| Summary: | Frequency hopped signals are widely used in various communication applications for their inherent security features. The demand, by civilian and governmental agencies, to intercept communication signals is increasing. The interception task can be summarized by detecting the signal's presence in additive noise, classifying the modulation type, estimating the control parameters, decoding the data, and decrypting the information content. This work addresses the merging of wavelet and correlation concepts to detect, classify and estimate the parameters of frequency hopped signals. We address the interception problem in two ways. The first approach is based on a visual inspection of the wavelet surfaces generated from the instantaneous correlation function of the communication signal and leads to hop start/stop times estimates. In the second approach, we apply an energy-based processing scheme to estimate the hop start and stop times, the hop scale pattern, and the hop frequency. Results show that frequency hopped signals can be identified at an SNR of 3 dB or 6 dB using visual inspection or an automated scheme, respectively
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