A jamming recognition method based on gray-level co-occurrence matrix is proposed for discriminating micro-motion jamming patterns including modulation and repeater micro-motion jamming from micro-motion scatter-wave jamming and pulse convolution micromotion jamming. Firstly, from the perspective of image domain, the received radar signal matrix is grayed. Then, the texture parameters are extracted by using the graylevel cooccurrence matrix to construct feature parame ters. Finally, KNearest Neighbor (KNN) classifier is adopted to test the jamming recognition rate. The simulation results show that the recognition method can effectively classify and recognize target echo without jamming and three kinds of micromotion jamming patterns under condition of noisy environment. When the signaltonoise ratio is -5 dB, the overall recognition rate is over 98%. When the signaltonoise ratio is -5 dB, the recognition rate of four kinds of signal is over 90% under different jammertosignal ratios, and the overall recognition rate of each kind of signal is over 98%. When the signal-to-noise ratio is 5 dB, the recognition rate of four kinds of signal is over 95% under different jammer-to-signal ratios, and the overall recognition rate of each kind of signal is over 99%.