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

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.

Scheme design of the optimal background clutter suppression for impulse radio ultrawide band radar in complex fire environment: a simulation and experimental study

“…37 The wavelet transform denoising method has advantages over traditional Fourier transforms for accurately deconstructing and reconstructing finite, non-periodic, and non-stationary signals such as radar echo signals. 38 When processing noisy signal using WT, decompose, apply threshold, and signal regeneration are the three steps that must be performed , 39 and 40 gives the implementation steps.…”