Earth, Moon, and Planets

, Volume 116, Issue 2, pp 101–113 | Cite as

Automatic Analysis of Radio Meteor Events Using Neural Networks

  • Victor Ştefan Roman
  • Cătălin Buiu


Meteor Scanning Algorithms (MESCAL) is a software application for automatic meteor detection from radio recordings, which uses self-organizing maps and feedforward multi-layered perceptrons. This paper aims to present the theoretical concepts behind this application and the main features of MESCAL, showcasing how radio recordings are handled, prepared for analysis, and used to train the aforementioned neural networks. The neural networks trained using MESCAL allow for valuable detection results, such as high correct detection rates and low false-positive rates, and at the same time offer new possibilities for improving the results.


Automatic meteor detection Self-organizing map Multi-layered perceptron 



This work was supported by a grant from the Romanian National Authority for Scientific Research, CNDI-UEFISCDI, project number 205/2012. The work of V.Ş. Roman is supported by the Sectoral Operational Programme Human Resources Development (SOP-HRD), financed from the European Social Fund and the Romanian Government, under the contract number POSDRU/159/1.5/S/137390. V. Ş. Roman performed part of this work during a research stage at L’Institute d’Aéronomie Spatiale de Belgique and would like to thank Hervé Lamy for his kind support.

Supplementary material

11038_2015_9473_MOESM1_ESM.doc (378 kb)
Supplementary material 1 (DOC 377 kb)


  1. S. Calders, H. Lamy, Brams: status of the network and preliminary results, in Proceedings of the International Meteor Conference (IMC 2011) (2012), pp. 73–76Google Scholar
  2. A. Georgescu, T. Georgescu, Romanian AllSky Network: basic deployment, in Proceedings of the 32nd International Meteor Conference (IMC 2013) (2013). 22–25 Aug 2013Google Scholar
  3. P.S. Gural, Algorithms and software for meteor detection. Earth Moon Planets 102, 269–275 (2007)CrossRefADSGoogle Scholar
  4. S. Haykin, Neural Networks: A Comprehensive Foundation, 2nd edn. (Prentice Hall PTR, Upper Saddle River, NJ, 1998)Google Scholar
  5. W.K. Hocking, B. Fuller, B. Vandepeer, Real-time determination of meteor-related parameters utilizing modern digital technology. J. Atmos. Sol. Terr. Phys. 63(2–3), 155–169 (2001)CrossRefADSGoogle Scholar
  6. P. Jenniskens, P.S. Gural, L. Dynneson, B.J. Grigsby, K.E. Newman, M. Borden, M. Koop, D. Holman, CAMS: Cameras for Allsky Meteor Surveillance to establish minor meteor showers. Icarus 216(1), 40–61 (2011)CrossRefADSGoogle Scholar
  7. T. Kohonen, The self-organizing map. Proc. IEEE 78(9), 1464–1480 (1990)CrossRefGoogle Scholar
  8. H. Lamy, E. Gamby, S. Ranvier, Y. Geunes, S. Calders, J. de Kaiser, The BRAMS viewer: an on-line tool to access the BRAMS data, in Proceedings of the International Meteor Conference (IMC 2012) (2013). pp. 48–50Google Scholar
  9. J.D. Mathews, D. Janches, D.D. Meisel, Q.-H. Zhou, The micrometeoroid mass flux into the upper atmosphere: Arecibo results and a comparison with prior estimates. Geophys. Res. Lett. 28(10), 1929–1932 (2001)CrossRefADSGoogle Scholar
  10. D. Rumelhart, J. McClelland, PDP Research Group, Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol I, Foundations (MIT Press, Cambridge, MA, 1986)Google Scholar
  11. J.M. Trigo-Rodriguez, J.M. Madiedo, P.S. Gural, A.J. Castro-Tirado, J. Llorca, J. Fabregat, S. Vítek, P. Pujols, Determination of meteoroid orbits and spatial fluxes by using high-resolution All-Sky CCD cameras. Earth Moon Planets 102(1–4), 231–240 (2008)CrossRefADSGoogle Scholar
  12. E. Uriarte, F. Martín, Topology preservation in SOM, in World Academy of Science, Engineering and Technology, International Science Index 21, vol 2, no. 9 (2008), pp. 867–870Google Scholar
  13. C.-H. Wen, J.F. Doherty, J.D. Mathews, D. Janches, Meteor detection and non-periodic bursty interference removal for Arecibo data. J. Atmos. Sol. Terr. Phys. 67(3), 275–281 (2005)CrossRefADSGoogle Scholar
  14. R.J. Weryk, P.G. Brown, Simultaneous radar and video meteors—I: metric comparisons. Planet Space Sci. 62(1), 132–152 (2012)CrossRefADSGoogle Scholar
  15. R.J. Weryk, M.D. Campbell-Brown, P.A. Wiegert, P.G. Brown, Z. Krzeminski, R. Musci, The Canadian automated meteor observatory (CAMO): system overview. Icarus 225(1), 614–622 (2013)CrossRefADSGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Department of Automatic Control and Systems EngineeringPolitehnica University of BucharestBucharestRomania

Personalised recommendations