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As part of architecture studies and insight analysis focused on requirements development into Human Landing System lunar architecture designs, multiple studies are underway to understand the sensitivities and options for achieving high precision landing on the lunar surface. The baseline approach utilizes a combination of multiple sensors to capture autonomous state observations of the lander with respect to the lunar surface. These systems are typically constrained in terms of operational altitudes by parameters such as onboard map size, camera focus, or sensor transmitted power (for altimeter observations). While these sensor suites do enable high precision landing, they are typically very complex and expensive. For a human-rated vehicle, fault detection algorithms are needed in addition to redundant sensors drive additional design complexity. Conversely, for these early missions, mass performance is key, so extended analysis is required to identify numbers of sensors, their ideal placement, and integration algorithms. A key part of this analysis is to help identify key sensor suites and options to help alleviate this design tension. An alternate approach is to take advantage and build out in-situ assets to allow for GPS-like navigation within the lunar regime through the use of navigation references or beacons. This can be achieved through the integration of navigation services into potential relays and pre-placed lunar surface assets. This research focuses on the capability of this infrastructure to support navigation in all areas of cislunar space such as: approach to the moon, in orbit around the moon, and ascent/descent operations to the surface. An augmented state linear covariance analysis (LinCov) and navigation state covariance analysis (NavCov) tools were used to assess a variety of navigation reference locations and how they can support vehicle operations through both understanding of state uncertainties and trajectory dispersions. This research helps to supplement existing studies focused on communication link analysis by providing additional insight into specific vehicle operational scenarios that are tied closely to potential Human Landing System scenarios. Key aspect of this analysis focus on the sensitivity to state knowledge of the references, the accuracy of inter-asset measurements, and placement in support of the various scenarios.
The Mars Organic Molecule Analyzer (MOMA) is a key scientific instrument on the ExoMars Rover mission. MOMA is designed to detect and characterize organic compounds, over a wide range of volatility and molecular weight, in samples obtained from up to two meters below the martian surface. Thorough analog sample studies are required to best prepare to interpret MOMA data collected on Mars. We present here the MOMA characterization of Mars analog samples collected from an alkaline silica depositing hot spring in Yellowstone National Park, WY, USA. These samples contain microbial streamer communities composed primarily of oxygenic and anoxygenic phototrophs. Additionally, in a study focused on detection of key classes of nonvolatile organics, samples of microbial streamers and their total lipid extract (TLE) have been measured on a MOMA Engineering Test Unit (ETU) instrument using its laser desorption/ionization mass spectrometry (LDI-MS) mode. MOMA LDI-MS detected a variety of lipids and pigments in the TLE sample. Species such as chlorophyll a were also detected from the streamer sample with the help of mass isolation. The results add to the LDI-MS sample characterization database, as well as demonstrate the benefit of using mass isolation on the MOMA instrument to reveal the presence of complex organics, and potential biomarkers, preserved in a natural sample, providing guidance to the in situ analysis of surface samples during Mars operations.
In order to study the interaction with the surface, a Monte Carlo program is developed to determine the distribution with altitude as well as the global distribution of density at the surface in a single operation. The analysis presented shows that the appropriate source distribution should be Maxwell-Boltzmann flux if the particles in the distribution are to be treated as components of flux. Monte Carlo calculations with a Maxwell-Boltzmann flux source are compared with Mariner 10 UV spectrometer data. Results indicate that the presently operating models are not capable of fitting the observed Mercury exosphere. It is suggested that an atmosphere calculated with a barometric source distribution is suitable for more realistic future exospheric models.
Space system design for lunar orbit and extended operations on the lunar surface requires analysis of potential system vulnerabilities to plasma and radiation environments to minimize anomalies and assure that environmental failures do not occur during the mission. Individual environments include the trapped particles in Earth s radiation belts, solar energetic particles and galactic cosmic rays, plasma environments encountered in transit to the moon and on the lunar surface (solar wind, terrestrial magnetosheath and magnetotail, and lunar photoelectrons), and solar ultraviolet and extreme ultraviolet photons. These are the plasma and radiation environments which contribute to a variety of effects on space systems including total ionizing dose and dose rate effects in electronics, degradation of materials in the space environment, and charging of spacecraft and lunar dust. This paper provides a survey of the relevant charged particle and photon environments of importance to lunar mission design ranging from the lowest (approx.few 10 s eV) photoelectron energies to the highest (approx.GeV) cosmic ray energies.
