A Takagi-Sugeno (T-S) Target Recognition Algorithm Based on Global Intuitionistic Fuzzy Method (TS-GIFM) is presented to enhance the recognition of aerial targets in complex environments. In this paper, to realize the effectiveness of the model’s training process, we categorize the distinctive features of aerial targets as inputs for the intuitionistic T-S target recognition model. Then, the intuitionistic fuzzy theory and the ridge regression are employed in the consequent parameter identification to construct a robust regression system. Additionally, global intuitionistic fuzzy C-regression clustering is implemented to obtain the premise parameters and mitigate the influence of non-informative data items. Finally, experimental results demonstrate that TS-GIFM effectively recognizes typical aerial targets in aerial target recognition environments, outperforming other methods in aerial target recognition.