Catalogue Search | MBRL
Search Results Heading
Explore the vast range of titles available.
MBRLSearchResults
-
DisciplineDiscipline
-
Is Peer ReviewedIs Peer Reviewed
-
Reading LevelReading Level
-
Content TypeContent Type
-
YearFrom:-To:
-
More FiltersMore FiltersItem TypeIs Full-Text AvailableSubjectPublisherSourceDonorLanguagePlace of PublicationContributorsLocation
Done
Filters
Reset
2,676
result(s) for
"Deep Space Network."
Sort by:
Initial result of the Chinese Deep Space Stations’ coordinates from Chinese domestic VLBI experiments
2017
China’s Lunar Exploration Program(CLEP) prompted the design and construction of the globally distributed Chinese Deep Space Network(CDSN). This network consists of Jiamusi and Kashi stations in China, and Zapala station in Argentina. However, the positions of Jiamusi and Kashi are not accurate enough for future Chinese deep space missions, and geodetic Very Long Baseline Interferometry(VLBI) is the most effective way to determine their positions. Since the CDSN stations are equipped with narrow-band receivers,they cannot participate in current international VLBI sessions in which wide-band frequencies are utilized. Thus a cooperative geodetic program of the CDSN and Chinese VLBI Network(CVN, the VLBI tracking subsystem of the CLEP) was initiated to determine their positions, in which specially designed frequencies can be utilized,and some CVN stations can act as position reference stations owing to their precise positions from long-term international VLBI observations. Primary results have been obtained from the CDSN–CVN combined domestic VLBI experiments from September 28, 2014, through December 10, 2015. The positions of Jiamusi and Kashi are determined to be better than 10-mm precision in the X, Y, and Z directions, which are improved by a factor of approximately 20 over their a priori values.
Journal Article
Io’s tidal response precludes a shallow magma ocean
2025
Io experiences tidal deformation as a result of its eccentric orbit around Jupiter, which provides a primary energy source for Io’s continuing volcanic activity and infrared emission
1
. The amount of tidal energy dissipated within Io is enormous and has been suggested to support the large-scale melting of its interior and the formation of a global subsurface magma ocean. If Io has a shallow global magma ocean, its tidal deformation would be much larger than in the case of a more rigid, mostly solid interior
2
. Here we report the measurement of Io’s tidal deformation, quantified by the gravitational tidal Love number
k
2
, enabled by two recent flybys of the Juno spacecraft. By combining Juno
3
,
4
and Galileo
5
,
6
–
7
Doppler data from the NASA Deep Space Network and astrometric observations, we recover Re(
k
2
) of 0.125 ± 0.047 (1
σ
) and the tidal dissipation parameter
Q
of 11.4 ± 3.6 (1
σ
). These measurements confirm that a shallow global magma ocean in Io does not exist and are consistent with Io having a mostly solid mantle
2
. Our results indicate that tidal forces do not universally create global magma oceans, which may be prevented from forming owing to rapid melt ascent, intrusion and eruption
8
,
9
, so even strong tidal heating—such as that expected on several known exoplanets and super-Earths
10
—may not guarantee the formation of magma oceans on moons or planetary bodies.
By measuring the tidal deformation of Io as it orbits Jupiter using Juno Doppler and historically available data, the hypothesis of a shallow global magma ocean in Io is shown to be false.
Journal Article
The Rotation and Interior Structure Experiment on the InSight Mission to Mars
by
Folkner, William M.
,
Rivoldini, Attilio
,
Van Hoolst, Tim
in
Aerospace Technology and Astronautics
,
Angular momentum
,
Angular momentum budget
2018
The Rotation and Interior Structure Experiment (RISE) on-board the InSight mission will use the lander’s X-band (8 GHz) radio system in combination with tracking stations of the NASA Deep Space Network (DSN) to determine the rotation of Mars. RISE will measure the nutation of the Martian spin axis, detecting for the first time the effect of the liquid core of Mars and providing in turn new constraints on the core radius and density. RISE will also measure changes in the rotation rate of Mars on seasonal time-scales thereby constraining the atmospheric angular momentum budget. Finally, RISE will provide a superb tie between the cartographic and inertial reference frames. This paper describes the RISE scientific objectives and measurements, and provides the expected results of the experiment.
