Improved Moments Estimation for VHF Active Phased Array Radar Using Fuzzy Logic Method

S. Allabakash Department of Physics, Sri Venkateswara University, Tirupati, India

Search for other papers by S. Allabakash in
Current site
Google Scholar
PubMed
Close
,
P. Yasodha National Atmospheric Research Laboratory, Department of Space, Government of India, Gadanki, India

Search for other papers by P. Yasodha in
Current site
Google Scholar
PubMed
Close
,
L. Bianco Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, and NOAA/Earth System Research Laboratory/Physical Sciences Division, Boulder, Colorado

Search for other papers by L. Bianco in
Current site
Google Scholar
PubMed
Close
,
S. Venkatramana Reddy Department of Physics, Sri Venkateswara University, Tirupati, India

Search for other papers by S. Venkatramana Reddy in
Current site
Google Scholar
PubMed
Close
, and
P. Srinivasulu National Atmospheric Research Laboratory, Department of Space, Government of India, Gadanki, India

Search for other papers by P. Srinivasulu in
Current site
Google Scholar
PubMed
Close
Restricted access

We are aware of a technical issue preventing figures and tables from showing in some newly published articles in the full-text HTML view.
While we are resolving the problem, please use the online PDF version of these articles to view figures and tables.

Abstract

Various nonatmospheric signals contaminate radar wind profiler data, introducing bias into the moments and wind velocity estimation. This study applies a fuzzy logic–based method to Doppler velocity spectra to identify and eliminate the clutter echoes. This method uses mathematical analyses and a fuzzy inference system applied to each Doppler velocity spectrum to separate the atmospheric signals from the clutter. After eliminating the clutter, an adaptive algorithm is used to estimate mean Doppler velocities accurately. This combination of techniques is applied to the spectral data obtained by the newly developed 53-MHz active phased array radar located at the National Atmospheric Research Laboratory (NARL), Gadanki, India (13.5°N, 79°E). Winds derived using the conventional method and the method developed for this study are compared with those obtained by collocated GPS radiosonde. The comparison shows that the present method derives the winds more accurately compared to the conventional method.

Corresponding author address: S. Venkatramana Reddy, Department of Physics, Sri Venkateswara University, Tirupati 517 502, Andhra Pradesh, India. E-mail: drsvreddy123@gmail.com

Abstract

Various nonatmospheric signals contaminate radar wind profiler data, introducing bias into the moments and wind velocity estimation. This study applies a fuzzy logic–based method to Doppler velocity spectra to identify and eliminate the clutter echoes. This method uses mathematical analyses and a fuzzy inference system applied to each Doppler velocity spectrum to separate the atmospheric signals from the clutter. After eliminating the clutter, an adaptive algorithm is used to estimate mean Doppler velocities accurately. This combination of techniques is applied to the spectral data obtained by the newly developed 53-MHz active phased array radar located at the National Atmospheric Research Laboratory (NARL), Gadanki, India (13.5°N, 79°E). Winds derived using the conventional method and the method developed for this study are compared with those obtained by collocated GPS radiosonde. The comparison shows that the present method derives the winds more accurately compared to the conventional method.

Corresponding author address: S. Venkatramana Reddy, Department of Physics, Sri Venkateswara University, Tirupati 517 502, Andhra Pradesh, India. E-mail: drsvreddy123@gmail.com
Save
  • Anandan, V. K., Balamurlidhar P. , Rao P. B. , Jain A. R. , and Pan C. J. , 2005: An adaptive moments estimation technique applied to MST radar echoes. J. Atmos. Oceanic Technol., 22, 396408, doi:10.1175/JTECH1696.1.

    • Search Google Scholar
    • Export Citation
  • Balsley, B. B., and Gage K. S. , 1982: On the use of radars for operational wind profiling. Bull. Amer. Meteor. Soc., 63, 10091018, doi:10.1175/1520-0477(1982)063<1009:OTUORF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Barth, M. F., Chadwick R. B. , and van de Kamp D. W. , 1994: Data processing algorithms used by NOAA’s Wind Profiler Demonstration Network. Ann. Geophys., 12, 518528, doi:10.1007/s00585-994-0518-1.

    • Search Google Scholar
    • Export Citation
  • Bianco, L., and Wilczak J. M. , 2002: Convective boundary layer depth: Improved measurement by Doppler radar wind profiler using fuzzy logic methods. J. Atmos. Oceanic Technol., 19, 17451758, doi:10.1175/1520-0426(2002)019<1745:CBLDIM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Carter, D., Gage K. S. , Ecklund W. L. , Angevine W. M. , Johnston P. E. , Riddle A. C. , Wilson J. , and Williams C. R. , 1995: Development in UHF lower tropospheric wind profiling at NOAA’s Aeronomy Laboratory. Radio Sci., 30, 9771001, doi:10.1029/95RS00649.

