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At present, the main problem facing various types of infrared imaging guided missiles is the strength of anti-jamming capabilities, including natural environmental interference and artificial interference. Therefore, the anti-jamming performance of the infrared seeker has become the key performance of various infrared guided missiles, which greatly affects the combat performance of the missile. In order to reasonably evaluate the anti-jamming performance of the infrared imaging seeker, it is necessary to formulate a reasonable evaluation index for the anti-jamming performance of the infrared imaging seeker; for this reason, the author based on the anti-jamming work process and characteristics of the infrared imaging seeker, As well as traditional evaluation indicators, and drawing on the evaluation indicators of deep learning, an anti-jamming performance evaluation index system composed of four aspects: interception ability, recognition ability, tracking ability and hit accuracy ability is proposed; the second level under the four indicators is clarified Index connotation and calculation method. According to the results of infrared simulation and data processing, these four evaluation indexes can effectively reflect the anti-jamming performance of the seeker, and the two indexes of recognition ability and hit accuracy are more prominent. The anti-jamming performance index system and calculation method of the infrared imaging seeker proposed by the author can be used as the basis for evaluating the anti-jamming performance of infrared imaging guided missiles.