This is a novel unknown sar target identification method based on feature extraction networks and KLD-RPA joint discrimination. Experiment results form MSTAR dataset shows that our proposed Fea-DA achieves state of the art unknown sar target identification accuracy while maintaining the high recognition accuracy of known target.

python 3.7, pytorch 1.6

 implement the data2mat.py to transform the original images into .mat type.

 using the trian_FEN.py to trian the dataset, then use test_FEN.py to test, save the target features.

launch KLD-RPA.py, this is an unknown sar target joint discrimination scheme to realize high accuracy identification of unknown sar target.

if this project could provide any help to you, please cite our paper：

Zeng, Z.; Sun, J.; Xu, C.; Wang, H. Unknown SAR Target Identification Method Based on Feature Extraction Network and KLD–RPA Joint Discrimination. Remote Sens. 2021, 13, 2901. https://doi.org/10.3390/rs13152901 .

thank you.

Zhiqiang Zeng
[email protected]