Radon transformation of time-frequency distributions for analysis of multicomponent signals

The Radon transform of a time-frequency distribution produces local areas of signal concentration that facilitate interpretation of multicomponent signals. The Radon transform can be efficiently implemented with dechirping in the time domains; however, only half of the possible projections through the time-frequency plane can be realized because of aliasing. It is shown that the frequency dual to dechirping exists, so that all of the time-frequency plane projections can be calculated efficiently. Some Radon transforms of Wigner distributions are demonstrated.<<ETX>>

[1]  Françoise Peyrin,et al.  A unified definition for the discrete-time, discrete-frequency, and discrete-time/Frequency Wigner distributions , 1986, IEEE Trans. Acoust. Speech Signal Process..

[2]  Boualem Boashash,et al.  Note on the use of the Wigner distribution for time-frequency signal analysis , 1988, IEEE Trans. Acoust. Speech Signal Process..

[3]  Douglas L. Jones,et al.  A radially-Gaussian, signal-dependent time-frequency representation , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.

[4]  Jechang Jeong,et al.  Alias-free generalized discrete-time time-frequency distributions , 1992, IEEE Trans. Signal Process..

[5]  Patrick Flandrin.  On detection-estimation procedures in the time-frequency plane , 1986, ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[6]  Grant T. Gullberg,et al.  Users Manual: Donner Algorithms for Reconstruction Tomography , 1977 .

[7]  Weiping Li,et al.  Wigner distribution method equivalent to dechirp method for detecting a chirp signal , 1987, IEEE Trans. Acoust. Speech Signal Process..

[8]  Boualem Boashash,et al.  Kernel design for time-frequency signal analysis using the Radon transform , 1993, IEEE Trans. Signal Process..

[9]  Gabor T. Herman,et al.  Image reconstruction from projections : the fundamentals of computerized tomography , 1980 .

[10]  David S. K. Chan,et al.  A non-aliased discrete-time Wigner distribution for time-frequency signal analysis , 1982, ICASSP.

[11]  John C. Wood,et al.  Radon transformation of the Wigner spectrum , 1992, Optics & Photonics.

[12]  T. Claasen,et al.  The aliasing problem in discrete-time Wigner distributions , 1983 .

[13]  S. Kay,et al.  On the optimality of the Wigner distribution for detection , 1985, ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing.