Blind Estimation for the Generation Polynomial of FHSS Signals using Time Frequency Analysis

The escalation of worldwide conflicts and accessibility of unmanned aerial vehicles (UAVs) have led to the increase of various security concerns. To implement effective protective measures against unauthorized drones, it is crucial to blindly estimate the generation polynomial of the frequency hopping spread spectrum (FHSS) signals, which are commonly used in UAVs. This paper presents a robust algorithm for the blind estimation of generation polynomials with partial observation of the signal hopping period, utilizing time frequency images (TFI) and unique preprocessing methods to accurately and efficiently extract the hopping pattern. The TFI is segmented into each hopping region, which undertakes noise reduction via temporal marginalization independently. Subsequently, the noise-reduced image is standardized, clipped along the frequency axis for pattern enhancement. Then, the analysis of the preprocessed image allows for the identification of the hopping pattern, which can be used to reconstruct the generation polynomial by simple linear operations. Simulation results show that the proposed algorithm reduces the required signal duration for identifying the generation polynomial and enhances estimation accuracy.