Statistical Analysis of Fast Fluctuating Random Signals with Arbitrary-Function Envelope and Unknown Parameters

  • Oleg V. Chernoyarov
  • Martin Vaculik
  • Armen Shirikyan
  • Alexandra V. Salnikova
Keywords: fast fluctuating random signal, maximum likelihood method, solving statistics, signal detection and estimation, local Markov approximation method, statistical modeling

Abstract

We find a new expression for the solving statistics of fast fluctuating Gaussian pulses with arbitrary-function envelope, based on which we can receive much simpler processing algorithms of random signals with unknown parameters in comparison with available analogues. For example, the synthesis and analysis of maximum likelihood detector and measurer of a high-frequency random pulse with unknown time parameter is carried out. The asymptotically exact expressions for detection and estimation characteristics including anomalous effects are presented. By methods of statistical computer modeling the adequacy of the considered analytical approach of the statistical analysis of random pulsed signals is corroborated, the working capacity of offered detector and measurer is established, and applicability borders of asymptotically exact formulas for their characteristics are also defined.

Author Biographies

Oleg V. Chernoyarov

National Research University “Moscow Power Engineering Institute”, Moscow, Russia

Martin Vaculik

Department of Telecommunications and Multimedia, University of Zilina, Slovakia

Armen Shirikyan

University of Cergy-Pontoise, Cergy-Pontoise, France

Alexandra V. Salnikova

Voronezh State University of Architecture and Civil Engineering, Voronezh, Russia

Published
2015-04-30
How to Cite
Chernoyarov, O. V., Vaculik, M., Shirikyan, A., & Salnikova, A. V. (2015). Statistical Analysis of Fast Fluctuating Random Signals with Arbitrary-Function Envelope and Unknown Parameters. Communications - Scientific Letters of the University of Zilina, 17(1A), 35-43. Retrieved from http://journals.uniza.sk/index.php/communications/article/view/410
Section
Articles