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Research Article |

Lifting Wavelets with OGS for Doppler Profile Estimation

Author(s): Potladurty Suresh Babu* and Dr. G. Sreenivasulu,

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 11, Issue 4

Publisher : FOREX Publication

Published : 30 October 2023

e-ISSN : 2347-470X

Page(s) : 933-938

DOI: https://doi.org/10.37391/ijeer.110408

Abstract

This article discusses the second-generation wavelet transform concept and technique and its application to the noise removal problem of MST radar data. Located near Gadanki in Andhra Pradesh, India, the MST radar is collecting data on climate change. To obtain weather data, the signal collected by the radar needs to be analyzed, which usually requires power spectrum estimation. Most parametric and non-parametric methods cannot predict Doppler at an altitude above 14 KM, which makes to search for introduction of new denoising methods. More research is predominantly done on many denoising algorithms and tested with the simulated signal with various thresholds. It is observed that Lifting wavelets (LWT) with OGS is more effective in denoising the signals. Split, predict, and update are the three phases of lifting transform which on application of these steps reduces noise effectively. The LWT with OGS is applied to MST radar data and the research results shows that the noise level is reduced at higher altitudes and the signal-to-noise ratio is improved.

Keywords: MST RADAR Signal Processing, Doppler Estimation, Lifting Wavelets, Overlapping Group Shrinkage, Wind Speed.




Potladurty Suresh Babu*, Associate Professor, Department of ECE, Sri Venkateswara College of Engineering, Tirupati (A.P), India; Email: sureshbabu.413@gmail.com

Dr. G. Sreenivasulu, Professor, Department of ECE, Sri Venkateswara University College of Engineering, Sri Venkateswara University, Tirupati (A.P), India; Email: gunapatieee@rediffmail.com

    [1] Donoho, D., and I. Johnstone, “Minimax estimation via wavelet shrinkage”, Annals of Statistics, 26: 879-921, 1998.
    [2] Taswell, C., “The What, How and Why of Wavelet Shrinkage Denoising”, IEEE Computing Science and Engineering, 2(3), 12-19, 2000.
    [3] Soman, K.P., and K.I.Ramachandran,“Insight into Wavelets from theory to Practice”, Prentice hall of India, 2004.
    [4] Suresh Babu Potladurty, G.Sreenivasulu, “Mesosphere Stratosphere Troposphere (MST) Radar Signal using Discrete wavelet Transform with Overlapping Group Shrinkage”, International Journal of Advanced Science and Technology, Vol 28, No 9,133-136, 2019.
    [5] Liu, R., Liu X., Suo, J., Wang, X, “The radar clutter processor with wavelet floating threshold”, proceeding of CIE International Conference on Radar, pp.1001-1005, 2001.
    [6] Donoho, D., and I. Johnstone, “Adapting to unknown smoothness via wavelet shrinkage”, Journal of the American Statistical Association, 90: 1200-1224, 1995.
    [7] Zhang Xueying et al,“ Signal Denoising with Non linear lifting Scheme”, J. of Math. (Chinese), 24(2), 193-196, 2004.
    [8] S.R. Thatiparthi, R.R. Gudheti, V. Sourirajan, MST Radar Signal Processing Using Wavelet-Based Denoising, IEEE Geo science and Remote Sensing Letters, 2009.
    [9] G.Chandraiah et al, MST Radar Signal Processing using PCA Based Minimum-Variance Spectral Estimation Method, International Journal of Modern Electronics and Communication Engineering (IJMECE) ISSN: 2321-2152,Volume No.-6, Issue No.-6, November, 2018.
    [10] C.Raju et al, 2018, MST radar signal processing using iterative adaptive approach, Geosci. Lett. (2018), https://doi.org/10.1186/s40562-018-0120-0 16.
    [11] G.Chandraiah et al, 2018, Denoising of MST Radar Signal Using Multi-Band Wavelet Transform with Improved Thresholding, Second International Conference on Inventive Communication and Computational Technologies (ICICCT), DOI:10.1109/ ICICCT.2018.8473060.
    [12] Suresh Babu Potladurty et al, Spectral Estimation of MST Radar Data using IAP, IJRECE VOL. 7 ISSUE 3 JULY. -SEPT 2019, ISSN: 2348-2281 (ONLINE).
    [13] Suresh Babu Potladurty et al,2021, Denoising of MST RADAR Signal using CWT and Overlapping Group Shrinkage, Turkish Journal of Computer and Mathematics Education Vol.12 No. 5 (2021), 1950-1954.
    [14] Feng Lin et al, “Denoising of logging data using lifting Scheme”, Geophysical Prospecting for Petroleum, 43(3): 238–241,2004 Pages 79-84.

Potladurty Suresh Babu and Dr. G. Sreenivasulu (2023), Lifting Wavelets with OGS for Doppler Profile Estimation. IJEER 11(4), 933-938. DOI: 10.37391/ijeer.110408.