Résumé
Autonomous vehicles are able to sense their environment and operate without human involvement. In particular, they have to be able to locate themselves. In order to achieve this task, geolocalisation files such as RINEX files are used. Due to the large amount of data, these files are very large and there is a big challenge in reducing their size for real-time navigation. However, this problem has not really been explored for RINEX files. In this paper, we propose an efficient method to losslessly compress RINEX files based on quadratic polynomial interpolation for autonomous vehicles navigation. Indeed, due to the orbits of the satellites around the earth, satellite signals can be modeled by parabolic curves. After interpolation of this model, prediction errors are computed as the differences between each original value of the satellite signal and its associated predicted value. Finally, these prediction errors are compressed using entropy coding. Experimental results show that our proposed method allows us to outperform the compression rate obtained by a previous state-of-the-art approach.