Flight Dynamics and Navigation Technologies

Scope Title:

Advanced Techniques for Trajectory Design and Optimization

Scope Description:

NASA seeks innovative advancements in trajectory design and optimization for cislunar and interplanetary missions, including:

• Low-thrust trajectories in a multibody dynamical environment.
• Multiple small-body (moons, asteroids, and comets) exploration.
• Solar sail trajectories.
• Anytime abort (return to Earth) for crewed spaceflight missions (e.g., from the lunar surface, or a near rectilinear halo orbit).

NASA is seeking innovative techniques for optimization of trajectories that account for:

• System uncertainties (i.e., navigation errors, maneuver execution errors, missed maneuvers, etc.).
• Spacecraft and operational constraints (power, communications, thermal, etc.).
• Trajectory constraints imposed by navigational, crew safety, and/or science observation requirements.

Trajectory design for complex space missions can take weeks or months to generate a single reference trajectory. Providing algorithms and software to speed up this process will enable missions to explore trade spaces more fully and more quickly respond to changes in the mission. Thus, NASA seeks innovative techniques that allow rapid exploration of mission design trade spaces, address high-dimensionality optimization problems (i.e., multimoon/multibody tours; low thrust), and/or provide initial guesses that can be used to improve convergence of complex trajectories in existing tool suite.

Proposals that leverage state-of-the-art capabilities already developed by NASA, or that can  integrate with those packages, such as the General Mission Analysis Tool (GMAT); Collocation Stand Alone Library and Toolkit (CSALT); Copernicus; Evolutionary Mission Trajectory Generator (EMTG); Mission Analysis Low-Thrust Optimization (MALTO); Mission Analysis, Operations, and Navigation (MONTE); and Optimal Trajectories by Implicit Simulation (OTIS), or other available software tools are highly encouraged. Proposers who contemplate licensing NASA technologies are highly encouraged to coordinate with the appropriate NASA technology transfer offices prior to submission of their proposals.

Disclaimer: Technology Available (TAV) subtopics may include an offer to license NASA Intellectual Property (NASA IP) on a nonexclusive, royalty-free basis, for research use under the SBIR award. When included in a TAV subtopic as an available technology, use of the available NASA IP is strictly voluntary. Whether or not a firm uses available NASA IP within their proposal effort will not in any way be a factor in the selection for award.

Expected TRL or TRL Range at completion of the Project: 2 to 6

Primary Technology Taxonomy:

• Level 1 15 Flight Vehicle Systems
• Level 2 15.2 Flight Mechanics

Desired Deliverables of Phase I and Phase II:

• Research
• Analysis
• Prototype
• Software

Desired Deliverables Description:

Phase I research should demonstrate technical feasibility, with preliminary software being delivered to NASA, as well as show a plan towards Phase II integration.

Phase II new technology development efforts shall deliver components at Technology Readiness Levels (TRLs) 5 to 6 to NASA, with mature algorithms and software components complete and preliminary integration and testing in an operational environment.

State of the Art and Critical Gaps:

Trajectory optimization techniques that account for, or even minimize, spacecraft and trajectory uncertainties are not widely available in current trajectory design software. The incorporation of these uncertainties into optimization frameworks that also include constraints imposed by spacecraft, operational, and science requirements would result in more robust trajectory designs. Moreover, trajectory design for complex missions or in sensitive dynamical regimes is frequently a human in-the-loop process that relies upon the intuition of experienced engineers. While this approach can suffice for the design of a single reference trajectory, it is highly inefficient for processes that necessitate the generation of thousands of trajectories, e.g., the exploration of a trade space or a missed thrust analysis. Processes that reduce the person-hours required to generate optimal trajectories within these complex trade spaces are needed. 

Relevance / Science Traceability:

Relevant missions include:

• Artemis—Lunar Gateway.
• Europa Clipper.
• Lucy.
• Psyche.
• Dragonfly.
• Roman Space Telescope.
• Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging (DAVINCI).
• Venus Emissivity Radio science, InSAR, Topography, and Spectroscopy (VERITAS).
• SmallSat and CubeSat class missions, such as Lunar IceCube.

