Time–frequency analysis method based on affine Fourier transform and Gabor transform

• Published in: IET signal processing 2017-04, Vol.11 (2), p.213-220
• Main Authors: Wei, Deyun, Li, Yuan-Min, Wang, Ruikui
• Format: Article
• Language: English
• Subjects: affine Fourier transform; affine relation; affine transforms; AFT; Chirp signals; filter design; filtering theory; Fourier transforms; Gabor‐Wigner transform; linear time‐frequency representation; modified GT; multiple component chirp signal separation; optics; power integration relation; Projection; projection relation; quadratic distribution; recovery relation; Representations; Research Article; Signal processing; Simulation; TFR; Time-frequency analysis; time‐frequency analysis method; Transforms
• ISSN: 1751-9675; 1751-9683; 1751-9683
• DOI: 10.1049/iet-spr.2016.0231

The affine Fourier transform (AFT) plays an important role in many fields of optics and signal processing. The Gabor transform (GT) is a kind of linear time–frequency representation (TFR). Compared with many bilinear TFRs, the GT does not have the cross-term problem. In this study, the authors propose a time–frequency analysis method based on the AFT and GT. First, they obtain an affine relation between the AFT and the modified GT (MGT). Since the MGT is closely related to the AFT, they can use it as an assistant tool for signal processing in the AFT domain. Moreover, many useful relations between the AFT and the MGT are derived, such as recovery relation, projection relation and power integration relation. Then, they demonstrate that the AFT also has the affine relation with other TFRs, such as the Gabor–Wigner transform and the general class of quadratic distribution. Last, using the new time–frequency analysis method associated with the AFT and MGT, they present the filter design for multiple component chirp signal separation. Moreover, the simulation results illustrate the effectiveness of the proposed method.