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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Bibliographic Details
Published in:Journal of physics. Conference series Vol. 2387; no. 1; pp. 12039 - 12046
Main Authors: Zhang, Yue, Li, Li, Huang, Chengbin, Wang, Jinhua
Format: Journal Article
Language:English
Published: Bristol IOP Publishing 01.11.2022
Subjects:
Algorithms
Compression ratio
Data compression
Data storage
Entropy
Geomagnetic field
Geomagnetism
Physics
ISSN:1742-6588, 1742-6596
Online Access:Get full text
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Summary: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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ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2387/1/012039