Share Email Print
cover

Proceedings Paper

Radon transformation of the Wigner spectrum
Author(s): John C. Wood; Daniel T. Barry
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

The radon transform of the Wigner spectrum has been shown to be the optimal detection scheme for linear FM signals, but the properties of this representation have not been well characterized. By the projection slice theorem, each line integral through the Wigner spectrum corresponds to the inverse Fourier transform of a radial slice through the ambiguity plane. Since line integrals through the Wigner spectrum can be calculated by dechirping, calculation of the Wigner spectrum may be viewed as a tomographic reconstruction problem. In this paper we show that all time-frequency transforms of Cohen's class may be achieved by simple changes in backprojection reconstruction filtering. The resolution-ringing trade-off that occurs in computed tomography is shown to be analogous to the resolution-cross-term trade-off that occurs in time-frequency kernel selection. `Ideal' reconstruction using a purely differentiating backprojection filter yields the Wigner distribution while low-pass differentiating filters produce cross-term suppressing distributions such as the spectrogram or the Born-Jordan distribution. The one-to-one identities between the Wigner, Radon-Wigner, and ambiguity planes suggest that the Radon-Wigner domain may be a new design space for time-frequency filtering and kernel design. The distribution of white noise in this space is presented as well as some simple examples of time-varying filtering.

Paper Details

Date Published: 30 November 1992
PDF: 18 pages
Proc. SPIE 1770, Advanced Signal Processing Algorithms, Architectures, and Implementations III, (30 November 1992); doi: 10.1117/12.130943
Show Author Affiliations
John C. Wood, Univ. of Michigan Hospital (United States)
Daniel T. Barry, Univ. of Michigan Hospital (United States)


Published in SPIE Proceedings Vol. 1770:
Advanced Signal Processing Algorithms, Architectures, and Implementations III
Franklin T. Luk, Editor(s)

© SPIE. Terms of Use
Back to Top