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At least 253 records · Page 14

SOLAR-A

The DSN (Deep Space Network) mission support requirements for SOLAR-A are summarized. The SOLAR-A mission objectives are to investigate high energy phenomena of the Sun using x-ray telescopes and spectrometers during the maximum activity period of the solar cycle. The spacecraft will be launched into a circular earth orbit of approximately 500 km altitude and 31 deg inclination. The mission objectives are outlined and the DSN support requirements are defined through the presentation of tables and narratives describing the spacecraft profile; DSN support coverage; frequency assignments; support parameters for telemetry, command and support systems; and tracking support responsibility.

Ninomiya, K.↗

Telecommunications and navigation systems design for manned Mars exploration missions

This paper discusses typical manned Mars exploration needs for telecommunications, including preliminary navigation support functions. It is a brief progress report on an ongoing study program within the current NASA JPL Deep Space Network (DSN) activities. A typical Mars exploration case is defined, and support approaches comparing microwave and optical frequency performance for both local in situ and Mars-earth links are described. Optical telecommunication and navigation technology development opportunities in a Mars exploration program are also identified. A local Mars system telecommunication relay and navigation capability for service support of all Mars missions has been proposed as part of an overall solar system communications network. The effects of light-time delay and occultations on real-time mission decision-making are discussed; the availability of increased local mass data storage may be more important than increasing peak data rates to earth. The long-term frequency use plan will most likely include a mix of microwave, millimeter-wave and optical link capabilities to meet a variety of deep space mission needs.

Hall, Justin R.↗

Ulysses

The DSN (Deep Space Network) mission support requirements for Ulysses are summarized. The primary goal of the Ulysses mission is to explore the Sun, its environment, and possible links between solar variability and terrestrial weather and climate. The Ulysses spacecraft will be injected into an interplanetary orbit toward Jupiter after which the spacecraft travels in a heliocentric, out-of-ecliptic orbit with high heliographic inclination. The Ulysses mission objectives are outlined and the DSN support requirements are defined through the presentation of tables and narratives describing the spacecraft flight profile; DSN support coverage; frequency assignments; support parameters for telemetry, command and support systems; and tracking support responsibility.

Meeks, W.↗

Availability analysis of the traveling-wave maser amplifiers in the deep space network. Part 1: The 70-meter antennas

The results of the reliability and availability analyses of the individual S- and X-band traveling-wave maser (TWM) assemblies and their operational configurations in the 70-meter antennas of NASA's Deep Space Network (DSN) are described. For the period 1990 through 1991, the TWM availability parameters for the Telemetry Data System are: mean time between failures (MTBF), 930 hr; mean time to restore services (MTTRS), 1.4 hr; and the average availability, 99.85 percent. In previously published articles, the performance analysis of the TWM assemblies was confined to the determination of the parameters specified above. However, as the mean down time (MDT) for the repair of TWM's increases, the levels of the TWM operational availabilities and MTTRS are adversely affected. A more comprehensive TWM availability analysis is presented to permit evaluation of both MTBF and MDT effects. Performance analysis of the TWM assemblies, based on their station monthly failure reports, indicates that the TWM's required MTBF and MDT levels of 3000 hr and 36 to 48 hr, respectively, have been achieved by the TWM's only at the Canberra Deep Space Station (DSS 43). The Markov Process technique is employed to develop suitable availability measures for the S- and X-band TWM configurations when each is operated in a two-assembly standby mode. The derived stochastic expressions allow for the evaluation of those configurations' simultaneous availability for the Antenna Microwave Subsystem. The application of these expressions to demonstrate the impact of various levels of TWM maintainability (or MDT) on their configurations' operational availabilities is presented for each of the 70-m antenna stations.

