Analysis of Multicomponent Polynomial Phase Signals

Author

Pham, Duc Son ; Zoubir, Abdelhak M.

Author_Institution

Dept. of Comput., Curtin Univ. of Technol., Perth, WA

Volume

55

Issue

1

fYear

2007

Firstpage

56

Lastpage

65

Abstract

While the theory of estimation of monocomponent polynomial phase signals is well established, the theoretical and methodical treatment of multicomponent polynomial phase signals (mc-PPSs) is limited. In this paper, we investigate several aspects of parameter estimation for mc-PPSs and derive the Crameacuter-Rao bound. We show the limits of existing techniques and then propose a nonlinear least squares (NLS) approach. We also motivate the use the Nelder-Mead simplex algorithm for minimizing the nonlinear cost function. The slight increase in computational complexity is a tradeoff for improved mean square error performance, which is evidenced by simulation results

Keywords

computational complexity; least squares approximations; polynomials; signal processing; Cramer-Rao bound; Nelder-Mead simplex algorithm; computational complexity; mean square error; multicomponent polynomial phase signal; nonlinear cost function minimization; nonlinear least squares approach; parameter estimation; Computational complexity; Computational modeling; Cost function; Estimation theory; Least squares methods; Mean square error methods; Parameter estimation; Phase estimation; Polynomials; Signal analysis; High ambiguity function (HAF); Nelder–Mead algorithm; nonlinear least squares; nonstationary; polynomial phase signals;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/TSP.2006.882085

Filename

4034235