High-resolution inverse synthetic aperture radar （ISAR） images play a crucial role in target recognition. However， obtaining high-resolution ISAR images requires prolonged radar exposure， which does not meet the demands of radar resource scheduling. In this paper， we propose a recognition method that guides radar image feature fusion based on incidence angles. A portion of pulse accumulation imaging during the dwell time is selected to meet the temporal adjustments and allocations of the remaining radar functions. Considering the differences in modulation phenomena among images of different aircraft models and the modulation variations of the same model at different incident angles， a hybrid attention residual module and angle-guided attention module are designed to focus the network on critical areas of the image and correlate target features with target attitudes. A feature fusion module is employed to integrate image features for fusion recognition. Through practical data of three types of aircraft， we demonstrate that this method achieves higher recognition accuracy while satisfying radar resource scheduling requirements.