This paper analyzes the lunar terrain effects on the signal propagation of the planned NASA lunar wireless communication and sensor systems. It is observed that the propagation characteristics are significantly affected by the presence of the lunar terrain. The obtained results indicate that the terrain geometry, antenna location, and lunar surface material are important factors determining the propagation characteristics of the lunar wireless communication systems. The path loss can be much more severe than the free space propagation and is greatly affected by the antenna height, operating frequency, and surface material. The analysis results from this paper are important for the lunar communication link margin analysis in determining the limits on the reliable communication range and radio frequency coverage performance at planned lunar base worksites. Key Words lunar, multipath, path loss, propagation, wireless.
The Arctic is one of the most important regions in the world’s oceans for understanding the impacts of a changing climate. Yet, it is also difficult to measure because of extreme weather and ice conditions. In this work, we directly compare four datasets from the Group for High-Resolution Sea Surface Temperature (GHRSST) with a NASA Saildrone deployment along the Alaskan Coast and the Bering Sea and Bering Strait. The four datasets used are the Remote Sensing Systems Microwave Infrared Optimally Interpolated (MWIR) product, the Canadian Meteorological Center (CMC) product, the Daily Optimally Interpolated Product (DOISST), and the Operational Sea Surface Temperature and Ice Analysis (OSTIA) product. Spatial sea surface temperature (SST) gradients were derived for both the Saildrone deployment and GHRSST products, with the GHRSST products collocated with the Saildrone deployment. Overall, statistics indicate that the OSTIA product had a correlation of 0.79 and a root mean square difference of 0.11 °C/km when compared with Saildrone. CMC had the highest correlation of 0.81. Scatter plots indicate that OSTIA had the slope closest to one, thus best reproducing the magnitudes of the Saildrone gradients. Differences increased at latitudes > 65°N where sea ice would have a greater impact. A trend analysis was then performed on the gradient fields. Overall, positive trends in gradients occurred in areas along the coastal regions. A negative trend occurred at approximately 60°N. A major finding of this study is that future work needs to revolve around the impact of changing ice conditions on SST gradients. Another major finding is that a northward shift in the southern ice edge occurred after 2010 with a maxima at approximately 2019. This indicates that the shift of the southern ice edge is not gradual but has dramatically increased over the last decade. Future work needs to revolve around examining the possible causes for this northward shift.
Reactor core internal components such as baffle-former bolts (BFBs) are subjected to significant mechanical stress, corrosive environment, and neutron irradiation from the reactor core during the plant operation. Over the long operation period, these conditions lead to potential degradation and of the bolts. In this work, characterization was performed on the oxidized surface of stainless steel BFBs harvested from a commercial pressurized water reactor (PWR) after 40 years of operation. The analysis shows that a complex multilayered surface oxide with six identified layers formed that is different from 2-layer structure commonly observed in model experiments. The oxide varies by composition – predominantly Fe, Cr, and Ni, grain size, and phase, and has features resembling both unirradiated and radiation/ corrosion experiments likely due to the low radiation flux compared to ion-irradiation or the test reactor radiation. In addition, grain boundary oxidative attack featured a pathway for Fe and other elements to move from the metal matrix to the outermost oxide. In conclusion, the results help assess PWR lifetime extension, put into context previous experimental studies, and provide input for designing experiments combining radiation and corrosion effects.
