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All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Guidance system operations plan for manned LM earth orbital and lunar missions using program luminary 1E. Section 2: Data links

Data links for the guidance system of manned lunar module orbital and lunar missions are presented. Subjects discussed are: (1) digital uplink to lunar module, (2) lunar module liftoff time increment, (3) lunar module contiguous block update, (4) lunar module scatter update, (5) lunar module digital downlink, and (6) absolute addresses for update program.

Hamilton, M. H.↗
NASA NTRS1972

Apollo guidance, navigation and control: Guidance system operations plans for manned LM earth orbital and lunar missions using Program COLOSSUS 3. Section 7: Erasable memory programs

Erasable-memory programs (EMPs) designed for the guidance computers used in the command (CMC) and lunar modules (LGC) are described. CMC programs are designated COLOSSUS 3, and the associated EMPs are identified by a three-digit number beginning with 5. LGC programs are designated LUMINARY 1E, and the associated EMPs are identified, with one exception, by a three-digit number beginning with 1. The exception is EMP 99. The EMPs vary in complexity from a simple flagbit setting to a long and intricate logical structure. They all, however, cause the computer to behave in a way not intended in the original design of the programs; they accomplish this off-nominal behavior by some alteration of erasable memory to interface with existing fixed-memory programs to effect a desired result.

Hamilton, M. H.↗
NASA NTRS2015

Lander Technologies

Since 2006 NASA has been formulating robotic missions to the lunar surface through programs and projects like the Robotic Lunar Exploration Program, Lunar Precursor Robotic Program, and International Lunar Network. All of these were led by NASA Marshall Space Flight Center (MSFC). Due to funding shortfalls, the lunar missions associated with these efforts, the designs, were not completed. From 2010 to 2013, the Robotic Lunar Lander Development Activity was funded by the Science Mission Directorate (SMD) to develop technologies that would enable and enhance robotic lunar surface missions at lower costs. In 2013, a requirements-driven, low-cost robotic lunar lander concept was developed for the Resource Prospector Mission. Beginning in 2014, The Advanced Exploration Systems funded the lander team and established the MSFC, Johnson Space Center, Applied Physics Laboratory, and the Jet Propulsion Laboratory team with MSFC leading the project. The lander concept to place a 300-kg rover on the lunar surface has been described in the New Technology Report Case Number MFS-33238-1. A low-cost lander concept for placing a robotic payload on the lunar surface is shown in figures 1 and 2. The NASA lander team has developed several lander concepts using common hardware and software to allow the lander to be configured for a specific mission need. In addition, the team began to transition lander expertise to United States (U.S.) industry to encourage the commercialization of space, specifically the lunar surface. The Lunar Cargo Transportation and Landing by Soft Touchdown (CATALYST) initiative was started and the NASA lander team listed above is partnering with three competitively selected U.S. companies (Astrobotic, Masten Space Systems, and Moon Express) to develop, test, and operate their lunar landers.

Chavers, Greg↗
NASA NTRS2008

The NASA Lunar Impact Monitoring Program

We have a fruitful observing program underway which has significantly increased the number of lunar impacts observed. We have done initial test shots at the Ames Vertical Gun Range obtained preliminary luminous efficiency values. More shots and better diagnostics are needed to determine ejecta properties. We are working to have a more accurate ejecta. environment definition to support lunar lander, habitat, and EVA design. Data also useful for validation of sporadic model at large size range.

Suggs, Rob↗
NASA NTRS2008

The Moon is a Planet Too: Lunar Science and Robotic Exploration

The first decades of the 21st century will be marked by major lunar science and exploration activities. The Moon is a witness to 4.5 billion years of solar system history, recording that history more completely and more clearly than any other planetary body. Lunar science encompasses early planetary evolution and differentiation, lava eruptions and fire fountains, impact scars throughout time, and billions of years of volatile input. I will cover the main outstanding issues in lunar science today and the most intriguing scientific opportunities made possible by renewed robotic and human lunar exploration. Barbara is a planetary scientist at NASA s Marshall Space Flight Center. She studies meteorites from the Moon, Mars and asteroids and has been to Antarctica twice to hunt for them. Barbara also works on the Mars Exploration Rovers Spirit and Opportunity and has an asteroid named after her. She is currently helping the Lunar Precursor Robotics Program on the Lunar Mapping and Modeling Project, a project tasked by the Exploration System Mission Directorate (ESMD) to develop maps and tools of the Moon to benefit the Constellation Program lunar planning. She is also supporting the Science Mission Directorate s (SMD) lunar flight projects line at Marshall as the co-chair of the Science Definition Team for NASA s next robotic landers, which will be nodes of the International Lunar Network, providing geophysical information about the Moon s interior structure and composition.

