Research on Source Packet Data Splicing and Sorting Strategy for ASO-S Satellite

doi:10.19678/j.issn.1000-3428.0068497

Abstract

Abstract:

Source packet data sorting is a key step in processing scientific satellite ground segment data. Typically, sorting methods load all relevant information from a source package to be sorted into memory; this process consumes more memory resources and requires a longer execution time when dealing with large amounts of downstream data. When splicing the downstream data multiple times, the data volume increases exponentially. In addition, widely used sorting methods are not sufficiently comprehensive to handle abnormal data, which may result in some source packages being sorted incorrectly, thereby affecting subsequent data analysis. This paper presents a new source packet data splicing and sorting strategy for the Advanced Space-based Solar Observatory (ASO-S). This strategy deals with different types of anomalies while sorting source packet indexes for single downlink data and the splicing and sorting of source packet indexes for multiple downlink data. An index information fragment segmentation and reordering algorithm is also designed to reduce the amount of data required for source packet reordering and deduplication after the splicing of multiple downlink data. On multiple sets of experimental data, the strategy achieves 100% accuracy in source packet sorting when handling abnormal data such as timecode jumps. It also reduces memory resource usage and execution time during multiple downlink data splicing processes, effectively improving the accuracy of source packet sorting and data processing efficiency, laying a good foundation for the ASO-S satellite to produce high-quality scientific data products.

Key words: satellite data preprocessing, multiple downlink data splicing, source packet sorting, Advanced Space-based Solar Observatory(ASO-S), single downlink

摘要：

源包数据排序是科学卫星地面段数据处理的关键步骤。常用的排序方法将待排序的源包相关信息全部加载到内存, 在处理大体量的下行数据时占用内存资源多、执行时间较长, 在多次下行数据拼接时数据量会成倍数增长。此外, 常用的排序方法对异常数据的处理不够全面, 可能导致部分源包排序错误, 进而影响后续的数据分析。针对先进天基太阳天文台(ASO-S)提出了一种新的源包数据拼接与排序策略。该策略在单次下行数据的源包索引排序和多次下行数据的源包索引拼接与排序的处理过程中, 对不同类型异常做出了相应的处理, 并设计了索引信息片段切割再排序算法, 减少多次下行数据拼接后源包重排序、去重计算的数据量。使用多组实验数据对该策略进行了验证与测试, 实验结果表明, 该策略在对时间码跳变等异常数据的处理上源包排序准确率达到100%, 在对多次下行数据拼接处理时减少了内存资源的占用率, 缩短了执行时间, 能够有效提升源包排序的准确率和数据处理效率, 为ASO-S卫星产出高质量科学数据产品奠定了良好基础。

关键词: 卫星数据预处理, 多次下行数据拼接, 源包排序, 先进天基太阳天文台, 单次下行

PEI Xin, TONG Jizhou, MA Fuli, YU Qinsi, YANG Guangjian. Research on Source Packet Data Splicing and Sorting Strategy for ASO-S Satellite[J]. Computer Engineering, 2025, 51(5): 166-176.

裴欣, 佟继周, 马福利, 于勤思, 杨广建. ASO-S卫星源包数据拼接与排序策略研究[J]. 计算机工程, 2025, 51(5): 166-176.

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Figures/Tables 9

Fig.1 Preprocessing procedure of ASO-S satellite data

Fig.2 Processing procedure of single downlink data source packet index sorting

Fig.3 Procedure of source packet index splicing and sorting for multiple downlink data

Fig.4 Schematic diagram of index information fragment cutting and resorting process

Fig.5 Comparison of the effectiveness of index information fragment segmentation and resorting algorithms

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