    • Search Google Scholar
    • Export Citation
  • Cornman, L. B., Goodrich R. K. , Morse C. S. , and Ecklund W. L. , 1998: A fuzzy logic method for improved moment estimation from Doppler spectra. J. Atmos. Oceanic Technol., 15, 12871305, doi:10.1175/1520-0426(1998)015<1287:AFLMFI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Gage, K. S., and Balsley B. B. , 1978: Doppler radar probing of the clear atmosphere. Bull. Amer. Meteor. Soc., 59, 10741093, doi:10.1175/1520-0477(1978)059<1074:DRPOTC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hildebrand, P. H., and Sekhon R. S. , 1974: Objective determination of the noise level in Doppler spectra. J. Appl. Meteor., 13, 808811, doi:10.1175/1520-0450(1974)013<0808:ODOTNL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Jordan, J. R., Lataitis R. J. , and Carter D. A. , 1997: Removing ground and intermittent clutter contamination from wind profiler signals using wavelet transforms. J. Atmos. Oceanic Technol., 14, 12801297, doi:10.1175/1520-0426(1997)014<1280:RGAICC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Klir, G. J., Clair U. H. St. , and Yuan B. , 1997: Fuzzy Set Theory: Foundations and Applications. Prentice Hall, 245 pp.

  • Lehmann, V., and Teschke G. , 2001: Wavelet based methods for improved wind profiler signal processing. Ann. Geophys., 19, 825836, doi:10.5194/angeo-19-825-2001.

    • Search Google Scholar
    • Export Citation
  • Lehtinen, R., and Jordan J. , 2006: Improving wind profiler measurements exhibiting clutter contamination using wavelet transforms. Preprints, WMO Tech. Conf. on Meteorological and Environmental Instruments and Methods of Observation (TECO-2006), Geneva, Switzerland, WMO, P2.20. [Available online at http://www.wmo.int/pages/prog/www/IMOP/publications/IOM-94-TECO2006/P2(20)_Lehtinen_USA.pdf.]

  • Mathworks, 2013: MATLAB fuzzy logic toolbox: User’s guide. Release R2013b.

  • Merritt, D. A., 1995: A statistical averaging method for wind profiler Doppler spectra. J. Atmos. Oceanic Technol., 12, 985995, doi:10.1175/1520-0426(1995)012<0985:ASAMFW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Morse, C. S., Goodrich R. K. , and Cornman L. B. , 2002: The NIMA method for improved moment estimation from Doppler spectra. J. Atmos. Oceanic Technol., 19, 274295, doi:10.1175/1520-0426-19.3.274.

    • Search Google Scholar
    • Export Citation
  • Passarelli, R. E., Romanik P. , Geotis S. G. , and Siggia A. D. , 1981: Ground clutter rejection in the frequency domain. Preprints, 20th Conf. on Radar Meteorology, Boston, MA, Amer. Metor. Soc., 295–300.

  • Riddle, A. C., and Angevine W. M. , 1992: Ground clutter removal from profiler spectra. Proceedings of the Fifth Workshop on Technical and Scientific Aspects of MST Radar, B. Edwards, Ed., SCOSTEP Secretariat, University of Illinois, 418–420.

  • Sato, T., 1989: Radar principles. Middle Atmosphere Program, S. Fukao, Ed., Handbook for MAP, Vol. 30, SCOSTEP Secretariat, University of Illinois, 19–53.

  • Sivanandam, S. N., Sumathi S. , and Deepa S. N. , 2007: Introduction to Fuzzy Logic Using MATLAB. Kindle ed. Springer, 430 pp.

  • Srinivasulu, P., Kamaraj P. , Yasodha P. , Durga Rao M. , and Allabakash S. , 2013: VHF active phased array radar for atmospheric remote sensing at NARL. Proc. Int. Radar Symp. India 2013, Banaglore, India, IEEE, 149. [Available online at www.radarindia.com/irsi13papers/13-FP-149.pdf.]

  • Strauch, R. G., Merritt D. A. , Moron K. P. , Earnshaw K. B. , and van de Kamp D. W. , 1984: The Colorado wind-profiling network. J. Atmos. Oceanic Technol., 1, 3749, doi:10.1175/1520-0426(1984)001<0037:TCWPN>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wilczak, J. M., and Coauthors, 1995: Contamination of wind profiler data by migrating birds: Characteristics of corrupted data and potential solutions. J. Atmos. Oceanic Technol., 12, 449467, doi:10.1175/1520-0426(1995)012<0449:COWPDB>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Woodman, R. F., 1985: Spectral moment estimation in MST radars. Radio Sci., 20, 11851195, doi:10.1029/RS020i006p01185.

  • Zadeh, L. A., 1965: Fuzzy sets. Inf. Control, 8, 338353, doi:10.1016/S0019-9958(65)90241-X.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 608 305 123
PDF Downloads 294 35 4