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Deep Space Mission Systems lack the capability to provide end to end tracing of mission data products. These data products are simple products such as telemetry data, processing history, and uplink data.
The advent of deep space small spacecraft, as exemplified by the Mars Cubesat One (MarCO), Lunar Trailblazer, Janus, the Escape and Plasma Acceleration and Dynamics Explorers (EscaPADE), and the thirteen Artemis 1 missions, opens the possibility that a much larger number of deep space spacecraft may be launched over the next 10 years and beyond. While scientifically exciting, the prospect of a (much) larger mission suite raises significant challenges for the current approach to ground stations and mission operations. We have been investigating an integrated approach for ground stations and missions operations to enable new modes of operation while maintaining the capabilities of the current operational techniques. This integrated approach is built around three core capabilities: (1) A queuing antenna that enables monitoring the status of a much larger number of spacecraft, and allows spacecraft to transmit requests for telemetry with NASA’s Deep Space Network (DSN); (2) a flexible scheduling system that expands the current DSN scheduling services to enable allocating time on DSN antennas in near real-time; and (3) a cloud-based ground data system that can be spun up and down according to how tracks are assigned by the flexible scheduling system. We shall show that an 18 meter DSN queuing antenna equipped with cyrogenic receivers would enable use of the DSN Demand Access Service for small spacecraft throughout the inner Solar System, thus providing service to a large mission suite. We first discuss the architecture of the queuing antenna and its supporting systems, including, for instance, the service required to generate the schedule for the queueing antenna (which dictates how it slews to monitor multiple spacecraft in a day of operations). Next, we describe the signaling scheme used to encode a request, which is inherited from the already operational DSN Beacon Tone Service, and describe two alternative ways to detect the incoming tone at the ground station, one based on maximum likelihood estimation (MLE), and another one based on Fast-Fourier Transfer (FFT) processing. We then use these results to estimate the maximum range at which a request can be reliably detected as a function of the spacecraft and ground station communication capabilities. Finally, the last part of this part of this paper briefly describes the prototyping effort undertaken at Morehead State University (MSU) and JPL to demonstrate the viability of this new DSN demand access. In particular, we describe the suite of tests conducted using MSU’s 21 meter ground station to validate its use a queuing antenna.
Future missions to deep space, such as those to the outer planets (Jupiter, Saturn, etc.), which would rely on solar photovoltaic power, would need extremely large solar arrays to produce sufficient power for their operations because solar intensity is so low at those locations. Hence any additional power that would be needed for thermal control is extremely limited. Previous deep space missions like Juno (to Jupiter) required almost 200 W of electrical power for thermal control. This is prohibitively large for many future mission concepts, and leads to them needing very large solar arrays. For Saturn, where the solar flux is 1/4th the flux at Jupiter, this would entail an extremely large increase in the solar array size to accommodate the need for thermal survival power, which would be prohibitively large in size and mass, and very expensive. Hence there is a need to come up with a thermal architecture and design options that would not need such prohibitively large thermal power levels. One solution relies on harvesting the pre-existing waste heat from all the heat dissipation that would be present from operation of electronics, instruments, etc. for their own functionality. For example, for a generic Saturn mission, the various electronics would already dissipate about 200 Watts of heat that is simply "thrown away" to space from the spacecraft surfaces. The amount of thermal power that would be required for the safe thermal control of components within the spacecraft in deep space would be roughly of this magnitude for this class of spacecraft. So it makes good sense to try to harvest the waste heat and employ it to maintain the temperatures of all the components within their allowable limits. In particular, propulsion systems typically need to be kept above their freezing limits, around room temperature (15 C). Electronics needs to be kept typically above -40 C and batteries above -20 C. The next question becomes how to harvest this waste heat and direct it to the components that would need it for their survival. The proposed system utilizes a mechanically pumped, single phase fluid loop to pick up the waste heat from components attached to this loop's tubing and then directed to a thermal flask that has tubing attached to it. The thermal flask is cylindrically shaped and contains essentially all systems and components in the spacecraft within it, with the exception of the solar array, antennae, thrusters and various apertures of instruments, etc. to allow them an unobstructed view of space. Waste heat from the heat-dissipating components warms up the fluid and is carried to the flask surface and deposited on it via the fluid loop's flow. The entire flask is covered with Multi-Layered Insulation (MLI) to minimize the heat loss from the flask and allow it to remain warm. Hence the flask essentially creates a thermal environment within which the spacecraft components reside. The temperature of the components within the flask is then essentially the same as the temperature of the flask. This approach could be a very enabling feature for deep space missions. This paper describes the approach utilized for this thermal architecture, along with its mechanical and implementation aspects. Additionally it will compare and contrast this approach with the more conventional solutions utilized earlier.
