electrical Engineering
  • Neural Network Machine Learning.
  • Systems Analysis and Design