Journal Article
Electron Density in Io's Alfvén Wing Observed Via Radio Occultation With Juno
2025
Juno performed close flybys of the innermost Galilean moon, Io, in December 2023 (I57) and February 2024 (I58). During these flybys, the radio link connecting the Juno spacecraft to Earth observing stations of NASA's Deep Space Network (DSN) propagated through the Alfvén wing, a magnetospheric feature in which plasma is produced between Io and Jupiter. The radio link is sensitive to the elevated electron densities in the Alfvén wing. A direct measurement of the total electron content was made by a linear combination of Juno's X‐band and Ka‐band downlink frequencies. Two different approaches were used in inverting the measurements into electron densities which assume different electron density distributions within the Alfvén wing. The maximum electron densities estimated in the Alfvén wing were 20,500–27,000 cm−3 on I57, in the northern Alfvén wing, and 15,300–31,000 cm−3 on I58, in the southern Alfvén wing. Plain Language Summary Juno conducted two close flybys of Io, the innermost Galilean moon of Jupiter, in December 2023 and February 2024. During these flybys, the Juno spacecraft transmitted radio signals to NASA's DSN for radio science investigations. The radio signals were occulted by, and thus propagated through, the Alfvén wing, a magnetospheric feature connecting Io to Jupiter. The frequency of the radio signal was altered by the large number of electrons in the Alfvén wing. The average electron density within the Alfvén wing was inferred though this radio occultation data. Key Points The radio link from Juno to Earth passed through the Io Alfvén wing during Juno's close encounters with Io on 30 Dec 2023 and 03 Feb 2024 Electron content was observed with estimated peak electron densities of 15,300–31,000 cm−3 within the Alfvén wing The observations on each flyby demonstrate the large variability in structure and electron density in the Io Alfvén wings
Journal Article
Probing Jupiter's Atmosphere Through Juno Radio Occultations: Methodology and Initial Observations
by
Gomez Casajus, Luis
,
Buccino, Dustin
,
Gramigna, Edoardo
in
Antennas
,
Atmosphere
,
Atmospheric dynamics
2025
This paper presents an analysis of Juno's first radio occultation experiments. Relying on two‐way radio links in the X‐ and Ka‐bands, we processed data from NASA's Deep Space Network antennas through a ray‐tracing inversion algorithm. By effectively isolating dispersive effects, we obtained measurements of the neutral atmosphere's characteristics. This enabled the derivation of pressure and temperature profiles from the recorded frequencies. These results complement prior data from Voyager occultations and CIRS observations, providing valuable contributions to our understanding of Jupiter's atmospheric dynamics.
Journal Article
Deep Space Communications
2016
A collection of some of the Jet Propulsion Laboratory's space missions selected to represent the planetary communications designs for and progression of various types of missions The text uses a case study approach to show the communications link performance resulting from the planetary communications design developed by the Jet Propulsion Laboratory (JPL). This is accomplished through the description of the design and performance of six representative planetary missions. These six cases illustrate progression through time of the communications system's capabilities and performance from 1970s technology to the most recent missions. The six missions discussed in this book span the Voyager for fly-bys in the 1970s, Galileo for orbiters in the 1980s, Deep Space 1 for the 1990s, Mars Reconnaissance Orbiter (MRO) for planetary orbiters, Mars Exploration Rover (MER) for planetary rovers in the 2000s, and the MSL rover in the 2010s. Deep Space Communications: Provides an overview of the Deep Space Network and its capabilities Examines case studies to illustrate the progression of system design and performance from mission to mission and provides a broad overview of the missions systems described Discusses actual flight mission telecom performance of each system Deep Space Communications serves as a reference for scientists and engineers interested in communications systems for deep-space telecommunications link analysis and design control.
