An efficient SAR ATR approach

Automatic target recognition (ATR) based on synthetic aperture radar (SAR) imagery (denoted as SAR ATR for simplicity) is very important for battlefield awareness. Since SAR images are very sensitive to pose variation of targets, SAR ATR is a well-known very challenging problem. An efficient SAR ATR algorithm is given, which uses KFD (kernel Fisher discriminant) as feature extractor and linear SVM (support vector machine) as classifier. Experimental results evaluated with the MSTAR (moving and stationary target automatic recognition) public data sets provided by the DARPA/AFRL (Defence Advanced Research Project Agency/Air Force Research Laboratory) show that the proposed scheme performs much better than the conventional template matching and SVM methods, especially when the target pose uncertainty is large, which is desirable for SAR ATR.