Fuzzy Inference Based Multi Feature Fusion Approach for Radar Target Detection

This paper presents a hybrid radar target prediction method combining Synthetic Aperture Radar (SAR), Inverse Synthetic Aperture Radar (ISAR), and fuzzy logic for improved detection accuracy. SAR/ISAR imaging provides key features such as range, Doppler, and radar cross-section (RCS), while the fuzzy inference system effectively handles signal uncertainties through multi-feature fusion. Experimental results show strong agreement between theoretical and real-time area estimates, with an MAE of 266.0 and an MPE of 2.22%. Errors are lowest at mid-range distances (2000 m) and highest at shorter ranges (200 m). The fuzzy-based approach reduces measurement deviations and enhances detection reliability under noisy and cluttered conditions, making it highly suitable for real-time radar applications.