On February 22, 2024, the Intuitive Machines IM-1 NOVA-C lander, nick-named Odysseus, landed on the lunar surface, carrying with it a cadre of NASA scientific and technology demonstration payloads. These payloads and missions marked the first delivery of NASA instruments to operate from the lunar surface since the Apollo landings. One of these payloads is Lunar Node -1 (LN-1), a navigation beacon demonstration mission. The payload was designed and built by NASA’s Marshall Space Flight Center. The payload’s main goal was to demonstrate and provide insight into the use of lunar surface-based radio navigation aids. As part of the mission, LN-1 successfully conducted multiple one-way transmissions from the NOVA-C vehicle to Deep Space Network ground receivers using its onboard S-band transmitter, while being disciplined by an onboard Space Chip Scale Atomic Clock. LN-1 transmitted to DSN on an almost daily basis during transit to the moon, including two surface passes. The payload was originally plan to conduct 7-10 days of surface operation as an always-on beacon. These passes focused on evaluating two main navigation approaches: performance and stability of ranging using time-based transfer techniques on a cubesat size and grade platform, as well as one-way psuedonoise ranging approaches. To assess performance, the measurements were compared to independent navigation solutions using multiple approaches including: one-way Doppler tracking, two-way Doppler Tracking, and visual verification of the landing location provided by visual observations from orbital platforms. While the mission only conducted limited surface operations, the data provides some initial insight to performance form the lunar surface. These results are compared with initial ground-based testing as well as continued evaluation of the flight-space platform using multiple grades of oscillators for maintaining clock and frequency stability. These focus on the timing stability of platform in a deep-space environment as well variations in state determination. Given these insights, this paper provides additional description and evaluation of how this approach can be utilized as part of a broader lunar navigation architecture, such as being developed and deployed across multiple international space agencies. Analysis is provided to develop overall timing requirements and assessment of operational scenarios, such as orbit and surface location determination. In addition, the results support discussion as to how surface pseudolites could best be used within existing standard signal definitions, such as defined in the LunaNet Interoperability Specifications. This will consider concerns such as the near-/far- problem as well as operational considerations, including whether a beacon is better suited as two- or one-way ranging platform. The use cases are focused on how these psuedolites can provide additional coverage to augment and support planned operational coverage. For example, this analysis provides analysis of mid-latitude surface missions, where there may be limited geometry and availability of orbital relays. The results will show how these navigation psuedolites can fit within the developing architecture to provide additional robustness, capability, and support multiple use cases. Lastly, the paper will discuss challenges and next steps to be addressed in the implementation and testing of a follow-on payload and a continued path towards demonstration and integration of this capability into Lunar PNT architectures.
On February 22, 2024, Intuitive Machines NOVA-C lander, nick-named Odysseus, landed on the lunar surface, carrying with it a cadre of NASA scientific and technology demonstration payloads. These payloads and missions marked the first delivery of NASA instruments to operate from the lunar surface since the Apollo landings. One of these payloads is Lunar Node -1 (LN-1), a navigation beacon demonstration mission. The payload was designed and built by NASA’s Marshall Space Flight Center. The payload’s main goal was to demonstrate and provide insight into the use of lunar surface-based radio navigation aids. As part of the mission, LN-1 successfully conducted multiple one-way transmissions from the NOVA-C vehicle to Deep Space Network ground receivers using its onboard S-band transmitter, while being disciplined by an onboard Space Chip Scale Atomic Clock. LN-1 transmitted to DSN on an almost daily basis during transit to the moon, including two surface passes. The payload was originally plan to conduct 7-10 days of surface operation as an always-on beacon. These passes focused on evaluating two main navigation approaches: performance and stability of ranging using time-based transfer techniques on a cubesat size and grade platform, as well as one-way psuedonoise ranging approaches. To assess performance, the measurements were compared to independent navigation solutions using multiple approaches including: one-way Doppler tracking, two-way Doppler Tracking, and visual verification of the landing location provided by visual observations from orbital platforms. While the mission only conducted limited surface operations, the data provides some initial insight to performance form the lunar surface. These results are compared with initial ground-based testing as well as continued evaluation of the flight-space platform using multiple grades of oscillators for maintaining clock and frequency stability. These focus on the timing stability of platform in a deep-space environment as well variations in state determination. Given these insights, this paper provides additional description and evaluation of how this approach can be utilized as part of a broader lunar navigation architecture, such as being developed and deployed across multiple international space agencies. Analysis is provided to develop overall timing requirements and assessment of operational scenarios, such as orbit and surface location determination. In addition, the results support discussion as to how surface pseudolites could best be used within existing standard signal definitions, such as defined in the LunaNet Interoperability Specifications. This will consider concerns such as the near-/far- problem as well as operational considerations, including whether a beacon is better suited as two- or one-way ranging platform. The use cases are focused on how these psuedolites can provide additional coverage to augment and support planned operational coverage. For example, this analysis provides analysis of mid-latitude surface missions, where there may be limited geometry and availability of orbital relays. The results will show how these navigation psuedolites can fit within the developing architecture to provide additional robustness, capability, and support multiple use cases. Lastly, the paper will discuss challenges and next steps to be addressed in the implementation and testing of a follow-on payload and a continued path towards demonstration and integration of this capability into Lunar PNT architectures.