Cohen, Barbara↗
NASA NTRS2015

Lunar Impact Flash Locations from NASA's Lunar Impact Monitoring Program

Meteoroids are small, natural bodies traveling through space, fragments from comets, asteroids, and impact debris from planets. Unlike the Earth, which has an atmosphere that slows, ablates, and disintegrates most meteoroids before they reach the ground, the Moon has little-to-no atmosphere to prevent meteoroids from impacting the lunar surface. Upon impact, the meteoroid's kinetic energy is partitioned into crater excavation, seismic wave production, and the generation of a debris plume. A flash of light associated with the plume is detectable by instruments on Earth. Following the initial observation of a probable Taurid impact flash on the Moon in November 2005,1 the NASA Meteoroid Environment Office (MEO) began a routine monitoring program to observe the Moon for meteoroid impact flashes in early 2006, resulting in the observation of over 330 impacts to date. The main objective of the MEO is to characterize the meteoroid environment for application to spacecraft engineering and operations. The Lunar Impact Monitoring Program provides information about the meteoroid flux in near-Earth space in a size range-tens of grams to a few kilograms-difficult to measure with statistical significance by other means. A bright impact flash detected by the program in March 2013 brought into focus the importance of determining the impact flash location. Prior to this time, the location was estimated to the nearest half-degree by visually comparing the impact imagery to maps of the Moon. Better accuracy was not needed because meteoroid flux calculations did not require high-accuracy impact locations. But such a bright event was thought to have produced a fresh crater detectable from lunar orbit by the NASA spacecraft Lunar Reconnaissance Orbiter (LRO). The idea of linking the observation of an impact flash with its crater was an appealing one, as it would validate NASA photometric calculations and crater scaling laws developed from hypervelocity gun testing. This idea was dependent upon LRO finding a fresh impact crater associated with one of the impact flashes recorded by Earth-based instruments, either the bright event of March 2013 or any other in the database of impact observations. To find the crater, LRO needed an accurate area to search. This Technical Memorandum (TM) describes the geolocation technique developed to accurately determine the impact flash location, and by association, the location of the crater, thought to lie directly beneath the brightest portion of the flash. The workflow and software tools used to geolocate the impact flashes are described in detail, along with sources of error and uncertainty and a case study applying the workflow to the bright impact flash in March 2013. Following the successful geolocation of the March 2013 flash, the technique was applied to all impact flashes detected by the MEO between November 7, 2005, and January 3, 2014.

Moser, D. E.↗
NASA NTRS2020

A Flexible Lunar Architecture for Exploration (FLARE) Supporting NASA’s Artemis Program

The Flexible Lunar Architecture for Exploration (FLARE) is a concept to deliver four crew to the lunar surface for a minimum of seven days and then return them safely to Earth. FLARE can be implemented whenever the component vehicles are operational. FLARE was developed as an alternative to NASA’s Human Landing System (HLS) reference architecture from the Design Analysis Cycle (DAC) #2 created in 2019. The DAC2 guidelines required utilization of the Gateway vehicle in a Near- Rectilinear Halo Orbit (NRHO). Instead, FLARE chooses a Low Lunar Frozen Polar Orbit (LLFPO) for lunar rendezvous of components, and an optional Gateway vehicle. The LLFPO provides a stable orbit that overflies the south pole every 2 h, ensuring easy access to the lunar surface for surface aborts with a much lower propellant requirement than NRHO. The minimum FLARE concept uses one Space Launch System (SLS) launch, one Orion, one European Service Module (ESM), and one human lander (launched on commercial vehicle(s)). FLARE adds the SpaceTug, based upon the mature and successful ULA “Common” Centaur Upper Stage vehicle, with modifications to create an Earth-Moon transfer vehicle. In the FLARE baseline mission, the SpaceTug provides propulsion needed to return the Orion + ESM from LLFPO to Earth. The SpaceTug also provides propulsion to deliver the separate human lander components – the Descent Element (DE) and the Ascent Element (AE) - from Low Earth Orbit (LEO) to LLFPO. The SLS Block 1 then launches the Orion + ESM and completes a rendezvous with the mated DE + AE components in LLFPO. FLARE offers optional phases beyond the baseline mission. The SpaceTug can deliver components of the planned Gateway, including the Power and Propulsion Element (PPE) and the Habitable and Logistics Outpost (HALO), to LLFPO. FLARE provides an option to deliver precursor equipment to the lunar surface to enhance and extend the human mission. With these components, including an inflatable habitation module and airlock, individual crew mobility vehicle(s), an In-Situ Resource Utilization (ISRU) demonstration, and science and technology experiments, the crew can explore and conduct science on the lunar surface for up to 14 days.

