This thesis investigates the use of wavelet transforms in the detection and estimation of spread spectrum frequency hopping signals. The technique developed in this work makes only two basic assumptions of a minimum hopping time and a minimum frequency hopping differential. The approach is based on the phase information of the temporal correlation function and the resulting discrete wavelet transform is used to estimate the hopping time of frequency hopping signals. Results show the proposed scheme is robust to additive white noise for SNR levels of 3 dB and above.

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