The detection and recognition of radar signals play a critical role in the maintenance of future electronic warfare (EW).So far,however,there are still problems with signal detection and recognition,especially in the low probability of intercept(LPI) radar.This paper explores the usefulness of such an al-gorithm in the scenario of LPI radar signal detection and recog-nition based on visibility graphs (VG).More network and feature information can be extracted in the VG two-dimensional space,this algorithm can solve the problem of signal recognition using the autocorrelation function.Wavelet denoising processing is in-troduced into the signal to be tested,and the denoised signal is converted to the VG domain.Then,the signal detection is per-formed by using the constant false alarm of the VG average de-gree.Next,weight the converted graph.Finally,perform feature extraction on the weighted image,and use the feature to com-plete the recognition.It is testified that the proposed algorithm offers significant improvements,such as robustness to noise,and the detection and recognition accuracy,over the recent re-searches.