<FONT face=Verdana>The feature extraction is one of the key steps and difficulties for Synthetic Aperture Radar(SAR) Auto Target Recognition. This paper proposes a novel method based on Non-negative Matrix Factorization for SAR images feature extraction and target recognition. In order to make full use of local spatial structure information for target feature extraction to achieve target recognition

it takes the form of non-negative weighted combination of basis vectors to construct SAR target images. First

the level set SAR image segmentation method is adopted to get the target image from noisy SAR image

then

after non-negative matrix factorization

the resulting weighted vectors are regarded as the feature vectors of the target images

and finally

Fisher Linear Discriminant is considered as a classifier to perform target recognition. The method is used for recognizing three-type target motels in MSTAR database. Compared to other classical methods

the experimental results show that the new method is an effective approach for SAR images feature extraction and target recognition.