In preparation for the upcoming experimental test flight for the Orion crew module, considerable interest was raised over the possibility of exposure to elevated levels of plasma activity and vehicle charging both externally on surfaces and internally on dielectrics during the flight test orbital operations. Initial analysis using NASCAP-2K indicated very high levels of exposure, and this generated additional interest in refining/defining the plasma and spacecraft models used in the analysis. This refinement was pursued, resulting in the use of specific AE8 and AP8 models, rather than SCATHA models, as well as consideration of flight trajectory, time duration, and other parameters possibly affecting the levels of exposure and the magnitude of charge deposition. Analysis using these refined models strongly indicated that, for flight test operations, no special surface coatings were necessary for the thermal protection system, but would definitely be required for future GEO, trans-lunar, and extra-lunar missions...
In preparation for the upcoming experimental test flight for the Orion crew module, considerable interest was raised over the possibility of exposure to elevated levels of plasma activity and vehicle charging both externally on surfaces and internally on dielectrics during the flight test orbital operations. Initial analysis using NASCAP-2K indicated very high levels of exposure, and this generated additional interest in refining/defining the plasma and spacecraft models used in the analysis. This refinement was pursued, resulting in the use of specific AE8 and AP8 models, rather than SCATHA models, as well as consideration of flight trajectory, time duration, and other parameters possibly affecting the levels of exposure and the magnitude of charge deposition. Analysis using these refined models strongly indicated that, for flight test operations, no special surface coatings were necessary for the Thermal Protection System (TPS), but would definitely be required for future GEO, trans-lunar, and extra-lunar missions.
Over the last few years, the NASA Short-term Prediction Research and Transition (SPoRT) Center has been generating a 1-km sea surface temperature (SST) composite derived from retrievals of the Moderate Resolution Imaging Spectroradiometer (MODIS) for use in operational diagnostics and regional model initialization. With the assumption that the day-to-day variation in the SST is nominal, individual MODIS passes aboard the Earth Observing System (EOS) Aqua and Terra satellites are used to create and update four composite SST products each day at 0400, 0700, 1600, and 1900 UTC, valid over the western Atlantic and Caribbean waters. A six month study from February to August 2007 over the marine areas surrounding southern Florida was conducted to compare the use of the MODIS SST composite versus the Real-Time Global SST analysis to initialize the Weather Research and Forecasting (WRF) model. Substantial changes in the forecast heat fluxes were seen at times in the marine boundary layer, but relatively little overall improvement was measured in the sensible weather elements. The limited improvement in the WRF model forecasts could be attributed to the diurnal changes in SST seen in the MODIS SST composites but not accounted for by the model. Furthermore, cloud contamination caused extended periods when individual passes of MODIS were unable to update the SSTs, leading to substantial SST latency and a cool bias during the early summer months. In order to alleviate the latency problems, the SPoRT Center recently enhanced its MODIS SST composite by incorporating information from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) instruments as well as the Operational Sea Surface Temperature and Sea Ice Analysis. These enhancements substantially decreased the latency due to cloud cover and improved the bias and correlation of the composites at available marine point observations. While these enhancements improved upon the modeled cold bias using the original MODIS SSTs, the discernable impacts on the WRF model were still somewhat limited. This paper explores several factors that may have contributed to this result. First, the original methodology to initialize the model used the most recent SST composite available in a hypothetical real ]time configuration, often matching the forecast initial time with an SST field that was 5-8 hours offset. To minimize the differences that result from the diurnal variations in SST, the previous day fs SST composite is incorporated at a time closest to the model initialization hour (e.g. 1600 UTC composite at 1500 UTC model initialization). Second, the diurnal change seen in the MODIS SST composites was not represented by the WRF model in previous simulations, since the SSTs were held constant throughout the model integration. To address this issue, we explore the use of a water skin-temperature diurnal cycle prediction capability within v3.1 of the WRF model to better represent fluctuations in marine surface forcing. Finally, the verification of the WRF model is limited to very few over-water sites, many of which are located near the coastlines. In order to measure the open ocean improvements from the AMSR-E, we could use an independent 2-dimensional, satellite-derived data set to validate the forecast model by applying an object-based verification method. Such a validation technique could aid in better understanding the benefits of the mesoscale SST spatial structure to regional models applications.
Introduction: As we return to the Moon, the lunar regolith (i.e. lunar dust) covering the surface will be an obstacle to nominal operations. Accounts from Apollo astronauts and analysis of hardware returned from the surface illustrate just how deleterious the dust can be [1]. During Apollo missions, the lunar dust adhered to hardware mechanically and electrostatically [2]. Surviving the Night: Mitigating the lunar dust will be critical to surviving the night. Going hand-in-hand with other extreme environment considerations, dust mitigation is critical to mission success. Dust Impacts on Other Systems: The lunar dust can have negative implications for power, thermal, mechanisms, and several other systems or sub-systems. For example, Apollo encountered marked degradation of performance in heat rejection systems for the lunar roving vehicle, science packages, and other components because of the lunar dust [1]. For power alone, dust can cause internal clogging for power connectors, heat rejection issues, excessive dust on reflective surfaces, reduced power output for solar arrays, and so on. Dust Mitigation Strategy: In addition to considering technology solutions, it is important for hardware, systems, and or components to have a dust mitigation strategy. At a high level, hardware that will encounter the lunar dust should consider these things when defining a dust mitigation strategy: • Understand Natural Environment • Understand Induced Environment • Understand Tolerance to Dust • Write Dust Requirements • Select Dust Mitigation Solutions • Test Hardware in Dusty Environment More information on each of these can be provided to hardware owners. Dust Mitigation Technology Development: NASA has a series of technologies that may be available for hardware that needs to survive the lunar night. Many of these solutions are leveraging dust mitigation technology development efforts from NASA’s Space Technology Mission Directorate (STMD), as well as efforts from ESDMD programs, industry, and academia. Through a series of STMD programs (both internal to NASA and through partnerships), there are several technologies in development as considerations as dust mitigation solutions for hardware. Within STMD, the Game Changing Development Program (GCD) has funded several internal dust mitigation projects including low to mid TRL development, demonstrations on CLPS landers of high TRL solutions, and creating standards and best practices for dust mitigation. STMD dust mitigation efforts also include a series of partnerships for developing technologies and advancing the state of dust mitigation at NASA. This includes the Lunar Surface Innovation Consortium (LSIC), Small Business Innovation Research, Early Stage Innovations (ESI), Space Technology Research Grants (STRG), Announcement of Collaboration Opportunities (ACOs) and Tipping Points (TPs), and Challenges and Crowdsourcing, among others. There are also a series of dust mitigation solutions that have been widely used terrestrially, or during Apollo. In recent years, several studies have produced more data on the efficacy of these potential solutions in the lunar environment. Dust Mitigation Solutions: Dust mitigation solutions generally fall into four categories: • Dust Tolerant Mechanisms • Passive Dust Mitigation Capabilities • Active Dust Mitigation Capabilities • Dust Measurement Capabilities There are a series of solutions that may prove beneficial for hardware that needs to survive the lunar night, including new technology development as well as proven, terrestrial solutions. This presentation will discuss in more detail what some of these solutions are for payloads going to the surface. References: [1] J. R. Gaier, NASA/TM—2005-213610, The Effects of Lunar Dust on EVA Systems During the Apollo Missions [2] T. J. Stubbs, et al. Impact of Dust on Lunar Exploration, 2005
Introduction: As we return to the Moon, the lunar regolith (i.e. lunar dust) covering the surface will be an obstacle to nominal operations. Accounts from Apollo astronauts and analysis of hardware returned from the surface illustrate just how deleterious the dust can be [1]. During Apollo missions, the lunar dust adhered to hardware mechanically and electrostatically [2]. Surviving the Night: Mitigating the lunar dust will be critical to surviving the night. Going hand-in-hand with other extreme environment considerations, dust mitigation is critical to mission success. Dust Impacts on Other Systems: The lunar dust can have negative implications for power, thermal, mechanisms, and several other systems or sub-systems. For example, Apollo encountered marked degradation of performance in heat rejection systems for the