Clutter Removal for RADAR Wind Profiler using Wavelet Thresholding
M. Krupa Swaroopa Rani1, G. Kiran Kumar2, M. Krishnaiah3, K. Kameswara Rao4
1M. Krupa Swaroopa Rani, Academic Consultant, Dept. of ECE, School of Engineering and Technology, SriPadmavathi Mahila Viswa Vidyalayam, Tirupati, Andhra Pradesh, India.
2G. Kiran Kumar, Research Scholar, Dept. of Physics, Sri Venkateswara University, Tirupati, Andhra Pradesh, India.
3M. Krishnaiah, Professor, Research Guide, Dept. of Physics, Sri Venkateswara University, Tirupati, Andhra Pradesh, India
4K. Kameswara Rao Sr. Lecturer, Dept. of Physics, S. V. Arts college, Tirupati, Andhra Pradesh, India.
Manuscript received on April 15, 2014. | Revised Manuscript received on April 16, 2014. | Manuscript published on April 25, 2014. | PP:28-42 | Volume-2 Issue-6, April 2014. | Retrieval Number: F0718042614/2014©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Atmospheric Signal processing has been one field of signal processing where there is a lot of scope for development of new and efficient tools for cleaning of the spectrum, detection and estimation of the desired parameters. The field of digital signal processing is a very active area for research and applications. Atmospheric signal processing deals with the processing of the signals received from the atmosphere when manually stimulated using atmospheric Radar. Removal of clutter in the radar wind profiler is the utmost important consideration in radar. In this paper, we implement wavelet thresholding for removing clutter from wind profiler Radar data. By applying the concept of discrete multi-resolution analysis and non-parametric estimation theory, we develop wavelet domain thresholding rules, which identifies the coefficients relevant for clutter and suppresses them and increases the accuracy of wind vector reconstruction.
Keywords: Clutter, Signal Processing, Wind Profiler, Wavelet Thresholding.