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Telecommunications and Radio Engineering
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ISSN Print: 0040-2508
ISSN Online: 1943-6009

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Telecommunications and Radio Engineering

DOI: 10.1615/TelecomRadEng.v79.i10.20
pages 847-853

PROBABILISTIC MEASURE FOR DESCRIPTION OF MARKS OF ALIVE HUMAN IN SIGNALS OF RADAR FOR RESCUER

Oleg Sytnik
O.Ya. Usikov Institute for Radio Physics and Electronics, National Academy of Sciences of Ukraine, 12 Academician Proskura St., Kharkiv 61085, Ukraine
I. Vyzmitinov
O.Ya. Usikov Institute for Radio Physics and Electronics, National Academy of Sciences of Ukraine, 12 Academician Proskura St., Kharkiv 61085, Ukraine

ABSTRACT

The problem of adequate mathematical description of informative stochastic processes in Doppler spectrum of radar's signal is discussed. Smoke, fog, snow avalanche and sand scree, collapses of brick and concrete walls and other disasters do not allow the use of optical sensors to detect injured persons. Electromagnetic waves of decimeter band penetrate these obstacles well. The processes of breathing and heartbeat according to Doppler effect caused phase fluctuations in the reflected signals. The idea of analyzing Doppler phase spectrum of a signal reflected from a person is put on rescuer radar's operation algorithm. High sensitivity and jammer suppression of the sensor achieved by using pseudorandom phase manipulation of continuous sounding signals and coherent mode of digital signal processing. The properties of the spectra of human breathing and heartbeat were studied. To synthesize a model of a non-stationary stochastic process, the mathematical apparatus of the theory of probability measures is used. The description is based on a generalized distribution function of a random stationary non-Gaussian process. The model is a generalization of the local functions of Rayleigh, Rice, Hoyt, Markum, Nakagami, etc. The accuracy of the estimates is investigated theoretically and verified experimentally. It is shown that by controlling the parameters of the model it is possible to generate random sequences that satisfy various distribution functions. Relations for generating random sequences of generalized distribution function are obtained.

REFERENCES

  1. Sytnik, O.V., (2018) Methods and Algorithms of Signal Processing for Rescuer's Radar, Riga, Latvia: Palmarium Academic Publishing, 73 p. ISBN 978-3-659-72434-3.

  2. Sytnik, O.V., (2013) Digital Signal Processing in Doppler Radar for Rescuers to Detection of Human Breathing, Radar Science and Technology, 11(2), pp. 111-117.

  3. Sytnik, O.V., Vyzmitinov, I.A., and Myroshnichenko, Ye.I., (2009) Doppler Spectra of Human Breathing and Stochastic Models for their Description, Telecommunications and Radio Engineering, 68(9), pp. 779-788.

  4. Sytnik, O.V., (2015) Adaptive Radar Techniques for Human Breathing Detection, Journal of Mechatronics, 3(4), pp. 1-6.

  5. Frank, U.A., Kratzer, D.L., and Sullivan, J.L., (1967) The Twopound Radar, RCA Eng., 13(2), p.52-54.

  6. Chen Kun-Mu, Huang Yong, Zhang Jianping, and Norman Adam, (2000) Microwave life-detection systems for searching human subjects under earthquake rubble or behind barrier, IEEE Trans. Biomed. Eng., 47(1), pp. 105-114.

  7. Ivashov, S.I., Sablin, V.N., and Vasilyev I.A., (1999) Wide-Span Systems of Mine Detection, IEEE Aerospace & Electronics Systems Magazine, 14(5), pp. 6-8.

  8. Loeve, M., (1977) Probability Theory I, Springer-Verlag, N.Y., Berlin, Heidelberg, 912p.

  9. Terence Tao, (2011) An Introduction to Measure Theory, Graduate Studies in Mathematics, 126, 206 p.

  10. Huynen, I., Mcnolty, F., and Hansen, E., (1975) Component Distribution for Fluctuating Radar Targets, IEEE Trans., AES-11(6), pp. 1316-1328.

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