Compressão sem perdas de dados de telemetria satelital usando o algoritmo On+

Abstract

Satellite data telemetry comprises the set of information required to monitor, control, and ensure the safe and efficient operation of space missions. The reduction in the volume of this data, transmitted from the satellite to ground stations, is called telemetry stream compression. Lossless compression applied to this data is essential to guarantee the integrity of the original data. This approach primarily exploits the statistical redundancy present in the data to reduce the volume of information transmitted or stored. In this context, lossless compression becomes even more relevant, given the severe bandwidth constraints on communication links and the limited on-board storage capacity of satellites. This study proposes On+, a new lossless compression algorithm for satellite telemetry data. Using real telemetry data captured by the Aldebaran-1 CubeSat satellite and the TinyGS Ground Station platform, a dataset consisting of 2500 binary files was created. The performance of the proposed algorithm was evaluated in comparison with classical methods (Huffman coding and Arithmetic coding) and various commercial compressors (.rar, .zip, .7z, .xz, and .gz). The On+ algorithm achieved an average compression ratio of 29.19% on Aldebaran-1 satellite data, with a standard deviation of 1.26% and a median of 29.09%, outperforming the evaluated methods in terms of compression ratio. For satellites on the TinyGS platform, On+ also delivered significant results, achieving a median compression ratio close to 50% in specific satellite classes, with Starlink standing out in particular. This result demonstrates the method’s ability to efficiently exploit the statistical characteristics of certain telemetry datasets, obtaining substantial compression gains.