volume | PIER Journals

Abstract

In this paper, an AgileDARN (Agile Dual Auroral Radar Network) radar echo classification method based on support vector machine is proposed. AgileDARN radar echo includes ionospheric backscattering echo, meteor echo, noise interference, etc. With the continuous operation of AgileDARN radar, the amount of data increases rapidly, requiring efficient and reliable classification methods. In order to efficiently classify the echoes of AgileDARN radar, this paper proposes an echo classification method based on support vector machine. By analyzing the characteristics of the autocorrelation function (ACF) of the sampled data and extracting the features, the support vector machine(SVM) classification method is adopted to classify AgileDARN echo into ionospheric backscattering echo, meteor echo and noise interference. The data analysis shows that the classification accuracy of training data set is more than 99%, and that of test data set is more than 95%. Using this classification model to classify 1800 echo data of AgileDARN radar, the classification accuracy is more than 91% compared with the result of manual interpretation.

1. Greenwald, R. A., K. B. Baker, J. R. Dudeney, et al. "Darn superdarn --- A global view of the dynamics of high-latitude convection," Space Science Reviews, Vol. 71, No. 1-4, 761-796, 1995.
doi:10.1007/BF00751350 Google Scholar

2. Ribeiro, A. J., J. M. Ruohoniemi, P. V. Ponomarenko, et al. "A comparison of SuperDARN ACF tting methods," Radio Science, Vol. 48, No. 3, 274-282, 2013.
doi:10.1002/rds.20031 Google Scholar

3. Greenwald, R. A., J. B. Baker, R. A. Hutchins, et al. "An HF phased-array radar for studying small-scale structure in the high-latitude ionosphere," Radio Science, Vol. 20, 63-79, 1985.
doi:10.1029/RS020i001p00063 Google Scholar

4. Berngardt, O. I., J. M. Ruohoniemi, N. Nishitani, et al. "Attenuation of decameter wavelength sky noise during X-ray solar ares in 2013{2017 based on the observations of midlatitude HF radars," Journal of Atmospheric and Solar-Terrestrial Physics, Vol. 173, 1-13, 2018.
doi:10.1016/j.jastp.2018.03.022 Google Scholar

5. Ruohoniemi, J. M., R. A. Greenwald, J. P. Villain, et al. "Coherent HF radar backscatter from small-scale irregularities in the dusk sector of the subauroral ionosphere," Journal of Geophysical Research-Space Physics, Vol. 93, No. A11, 12871-12882, 1988.
doi:10.1029/JA093iA11p12871 Google Scholar

6. Milan, S. E., T. K. Yeoman, M. Lester, et al. "Initial backscatter occurrence statistics from the CUTLASS HF radars," Annales Geophysicae-Atmospheres Hydrospheres and Space Sciences, Vol. 15, No. 6, 703-718, 1997. Google Scholar

7. Hall, G. E., J. W. MacDougall, D. R. Moorcroft, et al. "Super dual auroral radar network observations of meteor echoes," Journal of Geophysical Research-Space Physics, Vol. 102, No. A7, 14603-14614, 1997.
doi:10.1029/97JA00517 Google Scholar

8. Hussey, G. C., C. E. Meek, D. Andre, et al. "A comparison of Northern Hemisphere winds using SuperDARN meteor trail and MF radar wind measurements," Journal of Geophysical Research- Atmospheres, Vol. 105, No. D14, 18053-18066, 2000.
doi:10.1029/2000JD900272 Google Scholar

9. Hibbins, R. E., M. P. Freeman, S. E. Milan, and J. M. Ruohoniemi, "Winds and tides in the mid-latitude Southern Hemisphere upper mesosphere recorded with the Falkland Islands SuperDARN radar," Annales Geophysicae, Vol. 29, No. 11, 1985-1996, 2011.
doi:10.5194/angeo-29-1985-2011 Google Scholar

10. Baker, K. B. and R. A. Greenwald, "The vertical angle of arrival of highfrequency signals propagating from thule to goose bay," Johns Hopkins APL Technical Digest, Vol. 9, No. 2, 121-130, 1988. Google Scholar

11. Chisham, G. and M. Pinnock, "Assessing the contamination of SuperDARN global convection maps by non-F-region backscatter," Annales Geophysicae, Vol. 20, No. 1, 13-28, 2002.
doi:10.5194/angeo-20-13-2002 Google Scholar

