Most commonly used frequencies in Synthetic Aperture Radar (SAR) imaging are from hundreds of MHz to tens of GHz. Nowadays, the unexplored mmWave and THz regimes are being investigated for SAR imaging to have higher resolution. Two research challenges for this technology motion compensation and real-time processing are addressed in this paper. SAR image reconstruction algorithms lack data dependencies. Therefore, it can be processed in a parallel computing environment to accelerate the image reconstruction. This paper presents the theoretical model of a distributed signal processing testbed. The performance enhancement with the inclusion of high performance computing for image processing is also explained. Another challenge for this technology comes from a motion compensation point of view. The SAR signal processing assumption is that the radar-carrying platform follows an ideal path. However, in reality, the platform deviates from this path. Especially at THz, very small deviations in the range of sub-mm produce motion errors because of wavelengths in the range of deviations. It degrades the image quality and provides wrong estimations of range and azimuth scatters. The paper summarizes motion error types, their characterization, and constraint on the amplitude of deviation. Also, the paper presents effects of these errors at 100 GHz with simulation results.