UWB weak signal detection and recovery algorithm based on power spectrum entropy and improved stochastic resonance

In electromagnetic spectrum monitoring, Ultra-Wideband (UWB) signals, as a kind of low interception rate communication signal, are easy to bring great security risks. UWB signals are easy to be submerged in the background noise and difficult to detect. Therefore, this paper proposes an UWB signal detection and recovery algorithm based on power spectrum entropy and improved stochastic resonance for the above problems. Firstly, the power spectrum entropy algorithm was used to detect the existence of the signal. After confirming the existence of the signal, the adaptive piecewise stochastic resonance system was used to recover the detected signal waveform. On the basis of stochastic resonance processing, the Variational Mode Decomposition (VMD) algorithm combined with wavelet transform is used to further filter the signal noise and improve the recovery degree of the signal waveform. The simulation results show that the proposed algorithm can effectively recovery the UWB signal, and the recovery degree is better than the traditional bistable stochastic resonance model. The measured experiment verifies the effectiveness of the proposed algorithm.