Data streams from the low frequency instrument on-board the PLANCK satellite: Statistical analysis and compression efficiency

Free access article

Issue		Astron. Astrophys. Suppl. Ser. Volume 147, Number 1, November II 2000


Page(s)		51 - 74
DOI		http://dx.doi.org/10.1051/aas:2000289

DOI: 10.1051/aas:2000289

Astron. Astrophys. Suppl. Ser. 147, 51-74

Data streams from the low frequency instrument on-board the PLANCK satellite: Statistical analysis and compression efficiency

M. Maris¹ - D. Maino¹ - C. Burigana² - F. Pasian¹

Send offprint request: M. Maris, e-mail: maris@ts.astro.it

1 - Osservatorio Astronomico di Trieste, Via G.B. Tiepolo 11, I-34131 Trieste, Italia
e-mail: <name>@ts.astro.it
2 - Istituto TeSRE, Consiglio Nazionale delle Ricerche, Via Gobetti 101, I-40129 Bologna, Italia
e-mail: burigana@tesre.bo.cnr.it

Received May 22; accepted August 7, 2000

Abstract:

The expected data rate produced by the Low Frequency Instrument (LFI) planned to fly on the ESA PLANCK mission in 2007, is over a factor 8 larger than the bandwidth allowed by the spacecraft transmission system to download the LFI data. We discuss the application of lossless compression to PLANCK-LFI data streams in order to reduce the overall data flow. We perform both theoretical analysis and experimental tests using realistically simulated data streams in order to fix the statistical properties of the signal and the maximal compression rate allowed by several lossless compression algorithms. We studied the influence of signal composition and of acquisition parameters on the compression rate C_r and develop a semiempirical formalism to account for it. The best performing compressor tested up to now is the arithmetic compression of order 1, designed for optimizing the compression of white noise like signals, which allows an overall compression rate $\overline{\mbox{$C_{\mathrm{r}}$ }} = 2.65\, \pm\, 0.02$ . We find that such result is not improved by other lossless compressors, being the signal almost white noise dominated. Lossless compression algorithms alone will not solve the bandwidth problem but needs to be combined with other techniques.

Key words: methods: data analysis -- methods: statistical -- instrumentation: miscellaneous -- space vehicles -- cosmology: cosmic microwave background

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