12. Andre, R., M. Pinnock, J. P. Villain, and C. Hanuise, "Influence of magnetospheric processes on winter HF radar spectra characteristics," Annales Geophysicae, Vol. 20, No. 11, 1783-1793, 2002.
doi:10.5194/angeo-20-1783-2002 Google Scholar

13. Blanchard, G. T., S. Sundeen, and K. B. Baker, "Probabilistic identification of high-frequency radar backscatter from the ground and ionosphere based on spectral characteristics," Radio Science, Vol. 44, No. 5, 1-9, 2009.
doi:10.1029/2009RS004141 Google Scholar

14. Berngardt, O. I., A. L. Voronov, and K. V. Grkovich, "Optimal signals of Golomb ruler class for spectral measurements at EKB SuperDARN radar: Theory and experiment," Radio Science, Vol. 50, No. 6, 486-500, 2015.
doi:10.1002/2014RS005589 Google Scholar

15. Barthes, L., R. Andre, J. C. Cerisier, and J.-P. Villain, "Separation of multiple echoes using a high-resolution spectral analysis for SuperDARN HF radars," Radio Science, Vol. 33, No. 4, 1005-1017, 1998.
doi:10.1029/98RS00714 Google Scholar

16. Liu, E. X., H. Q. Hu, R. Y. Liu, et al. "An adjusted location model for SuperDARN backscatter echoes," Annales Geophysicae, Vol. 30, No. 12, 1769-1779, 2012.
doi:10.5194/angeo-30-1769-2012 Google Scholar

17. Ribeiro, A. J., J. M. Ruohoniemi, J. B. H. Baker, et al. "A new approach for identifying ionospheric backscatter in midlatitude SuperDARN HF radar observations," Radio Science, Vol. 46, No. 4, 2011.
doi:10.1029/2011RS004676 Google Scholar

18. Lavygin, I. A., V. P. Lebedev, K. V. Grkovich, et al. "Identifying ground scatter and ionospheric scatter signals by using their ne structure at Ekaterinburg decameter coherent radar,", Cornell University Library, Ithaca, 2018. Google Scholar

19. Matthews, D. M., M. L. Parkinson, P. L. Dyson, et al. "Optimising estimates of mesospheric neutral wind using the TIGER SuperDARN radar," Advances in Space Research, Vol. 38, No. 11, 2353-2360, 2006.
doi:10.1016/j.asr.2005.07.046 Google Scholar

20. Yukimatu, A. S. and M. Tsutsumi, "A new SuperDARN meteor wind measurement: Raw time series analysis method and its application to mesopause region dynamics," Geophysical Research Letters, Vol. 29, No. 20, 2002.
doi:10.1029/2002GL015210 Google Scholar

21. Tsutsumi, M., A. S. Yukimatu, D. A. Holdsworth, et al. "Advanced SuperDARN meteor wind observations based on raw time series analysis technique," Radio Science, Vol. 44, No. 2, 1-11, 2009.
doi:10.1029/2008RS003994 Google Scholar

22. Parris, R. T., "Design and implementation of a meteor tracking retrot system for the HF radar at Kodiak Island, Alaska,", 110, University of Alaska Fairbanks, Ann Arbor, 2003. Google Scholar

23. Song, J., A. L. Lan, J. Y. Yan, et al. "Analysis of FPGA implementation for AgileDARN radar digital system," Remote Sensing Technology and Application, Vol. 32, No. 6, 1064-1070, 2017. Google Scholar

24. Farley, D. T., "Multiple-pulse incoherent-scatter correlation function measurements," Radio Science, Vol. 7, No. 6, 661-666, 1972.
doi:10.1029/RS007i006p00661 Google Scholar

25. Hanuise, C., R. A. Greenwald, and K. B. Baker, "Drift motions of very high latitude F region irregularities: Azimuthal Doppler analysis," Journal of Geophysical Research, Vol. 90, No. A10, 1985.
doi:10.1029/JA090iA10p09717 Google Scholar

26. Baker, J. B., R. A. Greenwald, J. P. Villain, et al. "spectral characteristics of high frequency backscatter from high latitude ionospheric irregularities | Preliminary analysis of statistical properties," Interim Rep., RADC-TR-87-284, Rome Air Dev. Cent., Briffis Air Force Base, 1988. Google Scholar

27. Cristianini, J. S.-T. N., An Introduction to Support Vector Machines and Other Kernel-based Learning Methods, Cambridge University Press, 2000.
doi:10.1017/CBO9780511801389

28. Burges, C. J., "A tutorial on support vector machines for pattern recognition," Data Mining Knowledge Discovery, 1998. Google Scholar

Dr. Guangming Li