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Analysis of Multicomponent Polynomial Phase Signals

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2 Author(s)
Duc Son Pham ; Dept. of Comput., Curtin Univ. of Technol., Perth, WA ; Zoubir, A.M.

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

Published in:

Signal Processing, IEEE Transactions on  (Volume:55 ,  Issue: 1 )

Date of Publication:

Jan. 2007

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