Space Traffic Management (STM) Architecture

information technology and software
Space Traffic Management (STM) Architecture (TOP2-294)
Highly scalable, decentralized, open-architecture data exchange platform for STM
Space is becoming increasingly congested due to rising numbers of on-orbit satellites and debris objects. Despite growing awareness of the orbital debris problem, recent developments such as launch ride sharing, growth in availability of small launch vehicles, and particularly large scale satellite constellation deployments, are dramatically increasing on-orbit congestion. Uncontrolled growth will severely affect future space operations. NASA Ames has developed a novel patent-pending technology known as Space Traffic Management (STM) which provides a robust framework for on-orbit coordination of activities to enhance the safety, stability, and sustainability of operations in the space environment. The STM system is critical for ensuring that the expanding orbital population operates safely and efficiently, avoiding collisions and radio-frequency interference while still facilitating widespread space operations in an increasingly congested space environment. Additionally, it meets the objectives associated with the transition of civil STM from the Department of Defense to a civilian entity.

The Technology
As ever larger numbers of spacecraft seek to make use of Earth's limited orbital volume in increasingly dense orbital regimes, greater coordination becomes necessary to ensure these spacecraft are able to operate safely while avoiding physical collisions, radio-frequency interference, and other hazards. While efforts to date have focused on improving Space Situational Awareness (SSA) and enabling operator to operator coordination, there is growing recognition that a broader system for Space Traffic Management (STM) is necessary. The STM architecture forms the framework for an STM ecosystem, which enables the addition of third parties that can identify and fill niches by providing new, useful services. By making the STM functions available as services, the architecture reduces the amount of expertise that must be available internally within a particular organization, thereby reducing the barriers to operating in space and providing participants with the information necessary to behave responsibly. Operational support for collision avoidance, separation, etc., is managed through a decentralized architecture, rather than via a single centralized government-administered system. The STM system is based on the use of standardized Application Programming Interfaces (API) to allow easier interconnection and conceptual definition of roles to more easily allow suppliers with different capabilities to add value to the ecosystem. The architecture handles basic functions including registration, discovery, authentication of participants, and auditable tracking of data provenance and integrity. The technology is able to integrate data from multiple sources.
Proposed STM architecture
  • Improved space traffic management systems are becoming a necessity to protect commercial and other space assets as low Earth orbit congestion increases.
  • Provides standardized roles, an open-access architecture, and Application Programming Interfaces (APIs) to interface between the participants and reduce barriers to entry.
  • Enables a common operating picture for space situational awareness.
  • Enables any interested entity to join the system and be discoverable as a new participant in the system.
  • System is designed to grow as the number and variety of participants grows.
  • Enables automation between participants to make the system sustainable and scalable.
  • Provides safe operations with cooperative management between diverse set of participants.
  • Reduces the STM burden for small owner/operators, and makes it easy to be a good citizen.
  • Flexible enough to accommodate future regulatory requirements, including potential for mandated maneuvers under certain conditions

  • The Space Traffic Management (STM) Service Supplier (S3)
  • Space Situational Awareness Supplier (SSA)
  • Conjunction Assessment Supplier (CAS)
  • Supplemental Data Supplier
  • Owner/Operator (O/O) - already commercialized, STM will allow seamless interaction between operators
  • Universities and research institutions
Technology Details