Issa, T. N.↗

Pioneer 6 through 8

The DSN (Deep Space Network) mission support requirements for Pioneer 6, 7 and 8 are summarized. The primary objective of these Pioneer missions is to collect scientific data relative to interplanetary phenomena within a range of approximately 0.8 to 1.2 astronomical units from the sun. Following orbital injection, each spacecraft was oriented with its spin axis normal to the ecliptic plane so that the high gain antenna pattern would be aligned with Earth's orbit. The mission objectives are outlined and the DSN support requirements are defined through the presentation of tables and narratives describing the spacecraft flight profiles; DSN support coverage; frequency assignments; support parameters for telemetry, command and support systems; and tracking support responsibility.

Lozier, D.↗

Nimbus-7

The DSN (Deep Space Network) mission support requirements for Nimbus 7 are summarized. The basic Nimbus series spacecraft is attitude-stabilized in three axes, with the yaw axis always pointing towards the center of the Earth. The spacecraft provides a stable platform, power, command, and data handling support for active and passive sensors for daily global surveillance of the atmosphere, and for mapping details of the atmospheric structure and Earth surface from satellite altitudes. The Nimbus 7 mission objectives are outlined and the DSN support requirements are defined through the presentation of tables and narratives describing the spacecraft flight profile; DSN support coverage; S-band frequency assignments; support parameters for telemetry, command and support systems; and tracking support responsibility.

Foreman, M.↗

An Array of Optical Receivers for Deep-Space Communications

An array of small optical receivers is proposed as an alternative to a single large optical receiver for high-data-rate communications in NASA s Deep Space Network (DSN). Because the telescope for a single receiver capable of satisfying DSN requirements must be greater than 10 m in diameter, the design, building, and testing of the telescope would be very difficult and expensive. The proposed array would utilize commercially available telescopes of 1-m or smaller diameter and, therefore, could be developed and verified with considerably less difficulty and expense. The essential difference between a single-aperture optical-communications receiver and an optical-array receiver is that a single-aperture receiver focuses all of the light energy it collects onto the surface of an optical detector, whereas an array receiver focuses portions of the total collected energy onto separate detectors, optically detects each fractional energy component, then combines the electrical signal from the array of detector outputs to form the observable, or "decision statistic," used to decode the transmitted data. A conceptual block diagram identifying the key components of the optical-array receiver suitable for deep-space telemetry reception is shown in the figure. The most conspicuous feature of the receiver is the large number of small- to medium-size telescopes, with individual apertures and number of telescopes selected to make up the desired total collecting area. This array of telescopes is envisioned to be fully computer- controlled via the user interface and prediction-driven to achieve rough pointing and tracking of the desired spacecraft. Fine-pointing and tracking functions then take over to keep each telescope pointed toward the source, despite imperfect pointing predictions, telescope-drive errors, and vibration caused by wind.

Vilnrotter, Chi-Wung↗

A determination of the radio-planetary frame tie and the DSN tracking station locations

The orientation of the reference frame of radio source catalogs relative to that of planetary ephemerides is uncertain by 30 mas (150 nrad). At this level of uncertainty this orientation offset, or 'frame tie', can be a major systematic error source for interplanetary spacecraft orbit determination. This work presents a method of determining the radio-planetary frame tie from a comparison of Very Long Baseline Interferometry (VLBI) and Lunar Laser Ranging (LLR) station coordinate and earth orientation parameter estimates. Preliminary results are presented which indicate that accuracies of 5 mas or better may be achieved with this method. An important by-product of this method of frame tie determination is a set of Deep Space Network (DSN) station locations with 10 cm per component accuracy. This station set is in a geocentric coordinate system with known orientation relative to the radio and planetary frames.

