Blind Parameters Estimation for FHSS Signals under Partial-band Observation

Frequency hopping spread spectrum (FHSS) signals span a widely varying frequency band, making it challenging to capture the entire spectrum in a non-cooperative context. Consequently, developing methods to blindly estimate FHSS parameters from only a partial observation becomes essential. This paper presents a robust algorithm for blind parameters estimation for FHSS signals under partial-band observation. The proposed algorithm first obtains a time-frequency image (TFI) of the partially observed FHSS signal and extracts its time-domain energy profile by marginalizing the TFI. By computing the derivative of this profile, the observed hop transitions are highlighted as positive and negative peaks, and correlation is used to reveal the repeating hop cycle. Subsequent peak detection isolates the hop duration, enabling the estimation of hop sequence length. Simulation results demonstrate that the proposed method achieves high estimation accuracy under partial-band observations, providing a valuable tool for spectrum monitoring and security applications in diverse non-cooperative contexts.