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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