Chapter 16 - The CCSDS Lossless Data Compression Recommendation for Space Applications

Abstract

This chapter discusses CCSDS lossless data compression recommendation for space applications. The space-based algorithm implementations face extra constraints relative to ground-based implementations and the difference is mainly because of the lack of computing resources in space and possible bit errors incurred in the communication channel. Taking all these constraints into consideration, a set of requirements was first formulated for selecting a lossless compression algorithm—first, the algorithm must adapt to changes in data statistics to maximize compression performance, and second, the algorithm must be implemented in real time with small memory and little power usage. Several available algorithms were evaluated on test science data and the excellent compression performance and the high throughput rate of the Rice algorithm suggested further study, which resulted in a mathematical proof of its performance. Further study on the algorithm brought out a parallel architecture, which was then implemented in an application-specific integrated circuit for space applications. An extension to low-entropy data was also devised and incorporated in the original Rice architecture. The resulting algorithm is referred to as the extended_Rice, or e_Rice, algorithm. The e_Rice algorithm exploits a set of variable-length codes to achieve compression. The adaptive entropy coder is discussed in the next section. The chapter further discusses the role of the preprocessor to transform the data into samples that can be more efficiently compressed by the entropy encoder. In general, a preprocessor that removes correlation between samples in the input data block will improve the performance of the entropy coder.