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Journal Science Intensive Technologies №3 for 2015 г.
Article in number:
Threshold ratio signal-to-noise in spectral measurements of signal parameters
Authors:
A.S. Glinchenko - Ph. D. (Eng.), Professor, Department «Radio-electronic systems», Institute of engineering physics and radio electronics of the Siberian Federal University. Е-mail: AGlinchenko@sfu-kras.ru
V.A. Komarov - Ph. D. (Eng.), Associate Professor, Department «Radio-electronic technics of information systems», Siberian federal university; Head of Group of development, integration and payload test department, JSC «Academician M.F. Reshetnev «Information Satellite Systems» (Zheleznogorsk). Е-mail: VKomarov@iss-reshetnev.ru
A.M. Aleshechkin - Dr. Sc. (Eng.), Professor, Department «Radioelectronic systems», Institute of engineering physics and radio electronics of the Siberian Federal University. E-mail: AAleshechkin@sfu-kras.ru
Abstract:
The paper considers the solution of problems to ensure the reliability of the spectral measure signals at low signal to noise ratio. The first problem is to determine the probability of false measurements in signal detection by the maximum modulo of the frequency sampling DFT and threshold signal-to-noise ratio corresponding to this probability. Its decision is based on probabilistic characteristics of the module noise and signal frequency sample DFT with the distribution of Rayleigh and Rice. Based on them received generalized integral expression for the probability of false measurements for the real signal and the noise and the weighting functions of different types used for spectral measurements. Shows the values of the threshold signal-to-noise ratio corresponding to different values of the probability of false measurements.
By estimating the MSE of channel noise DFT for one signal implementation, the possibility to determine the required number of cycles averaging at multiple measurements for the admissibility of the random error of measurement of signal parameters is show.
Specified on necessity research other ways to detect the signal to improve the authenticity of measurements with a priori unknown signal to noise ratio.
The results are confirmed by statistical computer simulation and tested in the developed multi-function computer system for measurement of signal parameters.
Pages: 61-65
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