GPS/Galileo navigation in GTO/GEO orbit

Marmet, François-Xavier; Maureau, Jerôme; Calaprice, Massimiliano; Aguttes, J.P.

doi:10.1016/j.actaastro.2015.08.008

Cited by 18 publications

(11 citation statements)

References 7 publications

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“…These receivers are picking up the spillover of the main lobe of the GNSS transmit antenna pattern around the Earth mask and also signals from the weaker side lobes of the antenna pattern. Research presented in [ 2 , 3 , 4 , 5 , 6 , 7 , 8 ] shows feasibility studies of GNSS as navigation system for space missions in High Earth Orbits (HEO) and beyond up to Moon altitude. Other research work, such as [ 9 , 10 , 11 , 12 ] and [ 13 ] has proposed GNSS receivers designed for such missions and the demonstration of a receiver positioning in HEO is detailed in [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

Standalone GPS L1 C/A Receiver for Lunar Missions

Capuano

Blunt

Botteron

et al. 2016

Sensors

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Global Navigation Satellite Systems (GNSSs) were originally introduced to provide positioning and timing services for terrestrial Earth users. However, space users increasingly rely on GNSS for spacecraft navigation and other science applications at several different altitudes from the Earth surface, in Low Earth Orbit (LEO), Medium Earth Orbit (MEO), Geostationary Earth Orbit (GEO), and feasibility studies have proved that GNSS signals can even be tracked at Moon altitude. Despite this, space remains a challenging operational environment, particularly on the way from the Earth to the Moon, characterized by weaker signals with wider gain variability, larger dynamic ranges resulting in higher Doppler and Doppler rates and critically low satellite signal availability. Following our previous studies, this paper describes the proof of concept “WeakHEO” receiver; a GPS L1 C/A receiver we developed in our laboratory specifically for lunar missions. The paper also assesses the performance of the receiver in two representative portions of an Earth Moon Transfer Orbit (MTO). The receiver was connected to our GNSS Spirent simulator in order to collect real-time hardware-in-the-loop observations, and then processed by the navigation module. This demonstrates the feasibility, using current technology, of effectively exploiting GNSS signals for navigation in a MTO.

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Section: Introductionmentioning

confidence: 99%

Standalone GPS L1 C/A Receiver for Lunar Missions

Capuano

Blunt

Botteron

et al. 2016

Sensors

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“…An additional step forward in this direction is the incipient use of POD GNSS receivers aboard geosynchronous satellites. Although their use is mainly driven by their need during geosynchronous transfer orbits and electric thrusters (Marmet et al, 2015), next generation geosynchronous transmitters will also have POD (tens of meters). The most promising strategy will probably be a combination of several of these techniques to obtain POD of the GEOs that will enable altimetry with W-SoOp.…”

Section: Challenges Of W-soopmentioning

confidence: 99%

Requirements for a Coastal Hazards Observing System

et al. 2019

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Coastal zones are highly dynamical systems affected by a variety of natural and anthropogenic forcing factors that include sea level rise, extreme events, local oceanic and atmospheric processes, ground subsidence, etc. However, so far, they remain poorly monitored on a global scale. To better understand changes affecting world coastal zones and to provide crucial information to decision-makers involved in adaptation to and mitigation of environmental risks, coastal observations of various types need to be collected and analyzed. In this white paper, we first discuss the main forcing agents acting on coastal regions (e.g., sea level, winds, waves and currents, river runoff, sediment supply and transport, vertical land motions, land use) and the induced coastal response (e.g., shoreline position, estuaries morphology, land topography at Frontiers in Marine Science | www.frontiersin.org 1 July 2019 | Volume 6 | Article 348Benveniste et al.Requirements for a Coastal Zone Observing System the land-sea interface and coastal bathymetry). We identify a number of space-based observational needs that have to be addressed in the near future to understand coastal zone evolution. Among these, improved monitoring of coastal sea level by satellite altimetry techniques is recognized as high priority. Classical altimeter data in the coastal zone are adversely affected by land contamination with degraded range and geophysical corrections. However, recent progress in coastal altimetry data processing and multisensor data synergy, offers new perspective to measure sea level change very close to the coast. This issue is discussed in much detail in this paper, including the development of a global coastal sea-level and sea state climate record with mission consistent coastal processing and products dedicated to coastal regimes. Finally, we present a new promising technology based on the use of Signals of Opportunity (SoOp), i.e., communication satellite transmissions that are reutilized as illumination sources in a bistatic radar configuration, for measuring coastal sea level. Since SoOp technology requires only receiver technology to be placed in orbit, small satellite platforms could be used, enabling a constellation to achieve high spatio-temporal resolutions of sea level in coastal zones.

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“…For planet Earth, the use of the Global Positioning System (GPS) for the orbital navigation at low altitudes [1,2,3] is conventional. For high altitude missions the use of similar constellation-based navigation methods is proposed and tested as well [4,5]. However, the use of GPS does not make the satellite completely autonomous, since it is related to the constellation of the GPS satellites and the constellation is mostly navigated from ground stations [6].…”

Section: Introductionmentioning

confidence: 99%

“…The performance of this state and parameter estimation has been verified by the Monte-Carlo simulation. Thus, the main contributions of the paper are: (1) Unlike the previous investigations the time delays between horizon vector measurements are included, so the measurements are non-simultaneous; (2) the CB is modelled as a tri-axial ellipsoid with uncertain geometric characteristics that are augmented to the process model and estimated using parameter estimation; (3) similarly, the rotation of the CB about its primary axes is considered as an unknown and estimated in the filtering procedure; (4) MacCullaghs' formula [30] is assumed as the governing gravitational dynamic model in the three-dimensional force field; (5) for such a problem a measurement model is proposed as an algorithm and UKF is utilized to overcome the nonlinearities.…”

Section: Introductionmentioning

confidence: 99%

Orbit estimation using a horizon detector in the presence of uncertain celestial body rotation and geometry

2018

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This paper presents an orbit estimation using non-simultaneous horizon detector measurements in the presence of uncertainties in the celestial body rotational velocity and its geometrical characteristics. The celestial body is modelled as a tri-axial ellipsoid with a three-dimensional force field. The non-simultaneous modelling provides the possibility to consider the time gap between horizon measurements. An unscented Kalman filter is used to estimate the spacecraft motion states and estimate the geometric characteristics as well as the rotational velocity of the celestial body. A Monte-Carlo simulation is implemented to verify the results. Simulations showed that using non-simultaneous horizon vector measurements, the spacecraft state errors converge to zero even in the presence of an uncertain geometry and rotational velocity of the celestial body.

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GPS/Galileo navigation in GTO/GEO orbit

Cited by 18 publications

References 7 publications

Standalone GPS L1 C/A Receiver for Lunar Missions

Standalone GPS L1 C/A Receiver for Lunar Missions

Requirements for a Coastal Hazards Observing System

Orbit estimation using a horizon detector in the presence of uncertain celestial body rotation and geometry

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