Showing papers by "Jordi Portell published in 2010"

Hardware implementation of the FAPEC lossless data compressor for space

Abstract: The instruments used in modern space missions require increasing amounts of telemetry resources to download the acquired data to the ground. Data compression helps to mitigate this problem and, therefore, it is currently seen as a mandatory stage for most of the missions, although the available on-board processing power is often modest. In many cases, data compression must be performed without losses. FAPEC is a lossless data compression algorithm that typically offers better ratios than the CCSDS 121.0 recommendation on realistic data sets. Its compression efficiency is higher than 90% of the Shannon limit in most cases, even in presence of large amounts of noise and outliers. FAPEC has been successfully implemented in software and its low-complexity algorithm also seemed suitable for a hardware implementation. In this paper we describe a prototype FPGA implementation which has been developed targeting the antifuse radiation-hardened RTAX Actel family. We have assessed that FAPEC can be easily implemented in hardware without requiring an external memory. The prototype presents an initial throughput of 32 Mbit/s and a complexity of 120 Kgate, hence being a compact and a robust solution for generic lossless compression. Finally, we discuss potential improvements that could easily boost the performance beyond the barrier of 100 Mbit/s.

Optimizing GPS data transmission using entropy coding compression

Abstract: The Global Positioning System (GPS) has long been used as a scientific tool, and it has turned into a very powerful technique in domains like geophysics, where it is commonly used to study the dynamics of a large variety of systems, like glaciers, tectonic plates and others. In these cases, the large distances between receivers as well as their remote locations usually pose a challenge for data transmission. The standard format for scientific applications is a compressed RINEX file - a raw data format which allows post-processing. Its associated compression algorithm is based on a pre-processing stage followed by a commercial data compressor. In this paper we present a new compression method which can achieve better compression ratios with a faster operation. We have improved the pre-compression stage, split the resulting file into two, and applied the most appropriate compressor to each file. FAPEC, a highly resilient entropy coder, is applied to the observables file. The results obtained so far demonstrate that it is possible to obtain average compression gains of about 35% with respect to the original compressor.

Simple resiliency improvement of the CCSDS standard for lossless data compression

Abstract: The Consultative Committee for Space Data Systems (CCSDS) recommends the use of a two-stage strategyfor lossless data compression in space. At the core of the second stage is the Rice coding method. The Ricecompression ratio rapidly decreases in the presence of noise and outliers, since this coder is specially conceived fornoiseless data following geometric distributions. This, in turn, makes the CCSDS recommendation too sensitivein front of outliers in the data, leading to non-optimal ratios in realistic scenarios. In this paper we proposeto substitute the Rice coder of the CCSDS recommendation by a subexponential coder. We show that thissolution oers high compression ratios even when large amounts of noise are present in the data. This is doneby testing both compressors with synthetic and real data. The performance is actually similar to that obtainedwith the FAPEC coder, although with slightly higher processing requirements. Therefore, this solution appearsas a simple improvement that can be done to the current CCSDS standard with an excellent return.Keywords: Data compression, lossless, CCSDS, resilient, robust, Rice, subexponential

Development of Optimum Lossless Compression Systems for Space Missions

Abstract: The scientific instruments included in modern space missions require high compression ratios in order to downlink all the acquired data to the ground. In many cases, this must be achieved without losses and the available processing power is modest. Algorithms requiring large amounts of data for their optimum operation cannot be used due to the limited reliability of the communications channel. Existing methods for lossless data compression often have difficulties in fulfilling such tight requirements. We present a method for the development of lossless compression systems achieving high compression ratios at a low processing cost while guaranteeing a reliable downlink. This is done using a two–stage compressor, with an adequate pre–processing stage followed by an entropy coder. The pre–processor should be tailored for each case and carefully evaluated. For the second stage, we analyze some existing solutions and we present a new entropy coder, which has comparable or even better performances than those offered by most coders and guarantees high ratios in front of outliers. Finally, we present the application of this method to the case of the Gaia mission and we present the results obtained.