References:

Scope Title:

Autonomous Onboard Spacecraft Navigation, Guidance, and Control

Scope Description:

Future human and robotic lunar and Mars missions require landing within a 50-m radius of the desired surface location to land near features of interest or other vehicles. Also, future exploration and On-orbit Servicing, Assembly and Manufacturing (OSAM) missions require rendezvous, formation flying, proximity operations, noncooperative object capture, and coordinated spacecraft operations in Earth orbit, cislunar space, libration orbits, and deep space. Furthermore, the next generation of human spaceflight missions in cislunar space (e.g., Artemis, Human Landing Systems (HLS), and Gateway) will require very complex trajectories with a wide range of possible abort and contingency scenarios that must be accounted for. These missions all require a high degree of autonomy.

The subtopic seeks advancements in autonomous, onboard trajectory design, spacecraft navigation and guidance algorithms and software for application in Earth orbit, lunar, cislunar, libration, and deep space to reduce dependence on ground-based tracking, and orbit determination, including:

• Advanced, computationally tractable algorithms and software for safe, precision landing on small bodies, planets, and moons, including real-time 3D terrain mapping, autonomous hazard detection and avoidance, and terrain relative navigation algorithms that leverage active lidar-based imaging, or methods with limited or no reliance on a priori maps.
• Computer vision techniques to support optical/terrain relative navigation and/or spacecraft rendezvous/proximity operations in low and variable lighting conditions, including artificial intelligence/machine learning (AI/ML) algorithms.
• Onboard relative and proximity navigation (relative position, velocity and attitude, and/or pose) algorithms and software, which support cooperative and collaborative space operations.
• Autonomous onboard mission design and trajectory planning for crewed missions. In a loss-of-comm scenario in cislunar space, potentially complex multi-burn transfer trajectory solutions will be required in order to return to Earth without inputs from ground controllers. This may include onboard trajectory optimization, analytical or semi-analytical methods to seed optimization or guidance algorithms, as well as machine learning (ML) algorithms to produce results from a complex abort space.
• High accuracy (1-meter level), local positioning concepts for surface operations (i.e., astronauts and rovers on the moon) within a local area of up to 10 km.

Proposals that leverage state-of-the-art capabilities already developed by NASA, or that can integrate with those packages, such as the Goddard Enhanced Onboard Navigation System (GEONS), Navigator NavCube, autoNGC, core Flight System (cFS), AutoNav, or other available NASA hardware and software tools are highly encouraged. Proposers who contemplate licensing NASA technologies are highly encouraged to coordinate with the appropriate NASA technology transfer offices prior to submission of their proposals.

Disclaimer: Technology Available (TAV) subtopics may include an offer to license NASA Intellectual Property (NASA IP) on a nonexclusive, royalty-free basis, for research use under the SBIR award. When included in a TAV subtopic as an available technology, use of the available NASA IP is strictly voluntary. Whether or not a firm uses available NASA IP within their proposal effort will not in any way be a factor in the selection for award.

Expected TRL or TRL Range at completion of the Project: 2 to 6

Primary Technology Taxonomy:

• Level 1 17 Guidance, Navigation, and Control (GN&C)
• Level 2 17.2 Navigation Technologies

Desired Deliverables of Phase I and Phase II:

• Research
• Analysis
• Prototype
• Software

Desired Deliverables Description:

Phase I research should demonstrate technical feasibility, determine expected system performance and assess computational resource requirements, with preliminary software being delivered to NASA, as well as show a plan towards Phase II integration.

Phase II new technology development efforts shall deliver components at the TRL 5 to 6 level to NASA, with mature algorithms and software components with complete and preliminary integration and testing in an operational environment.

