SSP'05 -- Proceedings

	IEEE/SP 13th workshop on Statistical Signal Processing July, 17-20, 2005 - Bordeaux - France

Information regarding the paper

Title

Maximum likelihood parameter estimation of short time multicomponent signals with nonlinear AM/FM modulation

Author(s)

Meryem Jabloun	LIS: Laboratoire des Images et des Signaux
Nadine Martin	LIS: Laboratoire des Images et des Signaux
Michelle Vieira	LIS: Laboratoire des Images et des Signaux
Leonard Francois	Institut d'hydro Quebec

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Abstract

Parameter estimation for closely spaced or crossing frequency trajectories is a difficult signal processing problem, especially in the presence of both nonlinear amplitude and frequency modulation. In this paper, polynomial models are assumed for the instantaneous frequencies and amplitudes (IF/IA). We suggest two different strategies to process multicomponent signals. In the first one, which is optimal, all model parameters are simultaneously estimated using a maximum likelihood procedure (ML), maximized via a stochastic technique called Simulated Annealing (SA). In the second strategy, which is suboptimal, the signal is iteratively reconstructed component by component. At each iteration, the IF and IA of one component are estimated using the ML procedure and the SA technique. To evaluate the accuracy of the proposed strategies, Monte Carlo simulations are presented and compared to the derived Cramer-Rao Bounds for closely spaced and crossing frequency trajectories. The results show the proposed algorithms perform well compared to existing techniques.