基于多节点协同的大规模星载SAR处理系统设计
Design of Large-Scale Spaceborne SAR Processing System Based on Multi-Node Collaboration
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摘要: 星载合成孔径雷达(Synthetic Aperture Radar,SAR)在轨处理技术对提升遥感应用效率至关重要,能解决传统模式下星地数传带宽瓶颈和数据处理延迟问题,在军事侦察、灾害应急监测等领域意义重大。然而,现有在轨处理硬件系统在功能覆盖和处理复杂任务能力方面存在不足,大多针对单个处理环节或简单任务进行研究,无法满足复杂星载任务需求。本文设计了一种大规模星载SAR处理系统,以应对这些挑战。该系统支持数据预处理、SAR成像、舰船检测、重聚焦、目标识别、几何矫正等多种操作,具备广域舰船检测和广域舰船识别两种复杂功能。通过提出基于多节点协同重构的星载SAR多任务兼容方法,详细设计了系统硬件方案,包括交互主控板、检测板、成像板、识别板等硬件板卡。交互主控板负责数据输入、预处理和分发;检测板实现目标检测、重聚焦等功能;成像板利用专用片上系统(System on Chip,SoC)芯片进行高速SAR成像;识别板完成虚警剔除和目标识别。同时,针对广域舰船检测和识别功能,分别设计了相应的数据流和流水线。在广域舰船检测中,数据经预处理后分发至各板卡,成像后进行目标检测、虚警剔除、动目标定位和几何矫正;广域舰船识别在检测基础上增加重聚焦环节,以实现精准识别。实验采用模拟信号源仿真星载SAR回波数据,对系统功能和性能进行验证。结果显示,SAR 成像功能的分辨率、峰值旁瓣比和积分旁瓣比均满足要求,目标检测发现率达93.7%,虚警密度为2.96个/万平方公里。在处理时效性方面,广域舰船检测和识别任务分别达到1∶2和1∶2.5准实时处理水平。综上,该系统处理质量良好,成像速度出色,为星载 SAR 大规模在轨处理技术发展提供了借鉴。Abstract: The onboard processing technology of spaceborne Synthetic Aperture Radar (SAR) is essential for enhancing the efficiency of remote sensing applications. It provides a critical solution to the bottleneck in space-to-ground data transmission bandwidth and addresses delays associated with data processing in traditional models. This technology plays a vital role in various domains, particularly in military reconnaissance, where it enables the acquisition of high-resolution imagery for intelligence gathering, and in disaster emergency monitoring, where it allows for the timely detection and assessment of disasters. However, current onboard processing hardware systems exhibit significant limitations in terms of functional coverage and their ability to handle complex tasks. Most existing research focuses on individual processing steps or relatively simple tasks, making it difficult to adequately meet the demands of modern spaceborne missions. These missions often require the integration of multiple functions and high-performance processing capabilities that current systems cannot provide. To overcome these limitations, this paper presents the design of a large-scale onboard processing system for spaceborne SAR. The proposed system supports a variety of operations, including data preprocessing, SAR imaging, ship detection, refocusing, target recognition, and geometric correction. Of particular note are two advanced capabilities: wide-area ship detection and recognition. A multi-task compatible approach based on multi-node collaborative reconstruction underpins the system’s design. This method informs the development of a detailed hardware architecture comprising several dedicated processing boards. The interactive master control board manages data input, preprocessing, and distribution, serving as the central hub for system-wide data flow. The detection board is responsible for target detection and refocusing tasks, aiming to accurately identify and re-image blurred moving targets. The imaging board, equipped with dedicated System-on-Chip (SoC) chips, performs high-speed SAR imaging to ensure the production of high-quality, high-resolution images. The recognition board handles false alarm rejection and target recognition, providing classification information for detected objects. Specialized data flow and pipeline designs have been developed to support wide-area ship detection and recognition functions. In the wide-area ship detection process, preprocessed data is distributed to the appropriate boards, followed by SAR imaging, target detection, false alarm rejection, moving target localization, and geometric correction. For wide-area ship recognition, the process includes additional steps, refocusing and recognition, after detection to enable precise identification. The system’s functionality and performance were verified through a series of experiments using a simulated signal source to generate spaceborne SAR echo data. The experimental results demonstrate that the SAR imaging function meets the required standards in terms of resolution, peak sidelobe ratio (PSLR), and integrated sidelobe ratio (ISLR). The system achieves a target detection rate of 93.7%, with a false alarm density of 2.96 per 10000 square kilometers. In terms of processing efficiency, the wide-area ship detection function reaches a 1∶2 near-real-time processing level, whereas the wide-area ship recognition function achieves a 1∶2.5 near-real-time level. In conclusion, the proposed system exhibits excellent processing quality and impressive imaging speed, offering a valuable reference for the future development of large-scale onboard processing technologies for spaceborne SAR applications.