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Fast De-hopping and Frequency Hopping Pattern (FHP) Estimation for DS/FHSS Using Neural Networks

  • Tarek Elhabian
  • Bo Zhang
  • Dingrong Shao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3174)

Abstract

A Fast de-hopping and FHP estimation model for Direct Sequence/Frequency Hopping Spread Spectrum (DS/FHSS) system is proposed. The Neural Networks (NNs) were used to mimic the Parallel Matched Filtering (PMF). The signal samples and its Fast Fourier Transform (FFT) were used for Back propagation Neural Network (BNN) training. The FH patterns designated as concatenated prime codes [8] were used for the Radial Basis Function (RBF) training. Computer simulations show that the proposed method can effectively identify the frequency and estimate its pattern. Small hardware resources compared with PMF hardware.

Keywords

Acquisition Direct Sequence Frequency Hopping Pattern Neural Network Matched Filter Fourier transform 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Tarek Elhabian
    • 1
  • Bo Zhang
    • 1
  • Dingrong Shao
    • 1
  1. 1.School of Electronics & InformationBeijing University of Aeronautics & AstronauticsChina

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