Deep space (DS) exploration is aimed at acquiring information about the solar system and its composition, a purpose that can be achieved only if a significant communication capacity can be provided to spacecrafts at very large distances [1]. The Ka-band (at 32-34 GHz) and higher frequency band channels can provide this capacity if compared to the current X-band (around 8.4 GHz) [2]-[4]. Ka-band can offer a striking performance advantage over X-band because of the square-frequency law increase of directivity of the downlink beam for the same physical antenna size. This opens up a possible and useful trade space for Ka-band missions with the same antenna size (and spacecraft constraints) and radio frequency power, since a Ka-band mission can return four times more data than a comparable X–band mission. For the European Space Agency (ESA), the next step in this direction will be the utilisation of Ka-band downlinks both to generate radiometric observables (in combination with X-band uplink) as well as to increase science data transfer [5]. The first satellite mission adopting such frequency operationally will be BepiColombo (BC), the ESA cornerstone mission to Mercury (expected launch in 2015) including the Mercury Orbiter Radio Experiment (MORE) at X-Ka band [6]. The optimal allocation of channel resources above Ku band is limited by the significant impact of radio- meteorological factors which can irremediably degrade the quality of service for fairly high percentage of time [7]. At Ka band, for instance, attenuation due to cloudy and rainy troposphere can be even one order of magnitude larger than at X-band. The major cause of outages at Ka band and above is due to rainfall, as well as non-precipitating clouds. For small carrier-to-noise ratio (CNR), the impact of atmospheric noise temperature can become non-negligible [4]. In order to achieve the optimum data return at Ka-band, a different approach with respect to the link budget computation at lower frequencies (e.g., S or X band) is necessary [2]. Such link analysis is based on the maximization of the expected data return in a probabilistic framework rather than on a specified link statistical availability. Recent methods uses monthly statistics collected at the receiving site with the aim of defining average values of expected received data volume [5] and the exploitation of numerical weather forecasting is also foreseen [3]. This paper introduces the preliminary concept of the RadioMetOP (RadioMeteorological Operations Planner) technique and describes its main modelling components and objectives, limiting the analysis to rainfall effects. Numerical results in terms of received frame data for unconstrained and constrained system scenarios are also described together with a discussion about the possible impact of RadioMetOP methods on BC operations.

Investigating Ka-band science data transfer for BepiColombo mission by using radiometeorological numerical models / Marzano, FRANK SILVIO; Biscarini, Marianna; Iess, Luciano; Gregnanin, Marco; Parisi, Marzia; Montopoli, Mario; K., De Sanctis; S., Di Fabio; L., Bernardini; M., Montagna; M., Arza; M., Mercolino; M., Lanucara. - ELETTRONICO. - (2013). (Intervento presentato al convegno TTC 2013 6th ESA International Workshop on Tracking, Telemetry and Command System for Space Application tenutosi a ESA-ESOC, Darmstadt nel 10-13 Settembre 2013).

Investigating Ka-band science data transfer for BepiColombo mission by using radiometeorological numerical models

MARZANO, FRANK SILVIO
;
BISCARINI, MARIANNA;IESS, Luciano
Membro del Collaboration Group
;
GREGNANIN, MARCO;PARISI, MARZIA;MONTOPOLI, MARIO;
2013

Abstract

Deep space (DS) exploration is aimed at acquiring information about the solar system and its composition, a purpose that can be achieved only if a significant communication capacity can be provided to spacecrafts at very large distances [1]. The Ka-band (at 32-34 GHz) and higher frequency band channels can provide this capacity if compared to the current X-band (around 8.4 GHz) [2]-[4]. Ka-band can offer a striking performance advantage over X-band because of the square-frequency law increase of directivity of the downlink beam for the same physical antenna size. This opens up a possible and useful trade space for Ka-band missions with the same antenna size (and spacecraft constraints) and radio frequency power, since a Ka-band mission can return four times more data than a comparable X–band mission. For the European Space Agency (ESA), the next step in this direction will be the utilisation of Ka-band downlinks both to generate radiometric observables (in combination with X-band uplink) as well as to increase science data transfer [5]. The first satellite mission adopting such frequency operationally will be BepiColombo (BC), the ESA cornerstone mission to Mercury (expected launch in 2015) including the Mercury Orbiter Radio Experiment (MORE) at X-Ka band [6]. The optimal allocation of channel resources above Ku band is limited by the significant impact of radio- meteorological factors which can irremediably degrade the quality of service for fairly high percentage of time [7]. At Ka band, for instance, attenuation due to cloudy and rainy troposphere can be even one order of magnitude larger than at X-band. The major cause of outages at Ka band and above is due to rainfall, as well as non-precipitating clouds. For small carrier-to-noise ratio (CNR), the impact of atmospheric noise temperature can become non-negligible [4]. In order to achieve the optimum data return at Ka-band, a different approach with respect to the link budget computation at lower frequencies (e.g., S or X band) is necessary [2]. Such link analysis is based on the maximization of the expected data return in a probabilistic framework rather than on a specified link statistical availability. Recent methods uses monthly statistics collected at the receiving site with the aim of defining average values of expected received data volume [5] and the exploitation of numerical weather forecasting is also foreseen [3]. This paper introduces the preliminary concept of the RadioMetOP (RadioMeteorological Operations Planner) technique and describes its main modelling components and objectives, limiting the analysis to rainfall effects. Numerical results in terms of received frame data for unconstrained and constrained system scenarios are also described together with a discussion about the possible impact of RadioMetOP methods on BC operations.
2013
TTC 2013 6th ESA International Workshop on Tracking, Telemetry and Command System for Space Application
BepiColombo; Deep Space radio links; space missions; space telecommunications
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Investigating Ka-band science data transfer for BepiColombo mission by using radiometeorological numerical models / Marzano, FRANK SILVIO; Biscarini, Marianna; Iess, Luciano; Gregnanin, Marco; Parisi, Marzia; Montopoli, Mario; K., De Sanctis; S., Di Fabio; L., Bernardini; M., Montagna; M., Arza; M., Mercolino; M., Lanucara. - ELETTRONICO. - (2013). (Intervento presentato al convegno TTC 2013 6th ESA International Workshop on Tracking, Telemetry and Command System for Space Application tenutosi a ESA-ESOC, Darmstadt nel 10-13 Settembre 2013).
File allegati a questo prodotto
File Dimensione Formato  
Marzano_preprint_Investingating-Ka-band_2013.pdf

accesso aperto

Tipologia: Documento in Pre-print (manoscritto inviato all'editore, precedente alla peer review)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 645.17 kB
Formato Adobe PDF
645.17 kB Adobe PDF

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/539887
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact