The integration of sensing and communication (ISAC) has significant potential for future wireless systems, enabling efficient spectrum utilization and novel application scenarios. In this paper, we propose a cooperative ISAC framework for synthetic aperture radar (SAR) imaging by leveraging orthogonal frequency division multiplexing (OFDM) communication signals. We address the challenge of severe imaging degradation in non-line-of-sight (NLOS) environments under the QUAsi Deterministic RadIo channel GenerAtor (QuaDRiGa). To detect weak signals and eliminate false points, we develop a two-stage compressed sensing-space alternating generalized expectation maximization (CS-SAGE) scheme for high-precision scatterer localization. In stage I, orthogonal matching pursuit (OMP) is employed for coarse estimation to identify the approximate locations of dominant scatterers. Then, the SAGE algorithm in stage II performs fine estimation to accurately extract scatterer parameters. Simulation results validate the effectiveness of the proposed cooperative ISAC framework, and provide valuable insights for practical system design.