Abstract
Modeling of a class of nonstationary signals with randomly time-varying amplitude and parametric polynomial phase is addressed. A novel approach is proposed for the estimation of the time-varying phase by exploiting the higher order cyclostationarity of these signals. The method does not require nonlinear search, is easy to implement, and yields consistent estimates for the parameters. The resulting algorithms are theoretically tolerant to a large class of noises including additive stationary non-Gaussian noise and any Gaussian noise. Simulation examples supporting the theory are provided.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 492-505 |
| Number of pages | 14 |
| Journal | IEEE Transactions on Signal Processing |
| Volume | 43 |
| Issue number | 2 |
| DOIs | |
| State | Published - Feb 1995 |
Bibliographical note
Funding Information:Manuscript received August 29, 1993; revised July 13, 1994. This work was supported by ONR "14-93-1-0485, NSFMIP-9210230, ONR N00014-91-5-1602, and NSF/MIP-90-17221. Part of results of this paper were presented at the Conf. on Information Sciences and Sysrems (The Johns Hopkins University, Baltimore, MD), March 1993. The associate editor coordinating the review of this paper and approving it for publication was Prof. Jose A. R. Fonollosa. S. Shamsunder is with the Department of Electrical Engineering, Colorado State University, Fort Collins, CO 80523 USA. G. B. Giannakis is with the Department of Electrical Engineering, University of Virginia, Charlottesville. VA 22903-2442 USA. B. Friedlander is with the Department of Electrical Engineering, University of Califomia, Davis, CA 9561 6 USA. IEEE Log Number 9407619.