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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2009

Hazard Detection Methods for Lunar Landing

The methods and experiences from the Apollo Program are fundamental building blocks for the development of lunar landing strategies for the Constellation Program. Each of the six lunar landing Apollo missions landed under near ideal lighting conditions. The astronauts visually performed terrain relative navigation while looking out of windows, and were greatly aided by external communication and well lit scenes. As the LM approached the landing site, the astronauts performed visual hazard detection and avoidance, also under near-ideal lighting conditions. The astronauts were looking out of the windows trying to the best of their ability to avoid rocks, slopes, and craters and find a safe landing location. NASA has expressed a desire for global lunar access for both crewed and robotic sortie lunar exploration missions (Cook, 2007) (Dale, 2006). Early NASA architecture studies have identified the lunar poles as desirable locations for early lunar missions. These polar missions have less than ideal lighting conditions and will significantly affect the way a crewed vehicle plans to land at such locales. Consequently, a variety of hazard identification methods should be considered for use by the crew to ensure a high degree of safety. This paper discusses such identification methods applicable to the poorly lit polar lunar environment, better ensuring global access for the soon to be designed Lunar Lander Vehicle (LLV).

Brady, Tye↗
NASA NTRSDate not supplied

Implementation of a Six Degree of Freedom Precision Lunar Landing Algorithm Using Dual Quaternion Representation

In this study, a powered descent guidance algorithm using a unit dual quaternion represen- tation of the vehicle dynamics is implemented in a high-fidelity simulation and on representative flight hardware. This Dual-Quaternion Guidance (DQG) algorithm is applied to the precision lunar landing problem which levies complex constraints upon the trajectory, including state triggered attitude constraints to enable terrain-relative navigation and hazard detection as well as real-time requirements for landing site re-designation. The investigation explores DQG’s usefulness as a mission design tool as well as a real-time guidance algorithm and defines real-time performance requirements for the hazard detection and avoidance (HDA) re-targeting phase of precision lunar landing. The experiment is presented in two parts. First, DQG is implemented within a high-fidelity Monte Carlo simulation to tune the algorithm’s parameters for the simulated vehicle, to refine the mission design, and to develop guidance update timing requirements to perform the HDA maneuver. DQG generates trajectories online for the divert which are tracked by the vehicle’s inner-loop controllers to the targeted landing site. Second, DQG is run on representative hardware to demonstrate real-time operation through a divert maneuver. These results allow for rapid, flexible, optimal mission design satisfying complex constraints, and for the definition of real-time performance requirements for the HDA operations inherent in precision lunar landing. The HDA divert maneuver is found to require guidance trajectory updates in less than three seconds. DQG is found to be too slow to meet this update timing on the descent and landing computer (DLC) in its current implementation. DQG running on alternative hardware can meet the update rate requirement. Algorithm implementation improvements are also recommended which are expected to speed up computation sufficiently to meet requirements on the DLC.

GN&C↗
NASA NTRS2010

Lunar Landing Operational Risk Model

Characterizing the risk of spacecraft goes beyond simply modeling equipment reliability. Some portions of the mission require complex interactions between system elements that can lead to failure without an actual hardware fault. Landing risk is currently the least characterized aspect of the Altair lunar lander and appears to result from complex temporal interactions between pilot, sensors, surface characteristics and vehicle capabilities rather than hardware failures. The Lunar Landing Operational Risk Model (LLORM) seeks to provide rapid and flexible quantitative insight into the risks driving the landing event and to gauge sensitivities of the vehicle to changes in system configuration and mission operations. The LLORM takes a Monte Carlo based approach to estimate the operational risk of the Lunar Landing Event and calculates estimates of the risk of Loss of Mission (LOM) - Abort Required and is Successful, Loss of Crew (LOC) - Vehicle Crashes or Cannot Reach Orbit, and Success. The LLORM is meant to be used during the conceptual design phase to inform decision makers transparently of the reliability impacts of design decisions, to identify areas of the design which may require additional robustness, and to aid in the development and flow-down of requirements.

Mattenberger, Chris↗