Finger, Mark H.↗

Mars Cube One (MarCO) Shifting the Paradigm in Relay Deep Space Operations

A very significant challenge in the planetary mission design and operations is communications with ground control teams during critical events and highly risky maneuvers. These include entry, descent, and landing (EDL) and orbit insertion, which should not be carried out in the blind. Although vast planetary distances and long round-trip light times disallow real-time intervention from controllers, acquiring the relevant event performance parameters in near real-time can be imperative for determining the corrective actions needed immediately following or, in the case of significant anomalies, aid in the diagnostic analysis. During several previous Mars missions landing events, and the Huygens probe landing on Titan, the communications strategy relied on proximity links to planetary orbiters, which then relayed the data to the Deep Space Network (DSN). In addition, attempts were successfully made in parallel to receive the signal carrier directly at Earth often using large radio telescopes when the wavelength was outside the DSN’s reception bands. This Direct-to-Earth (DTE) back-up method was only possible due to special techniques utilizing the DSN’s open-loop Radio Science Receivers. In every case, it was very challenging since the link budget of a landing vehicles were designed for proximity orbiter relays and not for distances across the solar system. A new method is introduced since not all future missions can rely on the presence of pre-existing orbiters at their planetary targets to relay their critical data ad, furthermore, most missions would not likely have the resources to implement a reliable DTE link at acceptable data rates, bypassing a need for a relay asset. With the advent CubeSat form-factor spacecraft, one or more, for added reliability, CubeSats can be launched with the primary mission, travel to the target, and be positioned to view the critical event, such as EDL, and carry out real-time relay of the data to the DSN at higher rates. CubeSats have flown in the Earth environment but never flown or been operated in deep space or planetary environment so careful design as well as flight experience are needed. The relay function requires the development of radio and antenna systems to meet challenging specifications. After initial technical demonstration of the concept and operational experience, the cost can decrease as systems become more standardized with increased reliability. This paper describes the invention of the “carry your own relay” concept and the formulation of the mission likely to be the first planetary CubeSat mission called Mars Cube One (MarCO). It also describes the operational concept of relay small spacecraft and their role reducing mission risk as well as overall mission cost.

Asmar, Sami↗

Scheduling the NASA Deep Space Network with Deep Reinforcement Learning

With three complexes spread evenly across the Earth, NASA’s Deep Space Network (DSN) is the primary means of communications as well as a significant scientific instrument for dozens of active missions around the world. A rapidly rising number of spacecraft and increasingly complex scientific instruments with higher bandwidth requirements have resulted in demand that exceeds the network’s capacity across its 12 antennae. The existing DSN scheduling process operates on a rolling weekly basis and is time-consuming; for a given week, generation of the final baseline schedule of spacecraft tracking passes takes roughly 5 months from the initial requirements submission deadline, with several weeks of peer-to-peer negotiations in between. This paper proposes a deep reinforcement learning (RL) approach to generate candidate DSN schedules from mission requests and spacecraft ephemeris data with demonstrated capability to address real-world operational constraints. A deep RL agent is developed that takes mission requests for a given week as input, and interacts with a DSN scheduling environment to allocate tracks such that its reward signal is maximized. A comparison is made between an agent trained using Proximal Policy Optimization and its random, untrained counterpart. The results represent a proof-of-concept that, given a well-shaped reward signal, a deep RL agent can learn the complex heuristics used by experts to schedule the DSN. A trained agent can potentially be used to generate candidate schedules to bootstrap the scheduling process and thus reduce the turnaround cycle for DSN scheduling.

Wilson, Brian↗

Autonomy for SOHO Ground Operations

The SOLAR and HELIOSPHERIC OBSERVATORY (SOHO) project [SOHO Web Page] is being carried out by the European Space Agency (ESA) and the US National Aeronautics and Space Administration (NASA) as a cooperative effort between the two agencies in the framework of the Solar Terrestrial Science Program (STSP) comprising SOHO and other missions. SOHO was launched on December 2, 1995. The SOHO spacecraft was built in Europe by an industry team led by Matra, and instruments were provided by European and American scientists. There are nine European Principal Investigators (PI's) and three American ones. Large engineering teams and more than 200 co-investigators from many institutions support the PI's in the development of the instruments and in the preparation of their operations and data analysis. NASA is responsible for the launch and mission operations. Large radio dishes around the world, which form NASA's Deep Space Network (DSN), are used to track the spacecraft beyond the Earths orbit. Mission control is based at Goddard Space Flight Center in Maryland. The agent group at the NASA Goddard Space Flight Center, in collaboration with JPL, is currently involved with the design and development of an agent-based system to provide intelligent interactions with the control center personnel for SOHO. The basic approach that is being taken is to develop a sub-community of agents for each major subsystem of SOHO and to integrate these sub-communities into an overall SOHO community. Agents in all sub-communities will be capable of advanced understanding (deep reasoning) of the associated spacecraft subsystem.

