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Double Least-Squares Projections Method for Signal Estimation | IEEE Journals & Magazine | IEEE Xplore

Double Least-Squares Projections Method for Signal Estimation


Abstract:

A real-world signal is always corrupted with noise. The separation between a signal and noise is an indispensable step in a variety of signal-analysis applications across...Show More

Abstract:

A real-world signal is always corrupted with noise. The separation between a signal and noise is an indispensable step in a variety of signal-analysis applications across different scientific domains. In this paper, we propose a double least-squares projections (DLSPs) method to estimate a signal from the noisy data. The first least-squares projection is to find a signal-dimensional optimal approximation of the noisy data in the least-squares sense. In this step, a rough estimation of the signal is obtained. The second least-squares projection is to find an approximation of a signal in another crossed signal-dimensional space in the least-squares sense. In this step, a much improved signal estimation that is close to orthogonal to the separated noise subspace can be obtained. The DLSP implements projection operation twice to obtain an almost perfect estimation of a signal. The application of the DLSP method in seismic random noise attenuation and signal reconstruction demonstrates the successful performance in seismic data processing.
Published in: IEEE Transactions on Geoscience and Remote Sensing ( Volume: 55, Issue: 7, July 2017)
Page(s): 4111 - 4129
Date of Publication: 24 April 2017

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