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For the existing support vector machine,when recognizing more questions,the shortcomings of high computational complexity and low recognition rate under the low SNR are emerged.The characteristic parameter of the signal is extracted and optimized by using a clustering algorithm,support vector machine is trained by grading algorithm so as to enhance the rate of convergence,improve the performance of recognition under the low SNR and realize modulation recognition of the signal based on the modulation system of the constellation diagram in this paper.Simulation results show that the average recognition rate based on this algorithm is enhanced over 30％ compared with methods that adopting clustering algorithm or support vector machine respectively under the low SNR.The average recognition rate can reach 90％ when the SNR is 5 dB,and the method is easy to be achieved so that it has broad application prospect in the modulating recognition.