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Miniature Synthetic Aperture Radar (MiniSAR) has been making breakthroughs to effectively overcome the limitations of time and space, and has exhibited superiority with respect to light weight and low- power consumption as well as high flexibility to achieve high-resolution imaging for the Region Of Interest (ROI). However, imaging signal processing for MiniSAR systems still face several technical challenges such as high-resolution imaging of ground targets under complicated trajectories, refocusing of non-cooperative moving targets, and efficient and real-time processing of echo data. In this paper, a series of imaging signal processing and associated hardware designs using Field-Programmable Gate Array (FPGA) architecture have been proposed to realize MiniSAR ultra-high-resolution imaging and real-time processing. Additionally, experimental results utilizing considerable spotlight and stripmap MiniSAR data have been presented to demonstrate the effectiveness and reliability of the proposed technology.

For real-time autofocus of defocused images produced by Synthetic Aperture Radar (SAR), the twodimensional autofocus approach proposed in this study is used to correct the residual range cell migration and compensate for the phase error. Next, a block-wise Phase Gradient Autofocus (PGA) is used to correct the space-variant phase error. The Field-Programmable Gate Array (FPGA) design procedures, resource utilization, processing speed, accuracy, and autofocus are discussed in detail. The system is able to autofocus an 8K × 8K complex image with single precision within 5.7 s when the FPGA works at 200 MHz. The processing of the measured data verifies the effectiveness and real-time capability of the proposed method.