Deep learning technology has been widely used in signal recognition by virtue of its powerful feature extraction capability,which brings great threat to the confidentiality security of wireless communication systems with confidentiality needs.To address the above problems,this paper proposes a wireless communication signals anti- reconnaissance method based on generating adversarial examples with adversarial networks(AdvGAN).Firstly,two different modulated signal recognition models are realized.Then three antagonistic sample generation methods are used to construct camouflage signals.Finally,they are superimposed on the original signals and tested on the modulated signal recognition model.The experimental results show that the method proposed in this paper can make the recognition accuracy of the intelligent modulation recognition model of the reconnaissance side drop dramatically,and make the recognition accuracy of the unknown model of the reconnaissance side drop by about 66%under the condition of SNR is 10 dB,so as to effectively counteract the intelligent recognition model of the reconnaissance side.