A novel method for UWB weak signal detection based on stochastic resonance and wavelet transform

Abstract

Pulse ultra-wideband (UWB) signal is a transient pulse in time domain with very low power spectral density; In the long-distance communication, it is difficult to detect the low signal to noise ratio (SNR) pulse UWB signal submerged in strong noise. To solve the above problems, a novel adaptive stochastic resonance fusion wavelet transform method for UWB weak signal detection is proposed. Firstly, the adaptive optimization method which is based on the improved stochastic resonance potential well model is used to match the optimal parameters of the stochastic resonance (SR) system for the noisy signal, so that the noise energy can be transferred to the UWB signal and the signal amplification can be realized; Secondly, in view of the problem that SR method is insensitive to phase transient information and amplitude shift, wavelet transform is used to extract mutation information, so as to realize the accurate detection of UWB weak signal. The simulation results show that the proposed method can solve the problem that it is difficult to distinguish the change of signal state by using stochastic resonance method alone. Finally, two groups of actual signals with bandwidth of 10 MHz and 20 MHz are collected by the experimental system to test the effectiveness of the method.