中图分类号：TP391 文献标志码：A DOI: 10.16157/j.issn.0258-7998.257658
中文引用格式： 王显，路瑶，高嘉轩. 基于高级综合约束的航天器星敏感器图像加固方法研究[J]. 电子技术应用，2026，52(7)：133-141.
英文引用格式： Wang Xian，Lu Yao，Gao Jiaxuan. Research on image reinforcement method for star sensor based on high-level synthesis constraints[J]. Application of Electronic Technique，2026，52(7)：133-141.

Research on image reinforcement method for star sensor based on high-level synthesis constraints

Abstract： Spacecraft star sensor image processing is a crucial component of Field Programmable Gate Array(FPGA) payload missions. This functionality significantly reduces the data transmission requirements of the payload, accelerates decision-making speed, and enhances the processing capability of the payload unit. Star sensor algorithms (e.g., star extraction, star pattern recognition, and attitude determination) play a vital role in improving the efficiency and real-time performance of on-board FPGA image processing. However, star sensor algorithms involve a large number of parameters and complex computational processes, consuming substantial storage and FPGA hardware resources. Traditional triple modular redundancy (TMR) reinforcement tools offer limited support for on-board algorithm modules, lack focus on critical aspects, and result in high resource consumption and significant performance degradation, making them inadequate for current mission requirements. This paper proposes an FPGA reinforcement technique for star sensor images based on high-level synthesis (HLS) constraints. HLS constraints enable system-level functional reinforcement of FPGAs, allowing for targeted reinforcement design based on the criticality of system and algorithm principles. This approach effectively reduces both the time and resource costs associated with reinforcing logically complex FPGAs.

Key words : start sensor；FPGA；high-level synthesis constraints