Optimizing GPS data transmission using entropy coding compression

Alberto G. Villafranca; Iu Mora; Patrícia Ruiz-Rodríguez; Jordi Portell; Enrique García-Berro

doi:10.1117/12.860848

24 August 2010 Optimizing GPS data transmission using entropy coding compression

Alberto G. Villafranca, Iu Mora, Patrícia Ruiz-Rodríguez, Jordi Portell, Enrique García-Berro

Proceedings Volume 7810, Satellite Data Compression, Communications, and Processing VI; 781015 (2010) https://doi.org/10.1117/12.860848
Event: SPIE Optical Engineering + Applications, 2010, San Diego, California, United States

Abstract

The Global Positioning System (GPS) has long been used as a scientific tool, and it has turned into a very powerful technique in domains like geophysics, where it is commonly used to study the dynamics of a large variety of systems, like glaciers, tectonic plates and others. In these cases, the large distances between receivers as well as their remote locations usually pose a challenge for data transmission. The standard format for scientific applications is a compressed RINEX file - a raw data format which allows post-processing. Its associated compression algorithm is based on a pre-processing stage followed by a commercial data compressor. In this paper we present a new compression method which can achieve better compression ratios with a faster operation. We have improved the pre-compression stage, split the resulting file into two, and applied the most appropriate compressor to each file. FAPEC, a highly resilient entropy coder, is applied to the observables file. The results obtained so far demonstrate that it is possible to obtain average compression gains of about 35% with respect to the original compressor.

Citation Download Citation

Alberto G. Villafranca, Iu Mora, Patrícia Ruiz-Rodríguez, Jordi Portell, and Enrique García-Berro "Optimizing GPS data transmission using entropy coding compression", Proc. SPIE 7810, Satellite Data Compression, Communications, and Processing VI, 781015 (24 August 2010); https://doi.org/10.1117/12.860848

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