Planetary and deep space mission guidance and control technology requirements
Operation of deep space missions requires stable frequency references and clocks to perform several mission critical functions. These references are used in generating the telecommunication links to maintain communications between earth and spacecraft, in generating accurate doppler, range, and very long baseline interferometry (VLBI) observables for determining the spacecraft's time varying position, and to generate on-board timing information for clocking out timed commands and time tagging instrument data. In addition, science applications exist, particularly those utilizing radio instrumentation, which can require additional functions and levels of performance. The design necessary to support these functions affects both the spacecraft and the ground tracking stations. This paper provides a brief description of these functions and some of the key requirements needed to support them.
Providing the necessary exercise capability to protect crew health for deep space missions will bring new sets of engineering and research challenges. Exercise has been found to be a necessary mitigation for maintaining crew health on‐orbit and preparing the crew for return to earth's gravity. Health and exercise data from Apollo, Space Lab, Shuttle, and International Space Station missions have provided insight into crew deconditioning and the types of activities that can minimize the impacts of microgravity on the physiological systems. The hardware systems required to implement exercise can be challenging to incorporate into spaceflight vehicles. Exercise system design requires encompassing the hardware required to provide mission specific anthropometrical movement ranges, desired loads, and frequencies of desired movements as well as the supporting control and monitoring systems, crew and vehicle interfaces, and vibration isolation and stabilization subsystems. The number of crew and operational constraints also contribute to defining the what exercise systems will be needed. All of these features require flight vehicle mass and volume integrated with multiple vehicle systems. The International Space Station exercise hardware requires over 1,800 kg of equipment and over 24 m3 of volume for hardware and crew operational space. Improvements towards providing equivalent or better capabilities with a smaller vehicle impact will facilitate future deep space missions. Deep space missions will require more understanding of the physiological responses to microgravity, understanding appropriate mitigations, designing the exercise systems to provide needed mitigations, and integrating effectively into vehicle design with a focus to support planned mission scenarios. Recognizing and addressing the constraints and challenges can facilitate improved vehicle design and exercise system incorporation.
Concept studies for deep space missions are typically time-consuming and costly, given the variety of missions and uniqueness of each design. Yet, in an increasingly cost-constrained environment, it is critical to identify the most scientifically valuable and cost-effective designs early in the design process. Modeling is an integral part in helping to identify the most desirable design option. While some spacecraft design models currently exist for Earth-orbiting spacecraft, there has been less success with deep space missions. Instead, these missions require a modified design and modeling approach to enable the same construction of a comprehensive, yet credible, mission tradespace. This paper presents an approach for efficiently constructing such a mission tradespace. In addition to a proposed design and modeling approach, three case study missions are presented including a solar orbiter, a Europa orbiter, and a near-Earth asteroid (NEA) sample return mission.
Deep space exploration is concerned with the study of natural phenomena in the solar system with the aid of measurements made at spacecraft on deep space missions. Deep space communication refers to communication between earth and spacecraft in deep space. The Deep Space Network is an earth-based facility employed for deep space communication. It includes a network of large tracking antennas located at various positions around the earth. The goals and achievements of deep space exploration over the past 20 years are discussed along with the broad functional requirements of deep space missions. Attention is given to the differences in space loss between communication satellites and deep space vehicles, effects of the long round-trip light time on spacecraft autonomy, requirements for the use of massive nuclear power plants on spacecraft at large distances from the sun, and the kinds of scientific return provided by a deep space mission. Problems concerning a deep space link of one billion miles are also explored.
Continuously powered deep space vehicle orbit determination, discussing state estimation accuracy and use of continuous data filtering
Continuously powered deep space vehicle orbit determination, discussing state estimation accuracy and use of continuous data filtering
This paper will discuss the development, adaptation, and operation of the MGDS in providing low-cost mission-unique information systems for testing and operating JPL deep space missions.
