Experimental Verification of a Parallel Compressive Sensing Based Back-Projection Algorithm for Bistatic SAR Imaging

Bistatic SAR, characterized by the separation of the transmitter and receiver, requires solutions to various technical challenges such as synchronization precision, reduced received signal power, and degraded range resolution. Owing to the complexity of the geometric alignment between the transmitter and receiver, the Back-Projection Algorithm (BPA) is advantageous for obtaining high-quality images. In this study, bistatic data were acquired using an FMCW radar with wirelessly shared local oscillator (LO) signals, and the monostatic and bistatic SAR images were compared and analyzed. Additionally, although compressive sensing enables high-resolution imaging with fewer samples, even under data loss conditions, it introduces the challenge of exponentially increasing the computation time. To address this, we propose a parallel BPA-CS algorithm that significantly improves computational speed by adjusting block sizes while maintaining image performance indicators, such as PSNR. This approach highlights the practical applicability of radar-imaging technologies that require high resolution and data efficiency, thereby providing a novel method for enhancing the utility of bistatic SAR.