Fractal Features of Specific Emitter Identification

• Authors: J. Dudczyk , A. Kawalec
• Languages of publication: EN

Abstracts

EN

This article presents the issues connected with emitter sources identification with low distinctive primary features of a signal. It is a specific type of identification called specific emitter identification, which distinguishes different copies of the same type of emitter. The term of specific emitter identification was presented on the basis of fractal features received from the transformation of measurement data sets. The use of linear regression and Lagrange polynomial interpolation resulted in the estimation of measurement function. The method analysing properties of measurement function which was suggested by the authors caused the extraction of two additional distinctive features. The features above extended the vector of basic radar signals' parameters. The extended vector of radar signals' features made it possible to identify the copy of emitter source.

Keywords

EN

42.30.Sy; 47.54.-r; 43.60.Lq

Discipline

• 47.54.-r: Pattern selection; pattern formation(see also 82.40.Ck Pattern formation in reactions with diffusion, flow and heat transfer in Physical chemistry and chemical physics; 87.18.Hf Spatiotemporal pattern formation in cellular populations in Biological and medical physics)
• 42.30.Sy: Pattern recognition

• Publisher: Institute of Physics, Polish Academy of Sciences
• Journal: Acta Physica Polonica A
• Year: 2013
• Volume: 124
• Issue: 3
• Pages: 406-409

Dates

published

2013-09

Contributors

author

J. Dudczyk

• WB Electronics S.A., Poznańska 129/133, 05-850 Ożarów Mazowiecki, Poland

author

A. Kawalec

• Institute of Radioelectronics, Faculty of Electronics, Military University of Technology, S. Kaliskiego 2, 00-908 Warsaw, Poland

References

• [1] K.I. Talbot, P.R. Duley, M.H. Hyatt, Technol. Rev. J. Spring/Summer, 113 ( 2003)
• [2] M.W. Liu, J.F. Doherty, in: 10.1109/SARNOF.2008.4520119 Proc. 2008 IEEE Sarnoff Symp., Princeton (NJ) 2008, p. 1
• [3] M. Conning, F. Potgieter, in: Proc. 2010 IEEE Radar Conf., Washington 2010, p. 35
• [4] F. Berizzi, G. Bertini, M. Martorella, IEEE Trans. Geosci. Remote Sens. 44, 2361 (2006)
• [5] M. German, G.B. Bénié, J.M. Boucher, IEEE Trans. Geosci. Remote Sens. 41, 1765 (2003)
• [6] J. Dudczyk, Ph.D. Thesis, Faculties Telecommunication, Univ. of Tech., Warsaw 2004 (in Polish)
• [7] L. Kowalski, Statistics, Military Univ. of Technology Press, Warsaw 2001 (in Polish)
• [8] Z. Hellwig, Theory of Probability and Mathematical Statistics, PWN, Warsaw 1998 (in Polish)
• [9] J. Kudrewicz, Fractals and Chaos, WNT, Warsaw 2007 (in Polish)
• [10] R. Leitner, Mathematics for Technical Studies, WNT, Warsaw 1989 (in Polish)
• [11] S. Theodoridis, K. Koutroumbas, Pattern Recognition, Academic Press, San Diego 1999
• [12] W. Jakubik, M. Urbanczyk, E. Maciak, T. Pustelny, Bull. Pol. Acad. Sci., Techn. Sci. 56, 133 (2008)
• [13] P. Marczynski, A. Szpakowski, C. Tyszkiewicz, T. Pustelny, Acta Phys. Pol. A 122, 847 (2012)
• [14] R.O. Duda, P.E. Hart, D.G. Stork, Pattern Classification, Wiley, New York 2000
• [15] K. Fukunaga, Introduction to Statistical Pattern Recognition, Academic Press, New York 1990

Identifiers

DOI

10.12693/APhysPolA.124.406