Truszkowski, Walt↗

Coherent Frequency Reference System for the NASA Deep Space Network

The NASA Deep Space Network (DSN) requires state-of-the-art frequency references that are derived and distributed from very stable atomic frequency standards. A new Frequency Reference System (FRS) and Frequency Reference Distribution System (FRD) have been developed, which together replace the previous Coherent Reference Generator System (CRG). The FRS and FRD each provide new capabilities that significantly improve operability and reliability. The FRS allows for selection and switching between frequency standards, a flywheel capability (to avoid interruptions when switching frequency standards), and a frequency synthesis system (to generate standardized 5-, 10-, and 100-MHz reference signals). The FRS is powered by redundant, specially filtered, and sustainable power systems and includes a monitor and control capability for station operations to interact and control the frequency-standard selection process. The FRD receives the standardized 5-, 10-, and 100-MHz reference signals and distributes signals to distribution amplifiers in a fan out fashion to dozens of DSN users that require the highly stable reference signals. The FRD is also powered by redundant, specially filtered, and sustainable power systems. The new DSN Frequency Distribution System, which consists of the FRS and FRD systems described here, is central to all operational activities of the NASA DSN. The frequency generation and distribution system provides ultra-stable, coherent, and very low phase-noise references at 5, l0, and 100 MHz to between 60 and 100 separate users at each Deep Space Communications Complex.

Tucker, Blake C.↗

StarNAV: An Architecture for Autonomous Spacecraft Navigation by the Relativistic Perturbation of Starlight

Exploration missions to the outer Solar System (e.g., Neptune, Kuiper belt objects) or to the interstellar medium present several challenges for conventional spacecraft designs. One of the greatest challenges is a means for navigation, as Earth-based tracking with the Deep Space Network (DSN) becomes less desirable due to high cost, decreased performance at long ranges, and long light-time delays. Indeed, light time delays at Neptune are over four hours (one way), making control of spacecraft during critical events nearly impossible—and this problem only becomes worse as we move to the Kuiper belt or to interstellar space. The need for autonomous spacecraft navigation is well established and is prominently featured in the 2015 NASA Technology Roadmap (e.g., TA 5.4.2.6 & 5.4.2.8). This has led to investment in various technologies to accomplish this task, with the majority of recent work focusing on optical navigation (OPNAV; TA 5.4.4.1) [1], X-ray pulsar navigation (XNAV; TA 5.6.1) [2], or DSN one-way ranging with the Deep Space Atomic Clock (DSAC; TA 5.4.1.1) [3]. This NIAC study suggests a new (and completely different) way of autonomously navigating a spacecraft anywhere in the Solar System or beyond. We call this new technique StarNAV.

NIAC Phase I↗

Dynamic modeling of fluid transmission lines of the DSN 70-meter antennas by using a lumped parameter model

Fluid transmission lines and fittings were found to significantly affect the dynamic and steady state operation of the engineering system in which they are incorporated. Therefore, a better understanding of the operation of a system can be obtained by including the performance of the transmission lines and fittings within the system model. The most accurate model of a transmission line or fitting is obtained by using a distributed parameter model. However, a distributed parameter model tends to be very complex. This complexity can be avoided without significant loss of model accuracy by using a lumped parameter model when the length of the fluid path through the transmission line or fitting is short. This article develops a lumped parameter model for short fluid transmission lines and fittings, describes the conditions under which the model is valid, and presents the model parameters associated with the servo hydraulic system of the Deep Space Network (DSN) 70-meter antennas.

