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"Deep Space Network."
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Initial result of the Chinese Deep Space Stations’ coordinates from Chinese domestic VLBI experiments
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
The Rotation and Interior Structure Experiment on the InSight Mission to Mars
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
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.
Journal Article
Deep Space Communications
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.
eBook
Probing Jupiter's Atmosphere Through Juno Radio Occultations: Methodology and Initial Observations
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
Long‐Term Variability of Mars' Exosphere Density Based on Precise Orbital Analysis of Mars Reconnaissance Orbiter and Mars Odyssey
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
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
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
Deep Space Network glitches worry scientists
NASA's aging radio antennas have faced years of budget cuts, threatening far-off spacecraft. Earlier this year, the Cassini spacecraft screwed up an orbital maneuver at Saturn because of a problem with its radio connection to Earth. The incident was one of several recent glitches in the Deep Space Network (DSN), NASA's complex of large radio antennas in California, Spain, and Australia. For more than 50 years, the DSN has been the lifeline for nearly every spacecraft beyond Earth's orbit, relaying commands from mission control and receiving data from the distant probe. On 30 September, in a meeting at NASA headquarters, officials will brief planetary scientists on the network's status. Many are worried, based on anecdotal reports, that budget cuts and age have taken a toll that could endanger the complex maneuvers that Cassini and Juno, a spacecraft now at Jupiter, will require over the next year.
Journal Article