Higher-order tensor-based method for delayed exponential fitting

Remy Boyer (1) , Lieven Delathauwer (2) , Karim Abed-Meraim (3)

1 L2S - Laboratoire des signaux et systèmes
2 KU Leuven - Catholic University of Leuven = Katholieke Universiteit Leuven
3 TSI - Département Traitement du Signal et des Images

We present subspace-based schemes for the estimation of the poles (angular frequencies and damping factors) of a sum of damped and delayed sinusoids. In our model, each component is supported over a different time frame, depending on the delay parameter. Classical subspace-based methods are not suited to handle signals with varying time supports. In this contribution, we propose solutions based on the approximation of a partially structured Hankel-type tensor on which the data are mapped. We show, by means of several examples, that the approach based on the best rank-( 1 2 3) approximation of the data tensor outperforms the current tensor and matrix-based techniques in terms of the accuracy of the angular frequency and damping factor parameter estimates, especially in the context of difficult scenarios as in the low signal-to-noise ratio regime and for closely spaced sinusoids.

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

Remy Boyer, Lieven Delathauwer, Karim Abed-Meraim. Higher-order tensor-based method for delayed exponential fitting. IEEE Transactions on Signal Processing, 2007, 55 (6). ⟨hal-00575669⟩