information technology and software
Similar Results
Flying drone
Unmanned Aerial Systems (UAS) Traffic Management
NASA Ames has developed an Autonomous Situational Awareness Platform system for a UAS (ASAP-U), a traffic management system to incorporate Unmanned Aerial Systems (UASs) into the National Airspace System. The Autonomous Situational Awareness Platform (ASAP) is a system that combines existing navigation technology (both aviation and maritime) with new procedures to safely integrate Unmanned Aerial Systems (UASs) with other airspace vehicles. It uses a module called ASAP-U, which includes a transmitter, receivers, and various links to other UAS systems. The module collects global positioning system GPS coordinates and time from a satellite antenna, and this data is fed to the UAS's flight management system for navigation. The ASAP-U module autonomously and continuously sends UAS information via a radio frequency (RF) antenna using Self-Organized Time Division Multiple Access (SOTDMA) to prevent signal overlap. It also receives ASAP data from other aircraft. In case of transmission overload, priority is given to closer aircraft. Additionally, the module can receive weather data, navigational aid data, terrain data, and updates to the UAS flight plan. The collected data is relayed to the flight management system, which includes various databases and a navigation computer to calculate necessary flight plan modifications based on regulations, right-of-way rules, terrain, and geofencing. Conflicts are checked against databases, and if none are found, the flight plan is implemented. If conflicts arise, modifications can be made. The ASAP-U module continuously receives and transmits data, including UAS data and data from other aircraft, to detect conflicts with other aircraft, terrain, weather, and geofencing. Based on this information, the flight management system determines the need for course adjustments and the flight control system executes them for a safe flight route.
Spacecraft to Remove Orbital Debris
An approach to mitigating the creation of additional orbital debris is to remove the sources of future medium debris by actively removing large spent objects from congested orbits. NASA has introduced the ADRV, an efficient and effective solution to remove large debris from LEO such as spent rocket bodies and non-functional satellites. The concept yields a single use, low-cost, lightweight, high mass fraction vehicle that enables the specific removal of large orbital debris (1000 - 4000 kg mass, 200 - 2000 km altitude, and 20 98-degree inclination). The ADRV performs rendezvous, approach, and capture of non-cooperative tumbling debris objects, maneuvering of the mated vehicle, and controlled, targeted reposition or deorbit of the mated vehicle. Due to its small form factor, up to eight ADRVs can be launched in a single payload, enabling high impact orbital debris removal missions within the same inclination group. Three key technologies were developed to enable the ADRV: - 1) The spacecraft control system (SCS) is a guidance, navigation, and control system that provides vehicle control during all phases of a mission; - (2) The debris object characterization system (DOCS) characterizes movement and capture of non-cooperative targets; and - (3) The capture and release system (CARS) allows the vehicle to capture and mate with orbital debris targets. These technologies can improve the current state-of-the-art capabilities of automated rendezvous and docking technology significantly for debris objects with tumbling rates up to 25 degrees per second. This approach leverages decades of spaceflight experience while automating key mission areas to reduce cost and improve the likelihood of success.
Urban Air Mobility
Near-Real Time Verification and Validation of Autonomous Flight Operations
NASA's Extensible Traffic Management (xTM) system allows for distributed management of the airspace where disparate entities collaborate to maintain a safe and accessible environment. This digital ecosystem relies on a common data generation and transfer framework enabled by well-defined data collection requirements, algorithms, protocols, and Application Programming Interfaces (APIs). The key components in this new paradigm are: Data Standardization: Defines the list of data attributes/variables that are required to inform and safely perform the intended missions and operations. Automated Real Time And/or Post-Flight Data Verification Process: Verifies system criteria, specifications, and data quality requirements using predefined, rule-based, or human-in-the-loop verification. Autonomous Evolving Real Time And/or Post-Flight Data Validation Process: Validates data integrity, quantity, and quality for audit, oversight, and optimization. The verification and validation process determines whether an operation’s performance, conformance, and compliance are within known variation. The technology can verify thousands of flight operations in near-real time or post flight in the span of a few minutes, depending on networking and computing capacity. In contrast, manual processing would have required hours, if not days, for a team of 2-3 experts to review an individual flight.
AVA Controller
Affordable Vehicle Avionics (AVA)
Significant contributors to the cost of launching nano- and micro-satellites to orbit are the costs of software, and Guidance, Navigation and Control (GNC) avionics systems that steer, navigate and control the launch vehicles, sequence stage separation, deploy payloads, and pass data to Telemetry. The high costs of these GNC avionics systems are due in part to the current practice of developing unique, custom, single-use hardware and software for each launch, and requiring high-precision measurements of position and attitude states. NASA Ames Research Center has developed and tested a low-cost avionics system prototype called Affordable Vehicle Avionics (AVA). AVA integrates a low-cost moderately-precise sensor suite with an advanced error-correcting software package to provide GNC for space launch vehicles in a package smaller than a multilayer sandwich (100 mm x 120 mm x 69 mm; 4in x 4.7in x 2.7in), and with a mass of less than 0.84kg (2lbs). The invention provides a common suite of avionics components and demonstration software that deliver affordable, capable GNC with flexible I/O which is applicable to a variety of nano/micro-sat launch vehicles at less than 10 percent of the cost to procure current state-of-the-art GNC avionics. Affordable Vehicle Avionics' (AVA's) approach to drastically reduce costs includes: (1) use of low-cost "tactical-grade" Commercial-off-the-Shelf MicroElectroMechanical Systems (MEMS) inertial measurement unit, wherein adequate navigation precision is achieved by fusing outputs from a Global Positioning System receiver, inertial sensors and a magnetic field vector sensor in an extended Kalman filter formulation that corrects inertial sensor biases; (2) a streamlined "cookbook" approach to define an effective process for launch vehicle developers to design, simulate, verify and support assembly, integration and testing of their SLVs, driven by high-fidelity six degrees of freedom SLV simulations and real-time hardware-in-loop tests to validate guidance, navigation and control for early test flights. Development Status: As of spring 2020, AVA has flown twice in its current configuration on a suborbital platform. Its navigation and control functions were successfully demonstrated for roll-rate control within a tight deadband onboard the first flight test, and it successfully issued attitude pointing commands to a failed reaction control subsystem and it issues issued a rocket-motor ignition command on a second flight test. To date, failure of SLV components other than AVA (e.g., electrical power) has precluded demonstration of navigation and control of an orbital or sub-orbital launch system, which remains to be demonstrated. AVA development was accomplished using a single magnetometer-based magnetic field vector sensor to provide attitude observability during free-fall (inter-stage coast periods). Therefore, the current tested AVA configuration is susceptible to magnetic/electric fields produced by other components and payloads onboard the SLV, so care must be exercised to either mount AVA well away from sources of such fields and or to incorporate magnetic/electric field barriers on field emitters if separation from emitters is inadequate. Also, licensees may wish to provide new AVA inputs from a pair of external horizon sensors to provide more accurate attitude navigation during coast phases of the SLV mission.
The touch screen of the Electronic Flight Bag allows pilots to easily use TASAR.
Traffic Aware Strategic Aircrew Requests (TASAR)
The NASA software application developed under the TASAR project is called the Traffic Aware Planner (TAP). TAP automatically monitors for flight optimization opportunities in the form of lateral and/or vertical trajectory changes. Surveillance data of nearby aircraft, using ADS-B IN technology, are processed to evaluate and avoid possible conflicts resulting from requested changes in the trajectory. TAP also leverages real-time connectivity to external information sources, if available, of operational data relating to winds, weather, restricted airspace, etc., to produce the most acceptable and beneficial trajectory-change solutions available at the time. The software application is designed for installation on low-cost Electronic Flight Bags that provide read-only access to avionics data. The user interface is also compatible with the popular iPad. FAA certification and operational approval requirements are expected to be minimal for this non-safety-critical flight-efficiency application, reducing implementation cost and accelerating adoption by the airspace user community. Awarded "2016 NASA Software of the Year"
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