State of the Art and Critical Gaps:

Currently navigation, guidance, and control functions rely heavily on the ground for tracking data, data processing, and decision making. As NASA operates farther from Earth and performs more complex operations requiring coordination between vehicles, round-trip communication time delays make it necessary to reduce reliance on Earth for navigation solutions and maneuver planning. For example, spacecraft that arrive at a planetary surface may have limited ground inputs and no surface or orbiting navigational aids, and may require rapid navigation updates to feed autonomous trajectory guidance updates and control. NASA currently has only limited navigational, trajectory, and attitude flight control technologies that permit fully autonomous approach, proximity operations, and landing without navigation support from Earth-based resources.

Relevance / Science Traceability:

Relevant missions and projects include:

• Artemis (Lunar Gateway, Orion Multi-Purpose Crew Vehicle, HLS).
• OSAM.
• LunaNet.
• Autonomous Navigation, Guidance, and Control (autoNGC).

These complex, deep space missions require a high degree of autonomy. The technology produced in this subtopic enables these kinds of missions by reducing or eliminating reliance on the ground for navigation and maneuver planning. The subtopic aims to reduce the burden of routine navigational support and communications requirements on network services, increase operational agility, and enable near real-time replanning and opportunistic science. It also aims to enable classes of missions that would otherwise not be possible due to round-trip light time constraints.

References:

1. Goddard Enhanced Onboard Navigation System (GEONS): https://software.nasa.gov/software/GSC-14687-1, https://goo.gl/TbVZ7G
2. Navigator: http://itpo.gsfc.nasa.gov/wp-content/uploads/gsc_14793_1_navigator.pdf
3. NavCube: https://goo.gl/bdobb9
4. core Flight System (cFS): https://cfs.gsfc.nasa.gov/
5. On-orbit Servicing, Assembly, and Manufacturing (OSAM): https://nexis.gsfc.nasa.gov/osam/index.html
6. LunaNet: https://esc.gsfc.nasa.gov/news/_LunaNetConcept
7. autonomous Navigation, Guidance and Control (autoNGC): https://techport.nasa.gov/view/94817
8. Bhaskaran, S., “Autonomous Navigation for Deep Space Missions,” Proceedings of the SpaceOps 2012 Conference, AIAA 20212-1267135, Stockholm, Sweden, June 11-15, 2012.

Scope Title:

Conjunction Assessment Risk Analysis (CARA)

Scope Description:

The U.S. Space Surveillance Network currently tracks more than 22,000 objects larger than 10 cm, and the number of objects in orbit is steadily increasing, which causes an increasing threat to spacecraft in the near-Earth environment. The NASA CARA team is responsible for protecting NASA assets from collision with other objects by submitting owner/operator trajectory information on the protected spacecraft, including predicted maneuvers, to the 18th Space Control Squadron (SPCS) at Vandenberg Space Force Base in California. The trajectories are screened against the catalog of space objects, and information about predicted close approaches between NASA satellites and other space objects is sent back to CARA. CARA then determines the risk posed by those events and works with the spacecraft owner/operator to develop an appropriate mitigation strategy. The ability to perform risk assessment more accurately and rapidly will improve space safety for all near-Earth operations and cislunar (Earth + 2 million kilometers) operations.

In addition, there are also an increasing number of spacecraft orbiting other solar system bodies, such as the Moon and Mars. The corresponding risk assessment process to CARA for satellites in deep space is called MADCAP (Multimission Automated Deepspace Conjunction Assessment Process). These spacecraft are not tracked by the Space Surveillance Network, and all trajectory data for them must be provided by their respective navigation teams, which compute orbits based on tracking data obtained from a suitable deep space antenna operated by NASA’s Deep Space Network and from some foreign space agencies.

Because neither CARA nor MADCAP produces ephemeris data for the NASA-protected assets or the catalogued objects, the orbit determination aspect of the problem is not of interest in this subtopic. Additionally, CARA does not control the screening process and is therefore not looking for solutions in that area. Only the conjunction assessment (CA) risk assessment aspect is within the scope of this call.

