2006Unpublished venueRequires access

Instantaneous Frequency Rate Estimation Based On the Robust Cubic Phase Function

Pu Wang, Igor Djurović, Jianyu Yang

Open publisher page 8 citations

Abstract

The cubic phase function (CPF) is recently proposed to estimate the instantaneous frequency rate (IFR) for the polynomial phase signals (PPS) in a Gaussian noise environment. However, for an impulse noise environment, the performance of the standard CPF degrades significantly. In addition, the resulting noise in the CPF is a mixture of the Gaussian and impulse noise even for a Gaussian input noise. Hence, a modified robust CPF algorithm based on the alpha-trimmed form of L-estimation is proposed in this paper. Extension to the robust higher-order phase function (HPF) is also derived. Simulation results demonstrate that the robust CPF outperforms the standard CPF in impulse noise and is also valid to estimate the IFR in Gaussian noise

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What this paper is about

The cubic phase function (CPF) is recently proposed to estimate the instantaneous frequency rate (IFR) for the polynomial phase signals (PPS) in a Gaussian noise environment. However, for an impulse noise environment, the performance of the standard CPF degrades significantly. In addition, the resulting noise in the CPF is a mixture of the Gaussian and impulse noise even for a Gaussian input noise. Hence, a modified robust CPF algorithm based on the alpha-trimmed form of L-estimation is proposed in this paper. Extension to the robust higher-order phase function (HPF) is also derived. Simulation results demonstrate that the robust CPF outperforms the standard CPF in impulse noise and is also valid to estimate the IFR in Gaussian noise

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Available abstract

The cubic phase function (CPF) is recently proposed to estimate the instantaneous frequency rate (IFR) for the polynomial phase signals (PPS) in a Gaussian noise environment. However, for an impulse noise environment, the performance of the standard CPF degrades significantly. In addition, the resulting noise in the CPF is a mixture of the Gaussian and impulse noise even for a Gaussian input noise. Hence, a modified robust CPF algorithm based on the alpha-trimmed form of L-estimation is proposed in this paper. Extension to the robust higher-order phase function (HPF) is also derived. Simulation results demonstrate that the robust CPF outperforms the standard CPF in impulse noise and is also valid to estimate the IFR in Gaussian noise

Key concepts: Impulse noise, Gaussian noise, Phase noise, Impulse (physics), Gaussian, Noise (video), Algorithm, Gradient noise

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