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<p>Frequency-hopped spread spectrum signals are widely used in military  communications to help combat or suppress interference due to jamming, other users of  the channel, and multipath propagation. Frequency-hopped signals may be difficult to  detect when embedded in background noise. Previous research has demonstrated  techniques for interference reduction and filtering frequency-hopped spread spectrum  waveforms with minimum distortion when the frequency-hop rate is on the order of 1,000  hops per second and the waveform is embedded in stationary interference waveforms.  The objective of this thesis was to apply previously developed interference reduction  techniques to frequency-hopped signals that hop at a much lower rate in order to  determine the efficacy and practicality of these techniques for hop rates as low as five  frequency-hops per second when the signal-of-interest is embedded in non-stationary  interference.  The technique used in this thesis to detect the frequency-hopped signals of interest  is based on exponential averaging in the frequency domain. This method averages a  weighted datastream in realtime. Specific fast Fourier transform block sizes and  exponential average weights produce good results if the signal-to-interference and the  signal-to-noise ratios are not too small.
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<br>Subjects: Fourier transform spectroscopy.; Noise-normalization; Detection; Estimation; Spread Spectrum; Frequency-Hopped; interference estimate; exponential average</div>
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Layfield, Steven C.</div>
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