This subtopic seeks innovative technologies to improve the risk assessment process, including the following specific areas (see Reference 1 for the 2020 NASA Technology Taxonomy (TX) areas TX05.6.4, TX10.1.4, TX10.1.5, and TX10.1.6):

• Alternative risk assessment techniques and parameters. The Probability of Collision (Pc) is the standard metric for assessing collision likelihood. Its use has substantial advantages over the previous practice of using standoff distances. The Pc considers the uncertainties in the predicted state estimates at the time of closest approach (TCA) so it provides a probabilistic statement of risk. A number of concerns with the use of the Pc, however, have been identified, including “diluted” probability (see Reference 2) and “false confidence” (see Reference 3). Special consideration will be directed to approaches that explicitly avoid extreme conservatism but instead enable taking prudent measures, at reasonable cost, to improve safety of flight, without imposing an undue burden on mission operations and the balancing required to improve safety while allowing largely unencumbered space mission operations.
• Innovative approaches to characterizing the uncertainties in the hard-body radius and object covariances (see Reference 4) that account for all the uncertainties in the inputs to the Pc calculation in order to emerge with a range or Probability Density Function (PDF) of possible collision probabilities, or some other parameter that takes account of these uncertainties. Although NASA is open to entirely different constructs and approaches, CARA does not control the orbit determination process and cannot change the state estimation/propagation and uncertainty representation paradigm.
• New or improved techniques or algorithms that use information available in a Conjunction Data Message (CDM) and historical information of a given space object to predict event severity in either a singular event or an ensemble risk assessment for contiguous close approaches for several events including those using artificial intelligence (AI) or machine learning (ML) are sought.
• New or improved techniques are sought to increase the speed of risk analysis of conjunction events that also retain the ability to screen the planned trajectory via the 18 SPCS process. A semiautomatic approach for risk analysis could involve preliminary analysis on the severity levels of a given conjunction as a form of triage.
• Novel, efficient methods for locating the minimum distance and location of the closest approach between objects with reduced run times and/or increased accuracy. Due to limitations in the availability of formal trajectory uncertainty covariances for spacecraft in orbit at Mars and the Moon, MADCAP currently analyzes conjunctions by comparing minimum orbit distances, among other attributes. For spacecraft with noncoplanar orbits, the minimum orbit distance is located at the orbit crossing locations, which are relatively simple to find. However, the search for minimum orbit distances is less straightforward when the orbits are coplanar.  MADCAP currently utilizes a brute force algorithm to find the minimum orbit distance locations. Solutions that assume elliptical orbits are acceptable, but those which allow for hyperbolic orbits are preferred. An efficient method that applies universally to noncoplanar orbits could also be beneficial if quick and accurate, as it would eliminate the need to check for coplanarity and switch algorithms.
• Conjunction event visualizations are an effective method of improving understanding of conjunction geometry. To date, these visualizations have been set up manually when conjunctions of interest arise. It would be beneficial to be able to automatically produce an image showing the visualization of a close approach (state information in various coordinate/reference frames, covariance, variable hard-body radius information, approach angles, and other pertinent information using data from CDMs) when high-risk conjunctions are reported. These images would be sent out with email warnings of the high-risk event.

Disclaimer: Technology Available (TAV) subtopics may include an offer to license NASA Intellectual Property (NASA IP) on a nonexclusive, royalty-free basis, for research use under the SBIR award. When included in a TAV subtopic as an available technology, use of the available NASA IP is strictly voluntary. Whether or not a firm uses available NASA IP within their proposal effort will not in any way be a factor in the selection for award.

See section 1.6 for additional details on TAV requirements.

Expected TRL or TRL Range at completion of the Project: 2 to 5

Primary Technology Taxonomy:

• Level 1 05 Communications, Navigation, and Orbital Debris Tracking and Characterization Systems
• Level 2 05.6 Networking and Ground Based Orbital Debris Tracking and Management

Desired Deliverables of Phase I and Phase II:

• Research
• Analysis
• Prototype
• Software

Desired Deliverables Description:

Phase I research should demonstrate technical feasibility, with preliminary software being delivered to NASA, as well as show a plan toward Phase II integration.

Phase II new technology development efforts shall deliver components at the TRL 5 to 6 level to NASA, with mature algorithms and software components complete and preliminary integration and testing in a quasi-operational environment.