Two very different deep space exploration missions--Mars Exploration Rover and Cassini--have made use of distributed operations for their science teams. In the case of MER, the distributed operations capability was implemented only after the prime mission was completed, as the rovers continued to operate well in excess of their expected mission lifetimes; Cassini, designed for a mission of more than ten years, had planned for distributed operations from its inception. The rapid command turnaround timeline of MER, as well as many of the operations features implemented to support it, have proven to be conducive to distributed operations. These features include: a single science team leader during the tactical operations timeline, highly integrated science and engineering teams, processes and file structures designed to permit multiple team members to work in parallel to deliver sequencing products, web-based spacecraft status and planning reports for team-wide access, and near-elimination of paper products from the operations process. Additionally, MER has benefited from the initial co-location of its entire operations team, and from having a single Principal Investigator, while Cassini operations have had to reconcile multiple science teams distributed from before launch. Cassini has faced greater challenges in implementing effective distributed operations. Because extensive early planning is required to capture science opportunities on its tour and because sequence development takes significantly longer than sequence execution, multiple teams are contributing to multiple sequences concurrently. The complexity of integrating inputs from multiple teams is exacerbated by spacecraft operability issues and resource contention among the teams, each of which has their own Principal Investigator. Finally, much of the technology that MER has exploited to facilitate distributed operations was not available when the Cassini ground system was designed, although later adoption of web-based and telecommunication tools has been critical to the success of Cassini operations.
Two very different deep space exploration missions—Mars Exploration Rover and Cassini—have made use of distributed operations for their science teams. In the case of MER, the distributed operations capability was implemented only after the prime mission was completed, as the rovers continued to operate well in excess of their expected mission lifetimes; Cassini, designed for a prime mission of four years, had planned for distributed operations from its inception. The rapid command turnaround timeline of MER, as well as many of the operations features implemented to support it, have proven to be conducive to distributed operations. These features include: a single science team leader during the tactical operations timeline, highly integrated science and engineering teams, processes and file structures designed to permit multiple team members to work in parallel to deliver sequencing products, web-based spacecraft status and planning reports for team-wide access, and near-elimination of paper products from the operations process.
Unique requirements imposed on deep space telecommunications, such as operation at extreme ranges, have historically led to high cost, one-of-a-kind spacecraft telecommunications systems. Yet future deep space misssions must fit within severe cost, mass and power constraints. JPL recently completed a study to find ways of reducing telecommunicaitons cost for future deep space missions. They identified and evaluated alternative telecommunicaitons systems architectures capable of satisfying these needs and design constraints. Future missions are expected to occur more frequently than in the past. The study recommends that a standard deep space transponder be developed. It also recommends spacecraft power amplifier and antenna development efforts.
An overview is presented of deep space missions being planned for launch on the Space Shuttle, one element of the Space Transportation System (STS). A comparison is made between mission requirements and the planned capabilities of the STS. Finally, a potential evolution of the STS in order to accomodate these missions with adequate mass margins is discussed.
The deep space mission operations process has changed over the years, but mission operations are perceived to be overly expensive.
A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth independence and autonomy of mission operations. Here we present an overview of AI/ML architecture to support deep space mission goals, developed with leaders in the field. First, we focus on the fundamental biological research that supports our understanding of physiological responses to spaceflight, and we describe current efforts to support AI/ML research including data standardization and data engineering through maximally open and FAIR (findable, accessible, interoperable, reusable) databases and the generation of AI-ready datasets for reuse and analysis. We also discuss remote data management frameworks for research data as well as environmental and health data that are generated during deep space missions. We highlight several research projects that leverage data standardization and management for fundamental biological discovery to uncover the complex effects of space travel on living systems. Next, we provide an overview of cutting-edge AI/ML approaches that can be integrated to support remote monitoring and analysis during deep space missions, including generative models and large language models to learn the underlying biomedical patterns and predict outcomes or answer questions during off world medical scenarios. We also describe current AI/ML methods to support this research and monitoring through automated cloud-based labs which enable limited human intervention and closed-loop experimentation in remote settings. These labs could support mission autonomy by analyzing environmental data streams, and would be facilitated through in situ analytics capabilities to avoid sending large raw data files through low bandwidth communications. Finally, in the context of deep space missions with limited communications or access to medical advice from Earth, we describe a solution for integrated, real-time mission biomonitoring across hierarchical levels from continuous environmental monitoring, to wearables and point-of-care devices, to molecular and physiological monitoring. We introduce a precision space health system that will ensure that the future of space health is predictive, preventative, participatory and personalized.
The control of deep mission spacecraft by computing and signaling to the spacecraft a series of propulsive, velocity correction commands which maneuver the craft to its desired course is examined. The technical elements of the global navigation system (measurement, communications, computation, and propulsion) are described. The ground-computing facilities used to navigate spacecraft on deep space missions consist of computer and software systems used to compute orbits from radio tracking and on-board optical image data (radio, Doppler, and VLBI measurements). The accuracy of these measurements is evaluated, and the modeling of the data is discussed. Examples concerned with the navigation of Voyager and Galileo are presented.