遥感图像星上智能处理地面仿真模拟系统设计与实现

传统卫星遥感应用模式复杂繁长，无法满足用户越来越关注的实时化遥感服务需求，为卫星配备智能化大脑，一方面可以降低数据传输带宽，另一方面可以提高数据获取的时效性，因此，星上智能处理已经成为遥感卫星发展的必然选择。但星上处理在轨调试困难，现有遥感卫星星上处理平台的地面测试系统都是卫星实验室测试时，针对不同的卫星载荷临时组建，缺乏通用性且并未形成集成化的装置，导致现有遥感图像星上智能处理的地面测试效率偏低。尤其是面对目前星上处理智能化的新需求，缺乏一套高性能、低功耗、全流程的星上处理地面仿真系统。针对遥感数据处理自动化与智能化发展的新特点，提出了一套基于FPGA与GPU相结合的遥感图像星上处理地面仿真模拟系统。该系统能够在地面模拟实现多种载荷的0到1级数据预处理，在预处理的基础上实现智能遥感影像的加速识别，其关键难点在于遥感图像智能处理算法的高计算复杂度和嵌入式计算机有限计算力之间的平衡；遥感图像处理领域的AI专用算法固化和硬件加速之间的平衡；不同卫星平台测试需求和系统架构通用性之间的平衡。本文阐述了仿真平台设计的方法，构建了基本原型并对其进行了验证。测试结果表明：该系统可以较好地完成星上智能处理典型算法地面全流程测试，所有硬件可以直接上星组装，完备度高，对优化和指导卫星地面仿真系统运行管理体系具有一定的参考价值。

Design and Implementation of Ground Simulation System for Remote Sensing Image On-board Intelligent Processing

The traditional application mode of remote sensing satellites is complicated and complex， and unable to meet the demand for real-time remote sensing services that users are increasingly concerned about. To equip satellites with intelligent brains can reduce the data transmission bandwidth on the one hand， and improve the time-effectiveness of data acquisition on the other hand. Therefore， on-board intelligent processing has become an essential choice for the development of remote sensing satellites. However， it is difficult to debug on-board processing in orbit， and the existing ground test systems for remote sensing satellite on-board processing platforms are all formed temporarily for different satellite payloads during the satellite laboratory testing. They lack versatility and have not formed an integrated device， resulting in low efficiency of existing ground test platforms for on-board intelligent processing. Especially in the face of the new demand for intelligent on-board processing at present， there is a lack of an on-board processing ground simulation system with high performance， low power consumption and full process. Aiming at the new characteristics of automation and intelligent of remote sensing data processing development， this article proposes a set of ground simulation system for remote sensing image on-board processing based on the combination of FPGA and GPU. This system can realize the 0 to 1 level data pre-processing of multiple payloads in ground simulation and realize the accelerated recognition of intelligent remote sensing images on the basis of pre-processing. The key difficulties are as followed： the balance between the high computational complexity of remote sensing image intelligent processing algorithms and the limited computational power of embedded computers； the balance between the solidification of AI-specific algorithm and hardware acceleration in remote sensing image processing field； the balance between the testing requirements of different satellite platforms and the generality of system architecture. This article illustrates the approach of simulation platform design， builds a basic prototype and verifies it. The test results show that the system can better complete the whole ground testing process for typical algorithms of on-board intelligent processing， and all hardware can be directly assembled on-board with high completeness. It has a certain reference value for optimizing and guiding the operation management system of satellite ground simulation system.