Ph.D. Thesis Defense

Mark Hartigan

(Faculty advisor: E. Glenn Lightsey)

"Performance of Lunar Radiometric Navigation Satellite Systems"

Monday, August 14

11:00 a.m. 

Guggenheim Building, Classroom 246

Abstract: 

The Moon's growing population of missions and the push towards a sustainable human presence there demand a positioning, navigation, and timing (PNT) service capable of supporting a large and dispersed user base. In response, NASA and international partners developed the LunaNet Interoperability Specifications: a network architecture to provide distributed PNT through a one-way, spread-spectrum signal constructed similarly to terrestrial Global Navigation Satellite Systems (GNSSs). Despite GNSS heritage, the lunar environment poses new challenges for system designers and users alike; this thesis identifies how lunar navigation systems will be meaningfully different from terrestrial ones in the context of PNT performance.
This work presents a detailed breakdown of pseudorange and Doppler measurement error for LunaNet-compliant systems through the lens of established GPS error analysis, yielding analytic, state-dependent error expressions for typical user measurement models. This analysis shows that orbit determination and time synchronization uncertainties for lunar satellites dominate the resulting signal errors. Because clock stability proves to be such a significant contributor, a procedure is then developed for obtaining the maximum likelihood estimate fit of a generalized clock model to the stability variances commonly used in oscillator stability analysis. These error and clock models are synthesized within a representative LunaNet user navigation scenario during powered descent and landing. A proposed five-satellite lunar constellation supplies observables to the user, and a variety of techniques are employed within an extended Kalman filter to generate real-time navigation estimates. The LunaNet constellation is shown to produce persistently biased measurements, which are compensated for with per-link bias tracking. The resulting navigation performance is shown to meet NASA's end user accuracy requirements, demonstrating a viable path toward reliable PNT for future LunaNet users.

Committee:
Dr. E. Glenn Lightsey (advisor), School of Aerospace Engineering
Dr. E. Glenn Lightsey, School of Aerospace Engineering
Dr. John Christian, School of Aerospace Engineering
Dr. Brian Gunter, School of Aerospace Engineering
Dr. Yashwanth Nakka, School of Aerospace Engineering
Dr. David Gaylor, Intuitive Machines