面向星载SAR在轨解译的数字孪生建模与处理

Digital twin modeling and processing for on-orbit interpretation of satellite-based SAR

近年来,星载合成孔径雷达(synthetic aperture radar, SAR)成像和SAR图像处理已广泛应用在遥感图像领域的各个方面。SAR通常将接收到的回波数据传回地面系统进行处理,这导致当前星载SAR系统存在星地数据传输压力大、系统实时响应能力差等问题,因此将星载SAR成像和图像处理两大任务部署在SAR卫星上进行在轨解译成为新的解决方案。但SAR卫星上的载荷空间资源有限,难以搭载完成星载SAR成像和图像处理任务所需要的高性能计算设备,同时SAR卫星的制造成本高、研发风险大,需要在发射前对其进行验证。为解决上述问题,结合数字孪生技术设计了一种面向星载SAR在轨解译的数字孪生系统。在该系统中,首先构建了用于获取星载SAR回波数据及卫星几何信息的数据采集模型;其次,设计了用于模拟星载SAR在轨解译的数据处理模型及数据应用模型,为了适应星上资源有限的环境,对在轨解译进行了并行计算优化和轻量化处理;最后,搭建了一套由低功耗设备组成的系统硬件平台用于模拟资源有限的卫星环境。在多种场景目标下对该数字孪生系统进行实验,实验结果表明所设计数字孪生系统可以有效地模拟星载SAR在轨解译全流程,能为实际中的星载SAR在轨解译和功能验证提供合适的系统平台。

In recent years, satellite-based synthetic aperture radar(SAR) imaging and SAR image processing have been widely used in various aspects of remote sensing imagery. SAR usually transmits the received echo data back to the ground system for processing, which leads to current satellite-based SAR system having problems such as high pressure on the transmission of star to ground data and poor real-time response capability of the system. Therefore, deploying the two main tasks of satellite-based SAR imaging and image processing on SAR satellites for on-orbit interpretation has become a new solution. However, the load space resources on SAR satellites are limited, and it is difficult to carry the high-performance computing equipment required to complete the satellite-borne SAR imaging and image processing tasks. Furthermore, it is necessary to validate them before launch because of the high manufacturing cost and high development risk. In order to solve the above problems, we have designed a digital twin system for on-orbit interpretation of satellite-based SAR by combining digital twin technology. In this system, we first construct a data acquisition model for obtaining on-board SAR echo data and satellite geometric information. Secondly, we design a data processing model and a data application model for simulating on-board SAR in-orbit interpretation. In addition, the parallel computation and lightweight processing for in-orbit interpretation are optimized in order to adapt to the environment of limited resources on the star. Finally, we construct a set of systems consisting of low-power devices for simulating the resource-limited satellite environment. The digital twin system was tested in a variety of scenarios, and the experimental results show that it can effectively simulate the whole process of on-board SAR in-orbit decoding, and can provide a suitable system platform for function verification in practice.