Parameter estimation of short-time multi-component signals using damped-amplitude & polynomial-frequency model

Zhong-Yang Li (1) , Nadine Martin (1) , Michelle Vieira (1) , Philippe Guéguen (2)

1 GIPSA-SAIGA - GIPSA - Signal et Automatique pour la surveillance, le diagnostic et la biomécanique
2 ISTerre - Institut des Sciences de la Terre

This paper concerns the parameter estimation of multicomponent damped oscillations having non-linear frequency. In this paper, the instantaneous frequency is approximated by polynomials while the amplitude is characterized by damped exponentials to connect directly to its physical interpretations. A maximum likelihood procedure is developed via an adaptive simulated annealing technique which helps to speed up the convergence. Results on simulated signals show that the proposed algorithm is more efficient than the algorithm based on polynomial amplitude models, and allows the estimation of damping coefficients over a very short time duration. Finally, the proposed algorithm is applied for characterizing the ambient vibrations of a building.

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Zhong-Yang Li, Nadine Martin, Michelle Vieira, Philippe Guéguen. Parameter estimation of short-time multi-component signals using damped-amplitude & polynomial-frequency model. SSP 2011 - 2011 IEEE Workshop on Statistical Signal Processing, Jun 2011, Nice, France. pp.s/n. ⟨hal-00609194⟩