Three-dimensional (3-D) synthetic aperture radar (SAR) near-field imaging provides a novel radar cross section (RCS) measurement method, which has been widely concerned in the microwave field. However, the accuracy of RCS measurement based on image is easily affected by sidelobes of matching filtering (MF) imaging and background clutter. Although the existing observation-matrix-based sparse SAR imaging algorithm can suppress sidelobes and clutter, it requires huge computational cost. To solve the above problems, an RCS measurement method using sparse imaging based 3-D SAR complex image is proposed. First, 3-D sparse imaging based complex image is used to suppress sidelobe and clutter of MF image. After that, the far-field RCS of the target is obtained by the compensation factor. Compared with the observation-matrix-based sparse SAR imaging algorithm, the proposed algorithm can reduce the computation time while retain the phase information of scene distribution. Compared with the RCS measurement based on MF image, the RCS measurement performance of the proposed method is improved. The simulation and real data of the system results validate the proposed method.