Automatic target recognition of MSTAR SAR images based on sliding window weighted Zernike features

SAR images aspect sensitivity and speckle noise have a significant influence on SAR image target recognition effect. On this basis, a novel automatic target recognition method based on moving and stationary targets acquisition and recognition synthetic aperture radar(MSTAR SAR) images is proposed. At first, the target and the shadow were obtained from speckle noise by using delaunay tringulation and Growcut algorithm. Then, Zernike moments were calculated via Zernike transform, and sliding window weighted Zernike(SWWZ) moments as the feature invariants were extracted. Finally, the recognition results were obtained through utilizing the nearest neighbor criterion. The simulation results show that SWWZ moments as the feature invariants overcome the SAR aspect sensitivity and improve the recognition rate effectively, and also the proposed approach to MSTAR SAR images recognition is effective and robust.