Part absence is a difficult problem in Synthetic Aperture Radar (SAR)Automatic Target Recognition. However

such problem can be resolved to some extent by detecting the single scattering part of the target in the measured SAR data. This study proposes a matched filter-based approach to detect single scattering part on the basis of the part-level 3-D scattering model of the target;this approach can well predict the scattering properties of the whole target and the single scattering part comprising the target. The following steps are used in applying the matched filter approach in detecting single scattering part:First

a matched filter is built according to the image of the single scattering part predicted by the scattering model. Second

the matched filter slides in the 3-D parameter domain detects the best position of the scattering part that is appropriate for the measured SAR image and determines the maximum correlation coefficientto enhance detection precision. Moreover

in terms of the imprecision of azimuth estimation

the premiumposition is explored in the neighborhood to obtain the best result. According to the intensity of all visible scattering parts under the present position

the strongest to the weakest parts are detected sequentially. The interference from the neighboring scattering part disturbs the detection of the present scattering part. The CLEAN algorithm is employed to overcome this problem and to eliminate the interference of the other scattering parts. A part-level 3-D scattering model of a simple tank is used in this study. Experiments are conducted on the basis of electromagnetically simulated data

dark-room measured data of the simple tank

and MSTAR (moving and stationary target acquisition and recognition) data

which are used as interference. Results demonstrate that the proposed method can detect existing scattering parts in the measured image

as well as find the absent parts. In addition

interfering data can be excluded from the experiments. This study proposes a single scattering part detection method for SAR target. Experiment results confirm the efficiency of the method.