lunar roving vehicle, science packages, and other components because of the lunar dust [1]. For power alone, dust can cause internal clogging for power connectors, heat rejection issues, excessive dust on reflective surfaces, reduced power output for solar arrays, and so on. Dust Mitigation Strategy: In addition to considering technology solutions, it is important for hardware, systems, and or components to have a dust mitigation strategy. At a high level, hardware that will encounter the lunar dust should consider these things when defining a dust mitigation strategy: • Understand Natural Environment • Understand Induced Environment • Understand Tolerance to Dust • Write Dust Requirements • Select Dust Mitigation Solutions • Test Hardware in Dusty Environment More information on each of these can be provided to hardware owners. Dust Mitigation Technology Development: NASA has a series of technologies that may be available for hardware that needs to survive the lunar night. Many of these solutions are leveraging dust mitigation technology development efforts from NASA’s Space Technology Mission Directorate (STMD), as well as efforts from ESDMD programs, industry, and academia. Through a series of STMD programs (both internal to NASA and through partnerships), there are several technologies in development as considerations as dust mitigation solutions for hardware. Within STMD, the Game Changing Development Program (GCD) has funded several internal dust mitigation projects including low to mid TRL development, demonstrations on CLPS landers of high TRL solutions, and creating standards and best practices for dust mitigation. STMD dust mitigation efforts also include a series of partnerships for developing technologies and advancing the state of dust mitigation at NASA. This includes the Lunar Surface Innovation Consortium (LSIC), Small Business Innovation Research, Early Stage Innovations (ESI), Space Technology Research Grants (STRG), Announcement of Collaboration Opportunities (ACOs) and Tipping Points (TPs), and Challenges and Crowdsourcing, among others. There are also a series of dust mitigation solutions that have been widely used terrestrially, or during Apollo. In recent years, several studies have produced more data on the efficacy of these potential solutions in the lunar environment. Dust Mitigation Solutions: Dust mitigation solutions generally fall into four categories: • Dust Tolerant Mechanisms • Passive Dust Mitigation Capabilities • Active Dust Mitigation Capabilities • Dust Measurement Capabilities There are a series of solutions that may prove beneficial for hardware that needs to survive the lunar night, including new technology development as well as proven, terrestrial solutions. This presentation will discuss in more detail what some of these solutions are for payloads going to the surface. References: [1] J. R. Gaier, NASA/TM—2005-213610, The Effects of Lunar Dust on EVA Systems During the Apollo Missions [2] T. J. Stubbs, et al. Impact of Dust on Lunar Exploration, 2005
As humanity returns to the Moon, and more and more attention is being paid to lunar surface operations, there is a greater need than ever for methods of surface navigation. These could be methods of computer-assisted orienteering for astronauts exploring on foot during an Extra-Vehicular Activity (EVA), or methods of solving the Lost-on-the-Moon problem to initialize a crewed or autonomous rover’s state estimate. It may also be necessary to process navigation data associated with surface samples or other surface operations a posteriori to better understand where that analysis occurred. Autonomous rover operation will also require Hazard Detection and Avoidance (HDA) and terrain-aware pathfinding. While navigation on the surface of the Moon will likely rely on Earth-based assets such as the Deep Space Network (DSN) or communication with other spacecraft (e.g., LunaNet, LCRNS, pre-deployed moon beacons, a nearby lander) it may be necessary to navigate in a loss-of-communication scenario. This paper analyzes the methods of surface navigation used on other celestial bodies, such as those used during the Apollo missions and autonomous exploration of Mars, as well as novel methods which have been studied but not yet implemented which may prove useful. It is shown that the navigator has myriad options when processing data from an Inertial Measurement Unit (IMU), a star tracker, (rover) wheel encoders, optical cameras, and LIght Detection and Ranging (LIDAR) sensors. The intention of this paper is to provide a broad overview of what has been done and what could be done, to aid those designing vehicles and/or missions to the lunar surface.
