Please refer to this work: Physics-Guided Detector for SAR Airplanes, IEEE TCSVT 2025

The detailed implementation of the proposed physics-guided detector for SAR airplanes.

The explanation results based on Grad-CAM for PGD and PGD-Lite models.

• A general physics-guided detector (PGD) learning paradigm is proposed for SAR airplane detection and fine-grained classification, aiming to address the challenges of discreteness and variability.
• PGD is consist of physics-guided self-supervised learning (PGSSL), feature enhancement (PGFE) and instance perception (PGIP).
• Extensive experiments are conducted on SAR-AIRcraft-1.0 dataset. Based on existing detectors, we construct nine PGD models for evaluation.

In our precious works, we propose a physics guided learning method for SAR airplane target feature representation, where the airplane scattering characteristics are extracted to guide the model training.

@inproceedings{wang2023new,
  title={A new Perspective on Physics Guided Learning for SAR Image Interpretation},
  author={Wang, Zishi and Huang, Zhongling and Datcu, Mihai},
  booktitle={IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium},
  pages={1926--1929},
  year={2023},
  organization={IEEE}
}

Code is based on an object detection YOLOv5. Please refer to requirements.txt for installation and dataset preparation.

The code are proposed here. We will complete the pivotal code after the paper is accepted.

The file directory tree is as below:

├── data
│   ├── SAR_AIRcraft
│   │   ├── test
|   |   |   |——images
|   |   |   |——labels
│   │   ├── train
|   |   |   |——images
|   |   |   |——labels
│   │   ├── val
|   |   |   |——images
|   |   |   |——labels
├──models
│   ├── common.py
│   ├── PGD_yolo.py
│   ├── ...
├──tools
│   ├── main_cnn.py
│   ├── utils.py
│   ├── ...

SAR-AIRcraft-1.0:https://radars.ac.cn/cn/article/doi/10.12000/JR23043

python train_PGD.py --data data/SAR_PLANE.yaml  --cfg models/hub/resnet18_RepPAN.yaml  --hyp data/hyps/hyp_SARPLANE.yaml 

python train_PGD_Lite.py --data data/SAR_PLANE.yaml  --cfg models/hub/resnet18_RepPAN.yaml  --hyp data/hyps/hyp_SARPLANE.yaml 

PGD:download(https://pan.baidu.com/s/13OMggVOiwatqLR4hWIMMvA?pwd=zjs9) PGD_Lite:download(https://pan.baidu.com/s/1Hmt5lFrfHbJRfddJWL2dUg?pwd=ithq)

If you find this repository useful for your publications, please consider citing our paper.

@article{huang2025physics,
  title={Physics-Guided Detector for SAR Airplanes},
  author={Huang, Zhongling and Liu, Long and Yang, Shuxin and Wang, Zhirui and Cheng, Gong and Han, Junwei},
  journal={IEEE Transactions on Circuits and Systems for Video Technology},
  year={2025},
  publisher={IEEE}
}