New Deconvolution Technique to Improve the Depth Resolution in Secondary Ion Mass Spectrometry

Authors N. Dahraoui1, M. Boulakroune2, D. Benatia1

1Electronics Department, Faculty of Engineer Sciences, University Batna 2, 05000 Batna, Algeria

2Electrical and Automatic Department, National Polytechnic School of Constantine, 25000 Constantine, Algeria

Issue Volume 11, Year 2019, Number 2
Dates Received 30 December 2018; revised manuscript received 03 April 2019; published online 15 April 2019
Citation N. Dahraoui, M. Boulakroune, D. Benatia, J. Nano- Electron. Phys. 11 No 2, 02021 (2019)
PACS Number(s) 68.49.Sf, 82.80.Ms
Keywords Kalman filter, Denoising techniques, SIMS depth profiles, Wavelet shrinkage, Tikhonov-Miller regularization, Depth resolution.

This paper presents an efficient method for recovery of SIMS signals from strongly noised blurred discrete data. This technique is based on Tikhonov-Miller regularization where a priori model of solution is included. The latter is a denoisy signal obtained using the Kalman filter. This is an interesting estimation method, but it can only be used when the system is described precisely.By comparing the results of the proposed technique with those of the literature, our algorithm gives the best results without artifacts and oscillations related to noise and significant improvement of the depth resolution. While, the gain in FWHM is less improved than those obtained by the wavelet technique. Therefore, this new algorithm can push the limits of SIMS measurements towards its ultimate resolution.

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