Robustness Analysis of the Phase-Phase Correlator to White Impulsive Noise With Applications to Autoregressive Modeling

Using only the phase information and a relationship based on the Gaussian Hypergeometric function, the Phase-Phase Correlator can be utilized to estimate the normalized cross-correlation coefficient between two zero-mean complex Gaussian processes. This estimator naturally introduces a certain robus...

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Bibliographic Details
Published in:IEEE transactions on signal processing 2012-11, Vol.60 (11), p.6053-6058
Main Authors: Tamburello, P., Mili, L.
Format: Article
Language:English
Subjects:
Applied sciences
Asymptotic properties
Automotive engineering
Bias curve
Contamination
Correlation
correlation coefficient
Correlators
Detection, estimation, filtering, equalization, prediction
Estimates
Exact sciences and technology
Gaussian
impulsive noise
Information, signal and communications theory
Maximum likelihood estimation
Noise
outliers
phase-phase correlator
Random processes
robust statistics
Robustness
Signal and communications theory
Signal representation. Spectral analysis
Signal, noise
Telecommunications and information theory
Time series analysis
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Summary:Using only the phase information and a relationship based on the Gaussian Hypergeometric function, the Phase-Phase Correlator can be utilized to estimate the normalized cross-correlation coefficient between two zero-mean complex Gaussian processes. This estimator naturally introduces a certain robustness to white impulsive observation noise over the Gaussian Maximum Likelihood estimator. This correspondence examines the robustness of the Phase-Phase Correlator in the presence of uncorrelated impulsive noise. We show that its asymptotic bias compares favorably to the robust Schweppe-type GM-estimator with the Huber function termed SHGM at a cost of efficiency. Application of the PPC to autoregressive time series analysis is illustrated with a parametric spectral estimation example.
ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2012.2210551