Moon 2024↗
NASA NTRS2012

NASA's Robotic Lunar Lander Development Program

NASA Marshall Space Flight Center and the Johns Hopkins University Applied Physics Laboratory have developed several mission concepts to place scientific and exploration payloads ranging from 10 kg to more than 200 kg on the surface of the moon. The mission concepts all use a small versatile lander that is capable of precision landing. The results to date of the lunar lander development risk reduction activities including high pressure propulsion system testing, structure and mechanism development and testing, and long cycle time battery testing will be addressed. The most visible elements of the risk reduction program are two fully autonomous lander flight test vehicles. The first utilized a high pressure cold gas system (Cold Gas Test Article) with limited flight durations while the subsequent test vehicle, known as the Warm Gas Test Article, utilizes hydrogen peroxide propellant resulting in significantly longer flight times and the ability to more fully exercise flight sensors and algorithms. The development of the Warm Gas Test Article is a system demonstration and was designed with similarity to an actual lunar lander including energy absorbing landing legs, pulsing thrusters, and flight-like software implementation. A set of outdoor flight tests to demonstrate the initial objectives of the WGTA program was completed in Nov. 2011, and will be discussed.

Ballard, Benjamin W.↗
NASA NTRS1992

Lunar Resource Mapper/Lunar Geodetic Scout program status

Presentation on the Lunar Resource Mapper/Lunar Geodetic Scout (LRM/LGS) program status. Topics covered include the LEXWG Lunar Observer science measurement priorities, space exploration initiative priorities, the question of why a lunar orbiting mission is attractive to the Space Exploration Initiative (SEI), instrument selection, major milestones, and the organization of the LRM/LGS Program Office.

Mike Conley↗
NASA NTRSDate not supplied

Investigating Low-Altitude Constellations of Ad-Hoc Lunar PNT System for Distributed Spacecraft Autonomy

