Implementation of CCSDS lossless compression algorithm for geomagnetic data
Long-term geomagnetic data monitoring will generate a huge amount of data, and compression algorithms will be required to reduce the amount of data to save data storage and transmission expenses. To adapt to the application with limited resources, the CCSDS lossless compression algorithm is applied...
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| Veröffentlicht in: | Journal of physics. Conference series Jg. 2387; H. 1; S. 12039 - 12046 |
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| Hauptverfasser: | , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Bristol
IOP Publishing
01.11.2022
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| Schlagworte: | |
| ISSN: | 1742-6588, 1742-6596 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | Long-term geomagnetic data monitoring will generate a huge amount of data, and compression algorithms will be required to reduce the amount of data to save data storage and transmission expenses. To adapt to the application with limited resources, the CCSDS lossless compression algorithm is applied to geomagnetic data measurement in our work. This compression algorithm is made up of two parts: a preprocessor and an adaptive entropy coder. In this study, the unit-delay predictor is chosen as the preprocessor based on the properties of the geomagnetic signal, and the adaptive entropy coder chooses a suitable compression algorithm for geomagnetic data. A 14-hour continuous measurement was performed. The results reveal that when the block size is set to 64, the algorithm can obtain a compression ratio in the geomagnetic field of 0.269 to 0.318. Furthermore, the number of chosen encoding options for three-axis magnetic data was counted. |
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| Bibliographie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1742-6588 1742-6596 |
| DOI: | 10.1088/1742-6596/2387/1/012039 |