Accuracy improvement of the wigner distribution estimate in non-Gaussian noise environment by means of clipping technique application
ABSTRACT Wigner distribution (WD) is known to be one of the most convenient time-frequency representations for FM signal analysis in Gaussian noise environment. However, in case of impulsive interferences, WD occurs to be non -robust to noise. For improving robustness of the WD, it is proposed to use filtering approach based on the clipping technique. It can be applied at one of the following two stages: for filtering input FM signal or for local autocorrelation function processing. Based on the fact that there are two robust estimators of FM signal amplitude, four new methods for obtaining WD are proposed. The comparative analysis has been performed for two test signals - harmonic and linear FM ones. It is shown that the proposed methods allow considerable improving the accuracy of WD both for impulse noise environments and Gaus sian noise.
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ABSTRACT: This paper overviews basic principles and applications of the robust DFT (RDFT) approach, which is used for robust processing of frequency-modulated (FM) signals embedded in non-Gaussian heavy-tailed noise. In particular, we concentrate on the spectral analysis and filtering of signals corrupted by impulsive distortions using adaptive and nonadaptive robust estimators. Several adaptive estimators of location parameter are considered, and it is shown that their application is preferable with respect to non-adaptive counterparts. This fact is demonstrated by efficiency comparison of adaptive and nonadaptive RDFT methods for different noise environments.EURASIP Journal on Advances in Signal Processing. 01/2010;