In order to solve the problems of insufficient objective evaluation and lack of evaluation basis for the classification and identification of radar emitter signal， an improved gray correlation feature evaluation model combined with interval-valued intuitionistic fuzzy thought is constructed. The model introduces the dimension of signal-to-noise ratio （SNR） to examine the dynamic differences of data at different levels， describes feature information with interval data， and establishes an interval-valued intuitionistic fuzzy comprehensive decision matrix. Secondly， an optimization model that maximizes the total deviation between features is used to determine the weight of each indicator. Finally， based on the improved gray correlation framework， the ranking of feature schemes is achieved by combining with the approach to ideal points. The simulation results show that the proposed method can give the sorting identification feature evaluation and sorting results that are consistent with the actual situation， and is basically consistent with the analysis results by the unimproved gray correlation method， which verifies the feasibility and effectiveness of the proposed method.