Long‐Term Variability of Mars' Exosphere Density Based on Precise Orbital Analysis of Mars Reconnaissance Orbiter and Mars Odyssey
2024
The variability of Mars exosphere over monthly to solar‐cycle scales at 251 and 412 km altitude is quantified by analysis of 41‐Ls mean densities derived from precise orbit determination of the Mars Reconnaissance Orbiter (MRO) and Mars Odyssey (MO) satellites, respectively. The data encompass 2006–2020 (MRO) and 2002–2020 (MO). At both altitudes, most of the variance is captured by cos(Ls–ϕ), where ϕ ≈ 258°. This term represents the effects of solar heating changes due to the eccentricity of Mars orbit around the Sun, and climatological changes in heating due to lower‐atmosphere dust loading, which does not play a significant role. The remaining variability is connected with the “irregular” variability of solar flux over monthly time scales. For MO, the presence of Helium disrupts a clean correlation with these sources. Plain Language Summary The force of continuous bombardment of atmospheric particles on a satellite slowly changes its orbit. By tracking the satellite, changes in its orbit can in turn be used to infer atmospheric particle densities. In this paper, we use tracking from NASA's Deep Space Network, an international array of giant antennas, to measure minute orbital changes of the Mars Reconnaissance Orbiter and Mars Odyssey satellite orbits (and thereby atmospheric densities) around Mars during the 2002–2020 time frame. These data are used to study how the outer regions of Mars atmosphere respond to changes in heating due to solar radation absorption by various chemical species, and by dust that is elevated into the atmosphere by strong winds near the surface. The major finding of this paper is that the variability of Mars outer atmosphere is mainly controlled by solar heating changes due to the eccentricity of Mars orbit around the Sun. Key Points Densities from precise orbit determination of Mars Reconnaissance Orbiter and Mars Odyssey are used to quantify long‐term variability of Mars' exosphere The annual term is the greatest contributor to total variance, followed by the irregular component of EUV/UV flux Dust‐induced inter‐annual variability is small, but the analysis method does suppress potentially important regional‐scale events
Journal Article
The Juno Gravity Science Instrument
by
Folkner, William M.
,
Asmar, Sami W.
,
Buccino, Dustin R.
in
Aerospace Technology and Astronautics
,
Astrophysics and Astroparticles
,
Charged particles
2017
The Juno mission’s primary science objectives include the investigation of Jupiter interior structure via the determination of its gravitational field. Juno will provide more accurate determination of Jupiter’s gravity harmonics that will provide new constraints on interior structure models. Juno will also measure the gravitational response from tides raised on Jupiter by Galilean satellites. This is accomplished by utilizing Gravity Science instrumentation to support measurements of the Doppler shift of the Juno radio signal by NASA’s Deep Space Network at two radio frequencies. The Doppler data measure the changes in the spacecraft velocity in the direction to Earth caused by the Jupiter gravity field. Doppler measurements at X-band (
∼
8
GHz) are supported by the spacecraft telecommunications subsystem for command and telemetry and are used for spacecraft navigation as well as Gravity Science. The spacecraft also includes a Ka-band (
∼
32
GHz) translator and amplifier specifically for the Gravity Science investigation contributed by the Italian Space Agency. The use of two radio frequencies allows for improved accuracy by removal of noise due to charged particles along the radio signal path.
Journal Article
A federated reinforcement learning framework for balancing rapidity and availability in deep space networks
2026
Efficient task scheduling is essential for the success of deep space exploration missions, where communication delays, dynamic link availability, and limited on-board resources pose significant challenges. However, existing deep-space scheduling frameworks cannot effectively coordinate multi-agent decisions across interplanetary regions due to long delays, dynamic link conditions, and highly unbalanced resources, resulting in inefficient and unstable task allocation. To address these issues, we propose Fed-ASTRA, a novel scheduling framework that integrates a hierarchical deep space network architecture with federated multi-agent reinforcement learning. In the proposed architecture, base stations such as Earth and Mars ground centers act as regional control centers, orbital satellites function as edge intelligence nodes, and rovers serve as terminal execution units, forming a three-tier collaborative system. This hierarchical organization enables both local autonomy and cross-domain coordination, effectively balancing real-time responsiveness and long-term availability. On the algorithmic side, we model the scheduling process as a multi-agent Markov decision process and design environment-constrained action pruning (ECAP) to filter out infeasible actions caused by link outages, energy thresholds, and deadline violations. In addition, a prioritized experience replay (PER) mechanism improves sample efficiency by emphasizing high-cost task experiences. These enhancements ensure that agents learn feasible and efficient scheduling strategies under severe environmental constraints. We evaluate Fed-ASTRA using a high-fidelity deep space network simulator driven by real orbital data. Experimental results demonstrate that our framework outperforms traditional optimization approaches, heuristic methods, and baseline MARL algorithms in terms of rapidity, availability, fairness, and real-time capability. Overall, this work highlights the potential of combining hierarchical network architectures and federated reinforcement learning to achieve robust and efficient task scheduling in future deep space missions.
Journal Article