As humanity returns to the Moon, and more and more attention is being paid to lunar surface operations, there is a greater need than ever for methods of surface navigation. These could be methods of computer-assisted orienteering for astronauts exploring on foot during an Extra-Vehicular Activity (EVA), or methods of solving the Lost-on-the-Moon problem to initialize a crewed or autonomous rover’s state estimate. It may also be necessary to process navigation data associated with surface samples or other surface operations a posteriori to better understand where that analysis occurred. Autonomous rover operation will also require Hazard Detection and Avoidance (HDA) and terrain-aware pathfinding. While navigation on the surface of the Moon will likely rely on Earth-based assets such as the Deep Space Network (DSN) or communication with other spacecraft (e.g., LunaNet, LCRNS, pre-deployed moon beacons, a nearby lander) it may be necessary to navigate in a loss-of-communication scenario. This paper analyzes the methods of surface navigation used on other celestial bodies, such as those used during the Apollo missions and autonomous exploration of Mars, as well as novel methods which have been studied but not yet implemented which may prove useful. It is shown that the navigator has myriad options when processing data from an Inertial Measurement Unit (IMU), a star tracker, (rover) wheel encoders, optical cameras, and LIght Detection and Ranging (LIDAR) sensors. The intention of this paper is to provide a broad overview of what has been done and what could be done, to aid those designing vehicles and/or missions to the lunar surface.
The Sample Analysis at Mars Instrument Simulator (SAMSIM) is a numerical model dedicated to plan and validate operations of the Sample Analysis at Mars (SAM) instrument on the surface of Mars. The SAM instrument suite, currently operating on the Mars Science Laboratory (MSL), is an analytical laboratory designed to investigate the chemical and isotopic composition of the atmosphere and volatiles extracted from solid samples. SAMSIM was developed using Matlab and Simulink libraries of MathWorks Inc. to provide MSL mission planners with accurate predictions of the instrument electrical, thermal, mechanical, and fluid responses to scripted commands. This tool is a first example of a multi-purpose, full-scale numerical modeling of a flight instrument with the purpose of supplementing or even eliminating entirely the need for a hardware engineer model during instrument development and operation. SAMSIM simulates the complex interactions that occur between the instrument Command and Data Handling unit (C&DH) and all subsystems during the execution of experiment sequences. A typical SAM experiment takes many hours to complete and involves hundreds of components. During the simulation, the electrical, mechanical, thermal, and gas dynamics states of each hardware component are accurately modeled and propagated within the simulation environment at faster than real time. This allows the simulation, in just a few minutes, of experiment sequences that takes many hours to execute on the real instrument. The SAMSIM model is divided into five distinct but interacting modules: software, mechanical, thermal, gas flow, and electrical modules. The software module simulates the instrument C&DH by executing a customized version of the instrument flight software in a Matlab environment. The inputs and outputs to this synthetic C&DH are mapped to virtual sensors and command lines that mimic in their structure and connectivity the layout of the instrument harnesses. This module executes, and thus validates, complex command scripts prior to their up-linking to the SAM instrument. As an output, this module generates synthetic data and message logs at a rate that is similar to the actual instrument.