On the compression of spacecraft housekeeping data using discrete cosine transforms

To gain deeper insight into the behavior the mechanical and thermal stress and the environment of a spacecraft extended monitoring is required. This implies the application of high resolution sensors in both value and time domain which produces a considerable amount of data. Thus in order to optimize the information throughput of the bandwidth available for monitoring we propose a compression algorithm derived from well-established approaches for image compression. Namely a two-dimensional discrete cosine transform (DCT) will be applied to compress one-dimensional time-series data of various sensor types. Data quality in terms of mean square error and peak signal-to-noise ratio as well as compression ratio of the introduced algorithm together with its derived pareto optimal set of parameters will be verified by applying it to real-world sets of housekeeping data. We will use different sensor samples of both satellites (AISat) and launchers (ARIANE 5).