Wigner-Ville Distribution: A MATLAB-Based Time-Frequency Analysis Method

One of the time-frequency analysis methods implemented in MATLAB is the Wigner-Ville Distribution (WVD). This method enables comprehensive analysis of signals in both time and frequency domains, providing deeper insights into signal characteristics and behaviors. Through MATLAB implementation, the WVD computes the instantaneous frequency and amplitude information, allowing visualization of signal features and variations. The algorithm involves calculating the Fourier transform of the instantaneous autocorrelation function, typically implemented using MATLAB's signal processing functions like wvd() or through custom implementations with fft() and conj() operations. This method is particularly effective for detecting instantaneous frequency variations and phase jumps in signals, making it valuable for solving synchronization and communication-related problems. The MATLAB implementation typically involves parameters such as window length and overlap percentage to optimize time-frequency resolution. Key considerations include handling cross-term interference through advanced variations like Pseudo WVD or smoothed versions. In summary, the Wigner-Ville Distribution serves as a powerful time-frequency analysis tool that enhances our ability to understand and process signal data through MATLAB's computational capabilities. The implementation requires careful consideration of sampling frequency and signal length to maintain analytical accuracy while providing meaningful visual representations through spectrogram-like outputs.