Identification of Pseudo-random Sequences in DS/SS Intercepts by Higher-order Statistics

Abstract

This report results from a contract tasking Cranfield University (RMCS) as follows: The contractor will investigate discriminant functions for known m-sequences and develop higher-order statistical methods to identify Gold codes in intercepts. The contractor will then assess the robustness of a detection to realistic channel effects that would occur for airborne RF signals.

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Document Details

Document Type
Technical Report
Publication Date
May 07, 2004
Accession Number
ADA426462

Entities

People

  • Ernest R. Adams

Organizations

  • Cranfield University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Contractors
  • Contracts
  • Cross Correlation
  • Data Science
  • Detection
  • Detectors
  • False Alarms
  • Gaussian Noise
  • Identification
  • Information Science
  • Order Statistics
  • Power Spectra
  • Pseudo Random Sequences
  • Sequences
  • Signal Processing
  • Statistics
  • Universities

Readers

  • Radio communications and signal processing.
  • Statistical inference.
  • Technical Research and Report Writing.