Bartos, R. D.↗

BioSentinel Deep Space CubeSat Mission

The BioSentinel mission was recently launched aboard the SLS launch vehicle (LV) as part of the Artemis-1 campaign. This 6U CubeSat carries yeast cells to analyze the effects of radiation at large distances from Earth, becoming the first biological payload in Deep Space. Prelaunch activities included mission design updates, orbit determination rehearsals and the development of a tracking schedule in coordination with the Artemis-1 payload office and the Deep Space Network (DSN). An important influence on the trajectories of Artemis I secondaries was the uncertainty associated with deployment from the Interim Cryogenic Propulsion System (ICPS), the upper stage of the SLS LV. The ICPS was rotating at a rate of 1 rpm; there was also uncertainty in the spin axis attitude, which translated into an unknown clock angle of deployment. The variability in this angle and magnitude of deployment implied the existence of a non-negligible risk of a lunar impact, which was evaluated for various potential launch dates. On November 16 th 2022 BioSentinel successfully deployed from ICPS and the navigation team started to receive tracking data from the DSN and ESA antennas. Soon after deployment, the spacecraft was tumbling and entered safe mode. The mission team recovered the spacecraft and after four tracking passes, we solved for a first ephemeris that was sent to the DSN for better tracking of the spacecraft. After propagating this first ephemeris solution, we determined that we avoided impact with a margin of a few hundred km from the lunar surface. More tracking data over the next few days allowed for a more refined orbit solution predicting a periselene altitude of 406 km and a lunar eclipse lasting 36.5 minutes. Therefore, BioSentinel operators avoided any correction maneuvers on the trajectory and successfully tracked and guide the spacecraft. The spacecraft performed a nominal lunar flyby which provided the pertinent energy to achieve a final Earth-trailing heliocentric orbit. Over the course of two weeks, the mission operators corroborated that the subsystems were functioning as expected after the lunar eclipse and the large ΔV incurred. Science operations started once the mission achieved the nominal orbit in Deep Space. This paper discusses in detail the BioSentinel flight performance, as well as the challenges and lessons learned prior to and during this CubeSat mission.

Andres Dono Perez↗

Space Programs Summary No. 37-42, Volume III FOR the Period September 1, 1966 to October 31, 1966. Deep Space Network

The Deep Space Network (DSN), established by the NASA Office of Tracking and Data Acquisition, is under the system management and technical direction of JPL. The DSN is responsible for two-way communications with unmanned spacecraft travelling from approximately 10,000 miles from Earth to interplanetary distances. Tracking and data-handling equipment to support these missions is provided. Present facilities permit simultaneous control of a newly launched spacecraft and a second one already in flight. In preparation for the increased number of U.S. activities in space, a capability is being developed for simultaneous control of either two newly launched spacecraft plus two in flight, or four spacecraft in flight. Advanced communications techniques are being implemented to make possible obtaining data from, and tracking spacecraft to, planets as far out in space as Jupiter.