In this study, we examine a low-altitude Lunar Position, Navigation, and Timing (LPNT) constellations and the localization performance of Centralized Extended Kalman Filter (CEKF) and Decentralized Extended Kalman Filter (DEKF) algorithms. The primary investigation involves a 100-node swarm operating at a 100 km altitude, in contrast to previous studies that examined a 21-node asset in a frozen-orbit at 5,500 km. The autonomous operation of large-scale swarm is based on two-way Inter-Satellite Link (ISL) measurements, which involve pseudoranges and relative velocities among swarm nodes. We perform a numerical assessment of the two filtering approaches, utilizing ‘fully sampled’ measurements from all available assets as well as ‘two ISL’ measurements where each spacecraft is restricted to only two antennas. This research includes an analysis of CEKF under 2-ISL constraints and evaluates the performance of DEKF in a 100-node swarm, which has not been explored in previous studies. In addition, we examine the impact of increasing the sampling frequency for DEKF, showing that the update cycle can be shortened from a 10-minute interval. A novel approach for ‘2-ISL limited’ DEKF will also be introduced, using a matching formulation that exhaustively enumerates all potential matches. This study provides valuable insights into large-scale distributed swarm operations, considering various filter configurations, sampling frequencies, matching strategies, and scalability of CEKF and DEKF for low-altitude LPNT applications. The Lunar PNT technology plays a key role in providing reliable and robust navigation services on the Moon's surface and the South pole, where the primary Lunar missions are planned. To support upcoming Lunar missions, including small satellites from NASA's Commercial Lunar Payload Services program, the Lunar PNT system must be adaptable to smaller platforms like CubeSats. Driven by the growing involvement of public and private exploration partnerships, the traditional low Earth orbit missions are shifting to beyond geosynchronous orbit [1]. These upcoming missions aim to foster a sustainable and innovative exploration program, in collaboration with commercial and international partners, to facilitate human expansion throughout the solar system and return new knowledge and opportunities to Earth [2]. As part of this trend, there are increasing efforts to utilize science missions in Lunar orbit to develop a non-dedicated and ad-hoc PNT network system. Two traditional approaches, the Deep Space Network (DSN) and the weak signal Global Positioning System (GPS), are established deep-space navigation technologies for missions beyond the geosynchronous orbit. Beginning in 1958, the DSN was developed to communicate with the Explorer 1 spacecraft based on the use of radiometric tracking in spacecraft navigation [3]. The DSN is capable of providing nearly unfettered coverage to spacecraft beyond low-Earth orbit (LEO), however, increased space mission volume has created concerns about future expectations of DSN usage for spacecraft navigation [4]. For cislunar mission applications, the position accuracy using DSN achieves 100 m (3σ) with at least three geometrically diverse ground stations when using radiometric tracking alone [5]. The DSN's dependence on Earth-based ground stations restricts its operational capabilities to periods of Earth visibility. This limitation, coupled with its poor localization performance, renders the DSN unsuitable for future lunar missions that demand continuous tracking and precise positioning. To satisfy the increasing requirements of DSN in Lunar applications, spacecrafts are also required to improve their onboard antenna power and efficiency of the transmission. However, there is an important aggregate cost trade between adding capabilities to every spacecraft and adding to a capacity on the ground that serves multiple spacecraft [6]. A weak GPS system can provide PNT service while the user spacecraft is bound to the Moon, leveraging a single, steerable high gain antenna with the relatively narrow beam which includes all the sources in its field of view [7]. However, the higher the altitude the receiver is above the GPS constellations, the poorer and the weaker are the relative geometry and the received signal powers, respectively, leading to a significant navigation accuracy reduction [8]. The transmitted power becomes weaker with increasing distance from the Earth as well as signals tracked from one of the side lobes of the GPS antenna pattern. As a results, the number of visible satellites and relative geometric condition of the GPS satellites at very high altitude drops dramatically and reduces the navigation solution accuracy. Therefore, the weak GPS system is also not an ideal way to provide PNT service to upcoming Lunar missions when considering its limited geometric condition and the recued navigation accuracy. Another navigation approach on the Moon is being developed, similar to the Global Navigation Satellite System (GNSS) on Earth, aiming to offer navigation service with continuous 24/7 coverage across the entire Lunar surface. For example, lunar communications relay and navigation systems (LCRNS) by NASA and Lunar navigation satellite systems (LNSS) by JAXA are designed to serve as dedicated Position, Navigation, and Timing (PNT) systems for the Moon. However, designing a dedicated LNSS and PNT service involves additional challenges, which are unique to the lunar environment, including limited payload capacity for the CubeSat platform, i.e., the size, weight, and power (SWaP) of the onboard clock, limited lunar ground monitoring stations, and limited financial investment as compared to the legacy Earth-GPS [9]. NASA’s focus on utilizing CubeSat platforms on the Moon leads to an alternative Lunar navigation platform that leverages the existing Lunar science and exploration assets. The small satellites used in Lunar missions can be used to create a low-cost, autonomous, ad-hoc, and on-demand mission-centric Lunar PNT swarm capable of providing PNT services to these low-cost lunar missions [10]. As upcoming Lunar missions will often operate at low-altitude about 30 km to 100 km for scientific observations and mapping purposes, the low-altitude orbital constellations could be employed to create an ad-hoc Lunar PNT system. However, several issues must be addressed, such as the instability of these orbits, which often require maintenance or are only suitable for short-duration missions, operating for fewer than 90 days. Additionally, at an altitude of 100 km, the satellites have a limited period during which they are above the horizon and capable of providing PNT service to users. The implementation of a non-dedicated, ad-hoc Lunar navigation constellation facilitates on-demand PNT services. A preliminary study of ad-hoc Lunar PNT system was conducted using 21 spacecraft in 5,5000 km altitude frozen orbits to test its feasibility and a basic performance of orbital asset localization among ad-hoc Lunar constellations in small satellites format [10]. These swarm assets are designed for autonomous localization with minimal Earth interaction, reducing dependency on bandwidth and ground resources. The design in [10] demonstrated the feasibility of a decentralized PNT approach, specifically employing a DEKF approach for state estimation, which helps minimize onboard operating costs. The DEKF method distributes computation across individual satellites, which lightens the computational load while maintaining accuracy in orbit ephemeris and clock offsets, similar to centralized systems [11]. In a follow-on study [12], each spacecraft was limited to 2 communications antennae, forcing the selection of measurements and scheduling spacecraft activities to perform the measurements. A matching algorithm is implemented to select the best measurements and schedule position estimation updates. The decentralized localization performance is also investigated with increasing levels of network degradation for swarm assets considering the impact of intermittent and permanent communication failure, to demonstrate the robustness and fidelity of the decentralized Lunar PNT service [13]. This study confirmed that the ad-hoc PNT constellations in frozen orbit are highly robust and resilient to communication failures. However, unlike frozen orbit swarm assets, the low-altitude satellites have a limited ground view at an altitude of 100 km, where the ad-hoc Lunar constellation consists of 98 low-altitude satellites, evenly distributed across seven circular polar orbital planes, alongside two satellites in a frozen orbit at an altitude of 5,500 km (Figure 1). Therefore, the number of satellites visible to ground users is significantly limited in low-altitude orbit constellations. As each visibility of a spacecraft remains intact for only a few ticks before it moves out of the field of view, the ground user encounters challenges in maintaining continuous navigation service, resulting in sparse availability and provision of Lunar PNT system. Consequently, service availability is primarily restricted to the Lunar South Pole region (Figure 2). Given these limitations and concerns, the localization performance of low-altitude swarm assets will be assessed in this study. We focus on the investigation of the localization performance of low-altitude swarm assets and ground users near the Lunar South Pole. The overall flow of the Lunar PNT simulation incorporates the DEKF approach of asset localization and the weighted least-squares approach in user localization (Figure 3). The autonomous Lunar PNT simulation is primarily implemented in MATLAB, where the DEKF based on the matching scheduler is implemented with Google’s OR-tools as a model builder and Gurobi optimization tool as a backend solver. The General Mission Analysis Tool (GMAT) is utilized to generate ephemeris data for swarm assets, and accounts for satellite orbital details, mass, and perturbations like solar radiation pressure and drag coefficients. Each ephemeris dataset is produced in the Moon International Celestial Reference Frame (ICRF) inertial coordinate system. For state estimation, the distributed swarm assets rely on two-way Inter-Satellite Link (ISL) measurements, which involve tracking pseudoranges and relative velocities between visible satellites and anchor nodes during each observation. Numerical evaluations of the decentralized localization process are conducted to demonstrate the feasibility of the low-altitude PNT system in providing reliable navigation services. The main approach involves using DEKF and CEKF to localize 100 satellites in low-altitude constellations, where the CEKF is implemented to serve as a baseline for comparing the performance of distributed algorithms. In both cases, we evaluate ‘fully sampled’ measurements from all available assets, and ‘two ISL’ measurements when spacecraft are constrained to have only two antennas. We test four estimation techniques: CEKF fully sampled, CEKF two ISL, DEKF fully sampled, and DEKF two ISL filters. As the DEKF update cycle is comprised of network setup, communication, and computations, a global broadcast network and 2-way ISL network setup will take from 4 to 6 minutes as maximum [12]. In this simulation, the DEKF update cycle is set to 10 minutes, including a 4-minute latency for obtaining and computing the actual measurement updates. We experiment an increased update cycle to demonstrate the feasibility and evaluate the impact on localization performance using various tuning values for measurement noise covariances (Figures 4 and 5). By comparing centralized and decentralized approaches using a matching algorithm, we analyze the influence of cross-correlation factors in the covariance matrix, assuming 100% reliability of all assets and measurements. The increased frequency and the adjustments of tuning parameters reveal distinct error patterns between the two scenarios. The localization accuracy of the swarm assets and ground users is assessed by taking the median error across 100 assets and one ground user (84.9°S, 137.5°E) over 7-day simulation period (Table 1). Since the user localization accuracy is significantly affected by the performance of the swarm assets, it is crucial to maintain high localization accuracy within the swarm. This study will continue to explore decentralized filtering for autonomous LPNT operations, with further investigation of an 'iterative' matching approach which enumerates every valid matching pair, planned for the following month.