State of the Art and Critical Gaps:

The number of conjunction events is expected to continually increase with the increase of resident space objects from large constellations, the ability to track smaller objects, the increasing numbers of CubeSat/SmallSats, and the proliferation of space debris. Thus, CARA and MADCAP have identified the following challenges to which we are actively looking for solutions: efficient ways to perform conjunction analysis and assessments such as methods for bundling events and performing ensemble risk assessment, middle-duration risk assessment (longer duration than possible for discrete events but shorter than decades-long analyses that use gas dynamics assumptions), improved conjunction assessment (CA) event risk evolution prediction, ML/AI applied to CA risk assessment parameters and/or event evolution. The decision space for collision avoidance relies on not only the quality of the data (state and covariance) but also the tools and techniques for CA.

Relevance / Science Traceability:

This technology is relevant and needed for all human spaceflight and robotic missions in the near-Earth, cislunar, lunar, and other solar system body environments. The ability to perform CARA more accurately will improve space safety for all operations involving orbiting spacecraft, improve operational support by providing more accurate and longer-term predictions, and reduce propellant usage for collision avoidance maneuvers.

References:

1. 2020 NASA Technology Taxonomy: 2020_nasa_technology_taxonomy_lowres.pdf
2. Alfano, Salvatore. "A numerical implementation of spherical object collision probability." The Journal of the Astronautical Sciences 53, no. 1 (2005): 103-109.
3. Balch, Michael Scott, Martin, Ryan, and Ferson, Scott, "Satellite conjunction analysis and the false confidence theorem." Proceedings of the Royal Society A 475, no. 2227 (2019): 20180565.
4. Frigm, Ryan C., Hejduk,Matthew D., Johnson, Lauren C., and Plakalovic, Dragan, "Total probability of collision as a metric for finite conjunction assessment and collision risk management." Proceedings of the Advanced Maui Optical and Space Surveillance Technologies Conference, Wailea, Maui, Hawaii. 2015.
5. NASA Conjunction Assessment Risk Analysis (CARA) Office: https://www.nasa.gov/conjunction-assessment
6. NASA Orbital Debris Program Office: https://www.orbitaldebris.jsc.nasa.gov/
7. Newman, Lauri, K., "The NASA robotic conjunction assessment process: Overview and operational experiences," Acta Astronautica, Vol. 66, Issues 7-8, Apr-May 2010, pp. 1253-1261, https://www.sciencedirect.com/science/article/pii/S0094576509004913
8. Newman, Lauri K., et al., "Evolution and Implementation of the NASA Robotic Conjunction Assessment Risk Analysis Concept of Operations." (2014). https://ntrs.nasa.gov/search.jsp?R=20150000159
9. Newman, Lauri K., et al., “NASA Conjunction Assessment Risk Analysis Updated Requirements Architecture,” AIAA/AAS Astrodynamics Specialist Conference, Portland, ME, AAS 19-668, (2019).
10. Office of Safety and Mission Assurance, “NASA Procedural Requirements for Limiting Orbital Debris and Evaluating the Meteoroid and Orbital Debris Environments,” NPR 8715.6, https://nodis3.gsfc.nasa.gov/displayDir.cfm?t=NPR&c=8715&s=6B
11. NASA Interim Directive (NID) 7120.132: Collision Avoidance for Space Environment Protection: NID_7120_132_.pdf (nasa.gov)
12. NASA Spacecraft Conjunction Assessment and Collision Avoidance Best Practices Handbook: OCE_50.pdf (nasa.gov)
13. Consultative Committee for Space Data Systems (CCSDS) Recommended Standard for Conjunction Data Messages: https://public.ccsds.org/Pubs/508x0b1e2c2.pdf
14. Tarzi, Zahi, Berry, David, and Roncoli, Ralph “ An Updated Process for Automated Deepspace Conjunction Assessment,” Paper AAS 14-373, 25th International Symposium on Space Flight Dynamics, Munich, Germany, October 2015.