To realize the recognition of intermittent sampling repeater jamming,an algorithm for fusing multi-domain recognition results is proposed.Firstly,the internal differences between four kinds of signals,namely,the echo of real targets and the interference of intermittent sampling (including ISDJ,ISRJ and ISLJ) are analyzed in time domain,frequency domain and fractional domain,and a Singular Spectrum Analysis (SSA) is conducted for each domain.The results of SSA can be taken as a basis for distinguishing signal differences.Secondly,three base classifiers of time domain,frequency domain and fractional domain are constructed,and the kurtosis and skewness of the singular spectrum are extracted and taken as the characteristic factors of the base classifiers for training and verification.Finally,posterior probability and local credibility are combined to construct the Basic Probability Assignment (BPA) function,and a DS fusion decision is made for the recognition results of each base classifiers.The simulation results show that the fusion method can balance the recognition results of each base classifiers.When the SNR is 0 dB and the JSR is greater than 5 dB,the average recognition rate is over 95%.