Lossless Compression of Aldebaran-I Telemetry Data Using the On+ Algorithm

Lossless compression of telemetry data in satellites is essential due to the stringent limitations of bandwidth and onboard storage. Traditional methods based on information theory and entropy coding, such as Huffman and Arithmetic coding, exploit statistical redundancy but still present opportunities for improvement when applied to data with low redundancy, large alphabets, and near-uniform symbol distributions. This study proposes On+, a novel lossless compression algorithm for satellite telemetry data. Using real telemetry data captured by the Aldebaran-1 CubeSat satellite, a dataset consisting of 600 binary files was created. The performance of the proposed algorithm was evaluated in comparison with classical methods (Huffman and Arithmetic coding) and several commercial compressors (.rar, .zip, .7z, .xz, and .gz). The On+ algorithm achieved an average compression rate of 29.19%, with a standard deviation of 1.26 and a median of 29.09%, outperforming the traditional Huffman coding and Arithmetic coding methods in terms of compression efficiency. Furthermore, it exhibited superior performance compared with all commercial solutions evaluated, many of which resulted in file expansion (negative compression rates). These results demonstrate the effectiveness and viability of the On+ algorithm for optimizing telemetry data compression in satellites.