大规模GNSS观测数据一体化预处理系统设计与实现

Design and Implementation of an Integrated Preprocessing System for Large-Scale GNSS Observations

摘要:

针对全球GNSS观测数据规模持续增长及多源数据管理、质量控制和自动化处理的迫切需求，设计并实现了一种面向大规模GNSS观测数据的一体化预处理系统；该系统采用模块化分层架构，集成格式转换、数据编辑、质量检查、单点定位、结果可视化及报告生成等功能，具有功能完备性、结果可靠性、输出多样性、高度自动化和高效并行化等显著技术特征；基于135个基站的观测数据进行性能测试，结果表明：在六核十二线程的硬件环境下，该系统可将数据处理耗时由98分钟缩短至约17分钟，效率提升约576.5%，当并行度设置接近CPU物理核心数时可获得最佳性能；该系统有效降低了大规模GNSS数据预处理的技术门槛，显著提升了处理效率和可靠性，为GNSS精密定位、误差建模及气象反演等应用提供了高效的数据支撑。

Abstract:

In response to the rapid growth of global GNSS observation data and the urgent demand for multi-source data management, quality control, and automated processing, an integrated preprocessing system for large-scale GNSS observation data has been designed and implemented. The system adopts a modular layered architecture and integrates functionalities including format conversion, data editing, quality checking, single-point positioning, result visualization, and report generation. It is characterized by comprehensive functionality, reliable results, diverse outputs, high automation, and efficient parallelization. A performance test based on observation data from 135 reference stations shows that, in a six-core twelve-thread computing environment, the system reduces the data processing time from 98 minutes to approximately 17 minutes, achieving a 576.5% efficiency improvement; optimal performance is obtained when the parallelism level is close to the number of physical CPU cores. This system effectively lowers the technical barrier of large-scale GNSS data preprocessing, significantly enhances processing efficiency and reliability, and provides strong data support for applications such as GNSS precise positioning, error modeling, and atmospheric inversion.