Time-Frequency Analysis of the Pri Modulated and Frequency Hopping Radar Signals Using Spectrogram

  • A. A. Ahmad Department of Electrical and Electronic Engineering, Faculty of Engineering, Nigerian Defence Academy (NDA), Kaduna, Nigeria
  • A. S. Saliu Center for Geodesy and Geodynamics, National Space Research and Development Agency (NASRDA), Federal Ministry of Science and Technology, Toro, Nigeria
  • C. L. Wamdeo Department of Electrical and Electronic Engineering, Faculty of Engineering, Nigerian Defence Academy (NDA), Kaduna, Nigeria
  • S. Lawan Department of Electrical and Electronic Engineering, Faculty of Engineering, Nigerian Defence Academy (NDA), Kaduna, Nigeria
Keywords: Electronic warfare (EW), pulse width (PW), pulse repetition interval (PRI), time-frequency distribution (TFD), signal to noise ratio (SNR)

Abstract

Electronic warfare (EW) is drawing more attention in recent years. This is due to the dependency on electronic communication by both civilian and military worldwide. Despite all the measures to secure electronic communication, hostile parties such as terrorist groups, religious sects and multi-national corporations attack electronic communication. This paper proposes a set of algorithms to efficiently analyse the pulse width (PW), pulse repetition interval (PRI) and center frequency of radar signals. The aim is to use these accurately determined time and frequency parameters to determine capability of the emitted electromagnetic radar wave. The method involve the use of spectrogram time-frequency distribution (TFD) and other related statistical signal processing tools such as Hilbert transform and instantaneous frequency to process these radar signals using the MATLAB. The validation using the Monte Carlo simulation shows that probability of correct parameter estimation (POCPE) of 100% was achieved at signal to noise ratio (SNR) greater than (or equal to) -11dB and -1dB for time-based and frequency-based parameters respectively. The results obtained also show the method developed is efficient for signal analysis in the field of EW.

Published
2018-09-03
Section
Articles

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