Yeji Kim↗
NASA NTRS1992

The Quickest, Lowest-cost Lunar Resource Assessment Program: Integrated High-tech Earth-based Astronomy

Science and technology applications for the Moon have not fully kept pace with technical advancements in sensor development and analytical information extraction capabilities. Appropriate unanswered questions for the Moon abound, but until recently there has been little motivation to link sophisticated technical capabilities with specific measurement and analysis projects. Over the last decade enormous technical progress has been made in the development of (1) CCD photometric array detectors; (2) visible to near-infrared imaging spectrometers; (3)infrared spectroscopy; (4) high-resolution dual-polarization radar imaging at 3.5, 12, and 70 cm; and equally important (5) data analysis and information extraction techniques using compact powerful computers. Parts of each of these have been tested separately, but there has been no programmatic effort to develop and optimize instruments to meet lunar science and resource assessment needs (e.g., specific wavelength range, resolution, etc.) nor to coordinate activities so that the symbiotic relation between different kinds of data can be fully realized. No single type of remotely acquired data completely characterizes the lunar environment, but there has been little opportunity for integration of diverse advanced sensor data for the Moon. Two examples of technology concepts for lunar measurements are given. Using VIS/near-IR spectroscopy, the mineral composition of surface material can be derived from visible and near-infrared radiation reflected from the surface. The surface and subsurface scattering properties of the Moon can be analyzed using radar backscattering imaging.

Pieters, Carle M.↗