Time-Varying Filtering and Signal Estimation Using Wigner Distribution Synthesis Techniques
Date of Original Version
The short-time Fourier transform (STFT), the ambiguity function (AF), and the Wigner distribution (WD) are mixed time-frequency signal representations that use Fourier transform techniques to map a one-dimensional function of time into a two-dimensional function of time and frequency. These mixed time-frequency mappings have been used to analyze the local frequency characteristics of a variety of signals and systems. Although much work has also been done to develop STFT and AF synthesis algorithms that can be used to implement a variety of time-varying signal processing operations, no such synthesis techniques have thus far been developed for the WD. In this paper, a signal synthesis algorithm that works directly with the real-valued high-resolution WD will be derived. Examples of how this WD synthesis procedure can be used to perform time-varying filtering operations or signal separation will be given. © 1986 IEEE
Publication Title, e.g., Journal
IEEE Transactions on Acoustics, Speech, and Signal Processing
Boudreaux-Bartels, Gloria F., and Thomas W. Parks. "Time-Varying Filtering and Signal Estimation Using Wigner Distribution Synthesis Techniques." IEEE Transactions on Acoustics, Speech, and Signal Processing 34, 3 (1986): 442-451. doi: 10.1109/TASSP.1986.1164833.