A Scale Distillation Method for Multi-Source Target Recognition in SAR Imagery

In recent years, the rapid development of synthetic aperture radar (SAR) technology has enabled researchers to obtain SAR targets from multiple sources within the same class. However, most existing SAR target recognition methods are designed for single-source target recognition. When applied to multi-source target recognition in SAR imagery, the different data distributions from various sources can negatively impact recognition accuracy. To address this issue, this paper proposes a scale distillation method for multi-source target recognition in SAR imagery. This approach involves extracting feature representations of the target, incorporating multi-scale semantic information through the multi-scale feature fusion mechanism (MSFFM), and performing knowledge distillation on the output scale features to enhance discriminative knowledge about the target scales. Experimental results on the FUSAR-Ship and OpenSARShip datasets from different sources demonstrate an average improvement in classification accuracy by 2.5% after applying scale distillation, which is a significant advantage over other methods.