NAVIGATION AND GUIDANCE↗

Navigation Performance of the BioSentinel Deep Space CubeSat Mission

The BioSentinel mission was recently launched aboard the SLS launch vehicle (LV) as part of the Artemis- 1 campaign. The BioSentinel navigation team successfully tracked and guided the spacecraft through a lunar gravity assist to its destination Earth-trailing heliocentric orbit. This 6U CubeSat carries live yeast cells to analyze the effects of radiation at large distances from Earth, becoming the first biological payload in Deep Space. Prelaunch activities included mission design updates, orbit determination rehearsals and the development of a tracking schedule in coordination with the Artemis-1 payload office and the Deep Space Network (DSN). An important influence on the trajectories of Artemis I secondaries was the uncertainty associated with deployment from the Interim Cryogenic Propulsion System (ICPS), the upper stage of the SLS LV. The ICPS was rotating at a rate of 1 rpm; there was also an uncertainty in the spin axis attitude, which translated into an unknown clock angle of deployment. The variability in this angle and magnitude of deployment implied the existence of a non-negligible risk of a lunar impact, which was evaluated for various potential launch dates. We present the results of Monte Carlo analyses and compute the pertinent maneuvers to avoid it. In addition, we present a comparison with the actual deployment once the mission launched by reconstructing our trajectory with tracking data. On November 16th 2022 BioSentinel successfully deployed from ICPS and the navigation team started to receive 2-way Doppler and Sequential Ranging data from the DSN. We processed early data to try to obtain a first ephemeris using Initial Orbit Determination (IOD) methods such as the least squares. Soon after deployment, the spacecraft was tumbling and entered safe mode, creating a period where the tracking data were sparse. The mission team recovered the spacecraft and after four tracking passes, we solved for a first ephemeris that was sent to the DSN for better tracking of the spacecraft. After propagating this first ephemeris solution, we determined that we avoided impact with a margin of a few hundred km from the lunar surface. More tracking data over the next few days (from DSN as well as ESA antennas) allowed for a more refined orbit solution predicting a periselene altitude of 406 km and a lunar eclipse lasting 36.5 minutes. Therefore, BioSentinel operators aborted any correction maneuvers. This periselene altitude also gave us the necessary energy to achieve a heliocentric orbit. The next challenge was due to the necessary adjustments in our orbit determination method due to the large energy boost resulting from the lunar flyby. After a series of tracking passes we were able to get a nominal solution that resulted into a stable trajectory. This paper discusses in detail the navigation performance using the X-band IRIS transponder, as well as the challenges and lessons learned prior to and during this deep space, CubeSat mission.

Andres Dono Perez↗

Recommendations Emerging from an Analysis of NASA's Deep Space Communications Capacity

During 2016-2017, NASA’s Space Communications and Navigation (SCaN) Office chartered a study of Deep Space Network (DSN) communications capacity relative to projected future-mission demand over the next 30 years. In this paper, we briefly describe the methodology used to analyze capacity vs. demand over such a broad timeframe, summarize key findings emerging from the analysis, and discuss the associated recommendations. Performing the analysis entailed: identifying key factors shaping the anticipated future mission set, identifying several alternative future mission set scenarios consistent with these factors, and then analyzing each mission set scenario in terms of required antenna capacity, downlink and uplink capabilities, and spectrum as a function of time. On the basis of these aggregate requirements, DSN loading simulations were then conducted that examined how well each of the postulated mission sets could load up onto the the DSN’s “in-plan” architecture. To the extent that capacity shortfalls emerged during these baseline simulations, architectural solutions to the shortfalls were then postulated and tested via additional simulations. In general, the trend analyses and baseline loading simulations indicated a significant progression in challenges over the next three decades. In the current decade, the DSN appeared to be operating very close to capacity. The first human exploration mission and its secondary payload launch opportunities for cubesats traveling beyond GEO contributed to this loading. As a consequence, the main challenge appeared to be managing peak assetcontention periods. In the next decade, the DSN continued to operate close to capacity but also began transitioning to more frequent human mission support. Upgrading for, and operating, a human-rated system while continuing to meet robotic mission customer requirements emerged as the key challenge. In the 2030’s and beyond, simulations suggested a need for fundamentally new capability and capacity. The high data rates and long link distances characteristic of human Mars exploration drove requirements far beyond what is currently “in plan.” The key challenge then became determining the most cost-effective combination of RF and optical assets for communicating with the postulated human Mars assets while still providing for the needs of all the other missions across the solar system. Various link budget, visibility, and loading analyses ultimately suggested that the human Mars exploration demands of the 2030’s could best be addressed with two cross-linked RF-optical areostationary relays (or an areostationary relay and deep space habitat) providing a dual “trunk link” to an array of 2-to-3 additional 34m beam waveguide antennas and an ~8.5m optical antenna at each DSN Complex. The dual “trunk link” would enable the same amount of total data return to Earth as a single trunk link at twice the data rate, but with only half the required array size on the ground, assuming use of Multiple Spacecraft Per Antenna (MSPA) techniques. MSPA techniques, including a Multiple Uplink Per Antenna (MUPA) technique currently under investigation, also showed promise for reducing asset contention in the decades prior to human Mars exploration.

Lee, Carlyn-Ann↗