Three-Dimensional Surface Plot using Wigner-Ville Distribution

This analysis employs the Wigner-Ville Distribution (WVD) to create three-dimensional surface plots for frequency-hopping signal characterization. The implementation typically involves computing the WVD using quadratic time-frequency distributions, which provides superior time-frequency resolution compared to linear methods. Concurrently, Short-Time Fourier Transform (STFT) is applied to the frequency-hopping signals for spectral analysis, where the signal is divided into overlapping segments using a windowing function (e.g., Hamming or Hanning window) before Fourier transformation. The WVD spectrogram for frequency-hopping signals is generated by calculating the auto-term components while suppressing cross-terms through appropriate filtering techniques. This comprehensive approach enables detailed examination of both spectral characteristics and time-domain features of frequency-hopping signals, with the WVD offering particular advantages in analyzing rapidly changing frequency components typical of hopping patterns. The MATLAB implementation would typically utilize signal processing toolbox functions for WVD calculation and spectrogram visualization.