TWR signals de-noising by using WNN

The de-noising issue of through-the-wall radar (TWR) signal is an essential TWR´s performance on detecting lives. This paper introduces TWR signal de-noising algorithm based on a wavelet neural networks (WNN). WNN owns the property of time-frequency localization of wavelet transform, as well as the excellent characteristics of artificial neural networks, self-learning and fault-tolerance, which make it a powerful tool for removing noises from noisy through-the-wall radar signals. Experimental results show that the proposed WNN based de-noising algorithm can achieve good de-noising performance and hold the useful detail of TWR signals.