The Multi-spacecraft Autonomous Positioning System (MAPS) is a networked computer navigation software developed by NASA for enabling autonomous state estimation and positioning of spacecraft through inter-spacecraft communication networks. It leverages existing communication infrastructure to perform ranging measurements via packet travel times, reducing reliance on Earth-based ground tracking stations. MAPS embeds navigation data—such as timing, position, velocity, and accuracy estimates—directly into standard data packets transmitted between spacecraft, ground stations, or other assets. By measuring the round-trip time of these packets against local clocks, spacecraft can triangulate their positions relative to multiple reference points in the network, functioning similarly to a distributed GPS but without dedicated ranging hardware.
This system addresses key challenges in deep-space operations, where traditional radiometric tracking from Earth becomes inefficient due to signal delay, limited visibility windows, and resource constraints. MAPS transforms routine communication passes into opportunistic navigation updates, supporting Earth-independent operations for robotic and human missions. It has been demonstrated in low-Earth orbit (LEO), cislunar space, and on the lunar surface, with applications extending to Mars networks and future solar-system-wide navigation.
History and Development
MAPS originated from research at NASA's Marshall Space Flight Center (MSFC) in the mid-2010s, led by developer Steven M. Anzalone and collaborators. The concept emerged amid growing concerns over the scalability of ground-based navigation for an expanding fleet of spacecraft. Early work focused on utilizing the maturing interplanetary communication relays, such as those in the Martian network involving the Mars Reconnaissance Orbiter (MRO), Mars Odyssey, and MAVEN spacecraft.
A foundational technical report published in 2016 outlined MAPS as a software-only solution compatible with various hardware platforms, emphasizing its integration with onboard estimation algorithms. Development involved agent-based simulations for orbital scenarios in Mars and LEO environments, as well as hardware-in-the-loop (HIL) testing using flight-quality radios and clocks to model timing uncertainties and propagation delays. These efforts validated the system's potential for solar-system-wide autonomy.
By 2018, MAPS underwent its first in-space validation on the International Space Station (ISS) via NASA's Space Communications and Navigation (SCaN) testbed. The experiment successfully demonstrated networked ranging using ISS communication links, confirming packet-based state estimation in a microgravity environment.
Subsequent advancements extended MAPS principles to cislunar applications through the Cislunar Autonomous Positioning System (CAPS), a derivative tailored for Moon-proximate operations. CAPS was flight-tested in 2022 aboard the CAPSTONE CubeSat mission, which validated peer-to-peer ranging in a near-rectilinear halo orbit (NRHO) around the Moon. This mission, managed by Advanced Space for NASA, used crosslinks with the Lunar Reconnaissance Orbiter (LRO) to generate onboard position and velocity estimates, maturing software for future Artemis program assets like the Lunar Gateway.
In 2024, MAPS powered the Lunar Node-1 (LN-1) experiment, a compact S-band radio beacon deployed on the lunar surface via Intuitive Machines' IM-1 Odysseus lander. Despite the lander's tilted landing near Malapert A crater on February 22, 2024, LN-1 transmitted navigation signals for 30 minutes across two sessions, enabling lock-on by NASA's Deep Space Network (DSN) antennas. The demonstration included MAPS algorithms alongside pseudo-noise (PN)-based one-way ranging for performance comparison, marking the first lunar surface test of autonomous beacon navigation.
As of 2025, ongoing work at MSFC integrates MAPS with emerging lunar relay satellites under NASA's Lunar Communications Relay and Navigation Systems (LCRNS) project, aiming for a resilient cislunar positioning infrastructure.
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Technical Principles
MAPS operates on a distributed network architecture where participating nodes—spacecraft, relays, or surface beacons—broadcast augmented packets containing:
Timestamped state vectors: Current position, velocity, and covariance estimates.
Clock synchronization data: For compensating onboard clock drifts.
Metadata: Signal strength, link quality, and error bounds.
Upon receiving a packet, a node computes the propagation delay using its local clock, yielding a one-way range measurement. Multiple such measurements from diverse nodes enable least-squares or Kalman filter-based state estimation, fusing data with onboard sensors like star trackers or inertial measurement units (IMUs).
Key innovations include:
Opportunistic ranging: No dedicated ranging tones; leverages Ka-band or S-band communication links already in use.
Scalability: Supports ad-hoc networks with 2–N nodes, improving accuracy as node density increases (e.g., <1 km precision in dense LEO swarms).
Fault tolerance: Uses trusted reference nodes (e.g., DSN or high-accuracy orbiters) for initialization and error correction.
Software modularity: Implementable via firmware updates, minimizing hardware changes.
Performance depends on factors like clock stability (target: 10^{-11} fractional frequency), orbital geometry, and link budgets. Simulations show sub-kilometer accuracy in Mars relay scenarios and meter-level in cislunar tests.
CAPS extends these principles with radiometric crosslinks for peer-to-peer Doppler and delay measurements, achieving ~100 m positioning in NRHO orbits using just 1–2 references.
Applications and Demonstrations
In-Space Demonstrations
ISS Testbed (2018): Validated core algorithms in LEO, achieving ranging via SCaN network links.
CAPSTONE/CAPS (2022–present): Ongoing operations in NRHO, demonstrating autonomous orbit determination and station-keeping navigation. Data supports Gateway risk reduction.
Martian Networks: Routinely embeds MAPS-like state broadcasts in MRO/Mars Odyssey relays for rover positioning.
Surface and Cislunar
LN-1 (2024): Lunar beacon test provided DSN-compatible signals for rover/lander geolocation, with MAPS enabling relative positioning to orbiting assets. Future deployments could form a "lunar GPS" mesh.
Broader Uses
MAPS supports formation flying, debris avoidance, and precision landing. In human exploration, it aids astronaut wayfinding on planetary surfaces. Extensions target asteroid mining swarms and outer-planet relays.
Future Prospects
NASA envisions MAPS as a backbone for the Artemis era and beyond, integrating with LCRNS satellites for continuous cislunar coverage. Enhancements include AI-driven anomaly detection and quantum clocks for sub-meter accuracy. International collaborations, such as with ESA's Moonlight initiative, could expand the network. Challenges remain in cybersecurity for distributed nodes and standardization via CCSDS protocols.
See Also
Cislunar Autonomous Positioning System
NASA's Commercial Lunar Payload Services (CLPS)
Artemis program
References
Anzalone, S. M., et al. (2016). "Multi-spacecraft Autonomous Positioning System." NASA Technical Reports Server.
NASA. (2024). "NASA to Demonstrate Autonomous Navigation System on Moon." Marshall Space Flight Center.
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