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Power-based pulsed radar detection using wavelet denoising and spectral threshold with pattern analysis

Published online by Cambridge University Press:  26 February 2020

Ali Siblini Open the ORCID record for Ali Siblini [Opens in a new window] ,
Kassim Audi  and
Alaa Ghaith
Ali Siblini*
Affiliation:
Department of GRIT, Doctoral School of Sciences and Technologies, Lebanese University, Beirut, Lebanon
Kassim Audi
Affiliation:
Department of Physics and Electronics, Faculty of Sciences 1, Lebanese University, Beirut, Lebanon
Alaa Ghaith
Affiliation:
Department of Physics and Electronics, Faculty of Sciences 1, Lebanese University, Beirut, Lebanon
*
Author for correspondence: Ali Siblini, E-mail: ali.siblini.84@hotmail.com
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Abstract

In this paper, an algorithm for extracting and localizing a radar pulse in a noisy environment is described. The algorithm combines two powerful tools: wavelet denoising and the short-time Fourier transform (STFT) analysis with statistical-based threshold. We aim to detect radar pulses transmitted by any radar in blind mode regardless of the intra-pulse modulation and parametric features. The use of the proposed technique makes the detection and localization of radar pulses possible under very low signal-to-noise ratio conditions (−18 dB), which leads to a reduction of the required signal power or alternatively extends the detection range of radar systems. Radar classes pattern-based analysis is used in blind mode to decrease the probability of false alarm.

Keywords

EMI (electromagnetic interference)HOS (higher order statistics)LFM (linear frequency modulation)PRF (pulse repetition frequency)PSD (power spectral density)PW (pulse width)RMSE (root mean square error)STFT (short-time Fourier transform)WPD (wavelet packet decomposition)WT (wavelet transform)
Type
Radar
Information
International Journal of Microwave and Wireless Technologies , Volume 12 , Special Issue 8: Special Issue EuMW 2019. Part II , October 2020 , pp. 782 - 789
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Copyright
Copyright © Cambridge University Press and the European Microwave Association 2020

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