## 1 Introduction
The processor consists of a LEON2 FT anti-irradiation processing chip, an FFTC ASIC chip and a Synchronous Dynamic Random-Access Memory (SDRAM) structure designed by EDAC that can complete 1K\(\times\)1K granularity SAR imaging processing, which will be applied to the ESA EASCOREFH2O mission, the BIOMASS mission and the panelSAR satellite. In 2016, the California Institute of Technology (CIT) completed an Unmanned Aerial Vehicle (UAV) SAR real-time processing system using a single Xilinx Virtex-5 space-grade Field-Programmable Gate Array (FPGA) chip [18]. The system is the first that applies space-grade FPGA to SAR real-time signal processing. It provides a basis for the use of space-grade FPGA in spaceborne SAR on-board real-time processing scenarios. SpaceCube is a series of space processors developed by NASA in the United States. SpaceCube established a hybrid processing approach combining radiation-hardened and commercial components while emphasizing a novel architecture harmonizing the best capabilities of Central Processing Unit (CPU), Digital Signal Processor (DSP) and FPGA [19]. The latest SpaceCube v3.0 processing board launched in 2019 is equipped with Xilinx Kintex UltraScale, Xilinx Zynq MPSoC, Double-Data-Rate Three Synchronous Dynamic Random-Access Memory (DDR3 SDRAM) and NAND Flash chips, which can complete on-board real-time data processing missions, and provide a processing solution for next-generation needs in both science and defense missions [20]. In 2020, NASA's Goddard Space Flight Center developed a prototype design for the NASA SpaceCube intelligent multi-purpose system (IMPS) to serve high-performance processing needs related to artificial intelligence (AI), on-board science data processing, communication and navigation, and cyber security applications [21,22]. As indicated by the development of spaceborne SAR real-time processing technology, a high-performance on-board real-time processing platform needs to be equipped with processors and memories that meet many restrictions regarding power, performance and capacity constraints. CPU, DSP, FPGA, Graphics Processing Unit (GPU) and Application Specific Integrated Circuit (ASIC) are superior, to some extent, when it comes to real-time processing. Although CPU and DSP have strong design flexibility, they cannot provide enough computing resources, and there will be bottlenecks in massive data processing. GPU has strong processing capabilities, but has high power consumption and is not suitable for on-board scenarios. ASIC is a device that can be customized and has sufficient processing power, but the development time is long. FPGA has irreplaceable advantages in terms of on-chip resource storage, computing capabilities, reconfigurable characteristics, and can meet the requirements of large throughput and real-time processing under space-borne conditions [23; 24]. The on-chip storage resources of the above-mentioned processors are very limited, which cannot meet the requirements for massive data processing in the SAR algorithm. Taking Stripmap SAR imaging of 16,384 \(\times\) 16,384 granularity raw data (5 m resolution) as an example, the required data storage space is up to 2 GB [25]. Therefore, a high-speed, large-capacity external memory must be selected as the storage medium for SAR data. Hard Disk Drives (HDDs) have a higher storage capacity, but their stability is limited. Solid State Drives (SSDs) have strong stability, but a shorter lifetime. Flash memory is a non-volatile form of memory that can store data for a long time, but it has low data transmission efficiency and high power consumption. DDR3 SDRAM is a new type of memory chip developed on the basis of SDRAM chips [26]. It has double data transmission rate and meets the requirements of on-board processing in terms of capacity, speed, volume, and power consumption [27; 28; 29]. In summary, FPGA and DDR3 SDRAM are ideal processor and memory formats for on-board data processing.