Autonomous Navigation for Crewed Lunar Missions with DBAN

With the recent push for a crewed Lunar mission to descend, land, and ascend from the Moon, there is a need for real-time position, velocity, and attitude knowledge of a Lunar spacecraft. Proposed approaches to achieve this include the use of weak-signals received from GPS and Deep Space Network (DSN)-aided measurements, but these require significant hardware development and active tracking from multiple ground stations. Additionally, these solutions may be unavailable during close approach and landing. This paper extends the previously published relative Doppler-based positioning scheme (Law of Cosines – LOC) and an absolute Doppler-based scheme (Conic Doppler Localization – CDL) with the aid of range measurements, an inertial measurement unit (IMU), and a star tracker to create the Doppler Based Autonomous Navigation (DBAN) architecture. DBAN allows for real-time, autonomous positioning with as few as one Lunar orbiter and a reference station on the surface of the Moon. LOC is a relative navigation architecture that converts Doppler measurements into Doppler-based range measurements with the aid of a reference station and at least one satellite. In addition, CDL is an absolute navigation architecture that converts Doppler measurements into conic sections for angle-based positioning. These architectures allow for localization with solely Doppler measurements that can be made using existing hardware, with significant performance improvements when including range measurements. However, the existing drawback with these architectures is that they require a static user; they can be biased through the Doppler shift produced by a moving user. With the aid of range measurements, an IMU, a star tracker, and a filter, DBAN can correct these biases and provide continuous Doppler-based navigation. In this analysis, the Lunar Gateway and the Lunar Relay Satellite (LRS) were used with a pre-existing reference station located on the south pole of the Moon to localize a user during orbit, descent, and landing. A surface constraint assumption was optionally implemented using the knowledge of the altitude of the user as a constraint. Satellite ephemeris, velocity, and external and internal measurement errors were modeled as Gaussian variables and embedded in Monte Carlo simulations to increase fidelity. An Extended Kalman Filter (EKF) was used due to the non-linear effects during intervals of high user dynamics. With DBAN, the positioning accuracy after more than 20 hours of integration approached 80 m at landing with a maximum error of about 800 m during a period of no external measurements and high dynamics (during low Lunar orbit). This was a significant improvement from directly filtering the range and Doppler measurements or from only dead reckoning. Just as with position, velocity error also increased with user dynamics, reaching a maximum of around 1 m/s with around 20 cm/s of error at landing. Finally, attitude error ranged from 1–2 arcseconds throughout the entire trajectory. Ultimately, the DBAN architecture can provide real-time position, velocity, and attitude knowledge with a minimal navigation infrastructure. DBAN can enable autonomous navigation for future crewed and uncrewed missions on other planets.