A Linear Subspace Approach to Burst Communication Signal Processing

Abstract

This dissertation focuses on the topic of burst signal communications in a high interference environment. It derives new signal processing algorithms from a mathematical linear subspace approach instead of the common stationary or cyclostationary approach. The research developed new algorithms that have well-known optimality criteria associated with them. The investigation demonstrated a unique class of multisensor filters having a lower mean square error than all other known filters, a maximum likelihood time difference of arrival estimator that outperformed previously optimal estimators, and a signal presence detector having a selectivity unparalleled in burst interference environments. It was further shown that these improvements resulted in a greater ability to communicate, to locate electronic transmitters, and to mitigate the effects of a growing interference environment.

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Document Details

Document Type
Technical Report
Publication Date
Mar 12, 2004
Accession Number
ADA423141

Entities

People

  • Daniel E. Gisselquist

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Angle Of Arrival
  • Data Science
  • Detectors
  • Digital Communications
  • Estimators
  • Frequency Bands
  • Frequency Shift
  • Information Science
  • Modulation
  • Optimal Estimators
  • Orthogonal Frequency Division Multiplexing
  • Random Variables
  • Signal Processing
  • Statistical Algorithms
  • Statistical Analysis
  • Warning Systems

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Radio communications and signal processing.

Technology Areas

  • Microelectronics
  • Microelectronics - Microelectromechanical Systems