Abstract
National Atmospheric Research Laboratory (NARL) hosts several atmospheric measurements of which, MST Radar is being treated as a work horse, for which the wind observations up to an altitude of 100km is recorded. It is a great tool for studying the atmospheric dynamics. These radars are capable of measuring air motions over a wide range of heights with good spatial and temporal resolutions. The derivation of wind components from spectral data includes noise level estimation and then moment estimation. In the present context, Hildebrand and Sekhon method is utilized for noise level estimation for each range bin employing the physical properties of white noise. The interference due to stationary targets is reflected as the dc components which can be removed using conventional methods such as replacing the spectral power at zero frequency with the average of the power at adjacent spectral points and it is very important for distinguishing between the actual signals from interference echoes. In the light of automation of data analysis so as to obtain the wind components, it is mandatory to develop algorithms for the characterization of signal and interference echoes. In this work, an Automated Algorithm is developed for estimation of moments and is applied to Real Time Radar data from MST region near Gadanki, Tirupati.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Anandan, V.K.: Atmospheric Data Processor – Technical and User reference manual, National Atmospheric Research Laboratory, Gadanki
Hildebrand, P.H., Sekhon, R.S.: Objective determination of the noise level in Doppler spectra. J. Appl. Meterol. 13, 808–811 (1974)
Rao, P.B., Jain, A.R., Kishore, P., Balamuralidhar, P., Damle, S.H., Viswanadhan, G.: Indian MST radar. I: System description and samplevector wind measurements in ST mode. Radio Sci. 30(4), 1125–1138 (1995)
Woodman, R.F.: Spectral moment estimation in MST radars. Radio Sci. 20(6), 1185–1195 (1985). doi:10.1029/RS020i006p01185
Anandan, V.K., Ramachandra Reddy, G., Rao, P.B.: Spectral analysis of atmospheric signal using higher orders spectral estimation technique. IEEE Trans. Geosci. Remote Sens. 39(9), 1890–1895 (2001)
Anandan, V.K., Pan, C.J., Rajalakshmi, T., Ramchandra Reddy, G.: Multitaper spectral analysis of atmospheric radar signal. Ann. Geophys. 22(11), 3995–4003 (2004)
Anandan, V.K., Balamuralidhar, P., Rao, P.B., Jain, A.R.: A method for adaptive moments estimation technique applied to MST radar echoes. In: Proc. Prog. Electromagn. Res. Symp., pp. 360–365 (1996)
Madhavi latha, G., Padmaja, N., Varadarajan, S.: Estimation of Moments for Low and High SNR Atmospheric Radar Data. i-manager’s Journal on Communication Engineering and Systems (JCS), May–July 2012, ISSN Print: 2277-5102 ISSN Online: 2277-5242
Morse, C.S., Goodrich, R.K., Cornman, L.B.: The NIMA method for improved moment estimation from Doppler spectra. J. Atmos. Ocean. Technol. 19(3), 274–295 (2002)
Padmaja, N., Varadarajan, S., Swathi, R.: Signal Processing of Radar Echoes using Wavelets & Hilbert Huang Transform. Sipij: Signal and Image Processing: An International Journal 2(3), 101–119 (2011). ISSN: 0976 - 710X (Online); 2229 - 3922 (print)
Briggs, B.H.: Radar observations of atmospheric winds and turbulence: a comparison of techniques. Journal of Atmospheric and Terrestrial Physics 42, 823–833 (1980)
Goodrich, R.K., Morse, C.S., Cornman, L.B., Cohn, S.A.: A horizontal wind and wind confidence algorithm for Doppler wind profilers. J. Atmos. Oceans. Technol. 19(3), 257–273 (2002)
Anandan, V.K., Jagannatham, D.B.V.: An Autonomous Interference Detection and Filtering Approach Applied to Wind Profilers. IEEE Transactions on Geoscience and Remote Sensing 48(4), April 2010
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Ramyakrishna, E., Narayana Rao, T., Padmaja, N. (2016). Development and Evaluation of Automated Algorithm for Estimation of Winds from Wind Profiler Spectra. In: Thampi, S., Bandyopadhyay, S., Krishnan, S., Li, KC., Mosin, S., Ma, M. (eds) Advances in Signal Processing and Intelligent Recognition Systems. Advances in Intelligent Systems and Computing, vol 425. Springer, Cham. https://doi.org/10.1007/978-3-319-28658-7_40
Download citation
DOI: https://doi.org/10.1007/978-3-319-28658-7_40
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-28656-3
Online ISBN: 978-3-319-28658-7
eBook Packages: EngineeringEngineering (R0)