A New Flexible Approach to Estimate Highly Nonstationary Signals of Long Time DurationReport as inadecuate

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1 GIPSA-lab - Grenoble Images Parole Signal Automatique 2 IREQ - Institut de Recherche d-Hydro-Québec 3 GIPSA-SA-IGA - SA-IGA GIPSA-DA - Département Automatique, GIPSA-DIS - Département Images et Signal

Abstract : We propose an original strategy for estimating and reconstructing mono-component signals having a high nonstationarity and long time-duration. We locally apply to short duration intervals the strategy developed in our previous work about non-stationary short-time signals. This paper describes a non-sequential time segmentation that provides segments whose lengths are suitable for modeling both the instantaneous amplitude and frequency locally with low-order polynomials. Parameter estimation is done independently for each segment by maximizing the likelihood function by means of the simulated annealing technique. The signal is then reconstructed by merging the estimated segments. The strategy proposed is sufficiently flexible for estimating a large variety of non-stationarity and specifically applicable to high-order polynomial phase signals. The estimation of a high-order model is not necessary. The error propagation phenomenon occurring with the known approach, the Higher Ambiguity Function-based method, is avoided. The proposed strategy is evaluated using Monte-Carlo noise simulations and compared with the Cramer-Rao bounds. The signal of a songbird is used as a real example of its applicability.

Keywords : time-frequency Non-stationary signal nonlinear modulation polynomial phase signal maximum likelihood Cramer-Rao bounds simulated annealing time-frequency.

Author: Meryem Jabloun - François Léonard - Michelle Vieira - Nadine Martin -

Source: https://hal.archives-ouvertes.fr/


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