Recovery of drifting sensor responses by means of DWT analysis

This work underlines the ability of the discrete wavelet transform to recover sensor signals subjected to drift effects. The drift resides in low requencies, so that it is needed to reveal the signal trend. So far, discrete wavelet transform (DWT) is an efficient tool for pre-processing drifting ensor responses as this technique provides a multi-scale processing analysis where the signal is split into lowand high-frequency components t different scales (or different frequency bands) with different resolutions. The trend is the slowest part of the signal and as the scale increases a etter estimate of the unknown trend is obtained. Once the signal components, where drift contamination is present, are selected and discarded, the re-processed signal is not distorted by excessive cutting off low-frequency components. The results are compared with ones obtained by applying tandard high-pass filters. 2006 Elsevier B.V. All rights reserved.