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Communication dans un congrès

Polynomial Phase Signal Modeling Using Warping-Based Order Reduction

André Quinquis 1 Cornel Ioana 2 Emanuel Radoi 3
3 Lab-STICC_UBO_CACS_COM
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance, UBO - Université de Brest
Abstract : The high-order ambiguity function (HAF) was introduced for the estimation of polynomial-phase signals (PPS). Currently the HAF suffers from noise-masking effects and from the appearance of undesired cross terms in the presence of multi-components PPS. The multi-lag product HAF concept was then proposed as a way to improve the performances of the HAF. Nevertheless, performances of the new methods are affected by the error propagation. This effect is due to the technique used for polynomial order reduction, common for current approaches : signal multiplication with the complex exponentials formed with the estimated coefficients. In this paper, we introduce an alternative method to reduce the polynomial order, based on the successive unitary signal transformation, according to each polynomial order. We will prove that this method considerably reduces the effect of error propagation.
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Soumis le : mercredi 3 septembre 2008 - 17:18:00
Dernière modification le : vendredi 6 novembre 2020 - 04:12:30
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André Quinquis, Cornel Ioana, Emanuel Radoi. Polynomial Phase Signal Modeling Using Warping-Based Order Reduction. International Conference on Acoustic, Speech and Signal Processing ICASSP 2004, May 2004, Montreal, Canada. pp.741-744, ⟨10.1109/ICASSP.2004.1326364⟩. ⟨hal-00317938⟩

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