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This viewgraph presentation is an overview of the Lunar Reconnaissance Orbiter (LRO), with emphasis on the navigation and plans for the mission. The objective of the LRO mission is to conduct investigations that will be specifically target to prepare for and support future human exploration of the Moon. There is a review of the scientific instruments on board the LRO and an overview of the phases of the planned trajectory.
Linearized error analysis of onboard primary navigation systems for Apollo lunar module
Symbolic programming digital computer techniques, hardware interfacing and system errors in simulation of lunar midcourse guidance and navigation systems
As Lunar exploration continues to become more commonplace, reliable methods of precise Terrain Relative Navigation (TRN) are needed. While there are many TRN techniques available, one that has received increased interest in the past few years is that of crater based navigation. Crater based navigation has numerous benefits, including being a human recognizable feature (important for crewed missions), as well as the fact that craters are often possible hazards that need to be detected and avoided. The use of crater based navigation has been limited however. This has been due to the difficulty of running such algorithms on board a spacecraft, as well as the difficulty in procuring large amounts of the required training data. This paper presents a new rendering tool for generating large amounts of high quality training data. It then looks at two recently developed machine learning techniques for crater detection and crater identification in real-time on near-future space hardware.
Apollo cislunar navigation capability and procedures, describing onboard data acquisition and digital processing equipment
This paper describes and predicts the performance of a conceptual autonomous GPS-based navigation system for NASA's planned lunar Gateway. This system is based on the flight-proven Magnetospheric Multiscale (MMS) GPS navigation system, augmented with an earth-pointed high-gain antenna and with an option for an atomic clock. High-fidelity simulations, calibrated against MMS flight data and making use of GPS transmitter patterns from the GPS Antenna Characterization Experiment (ACE) project are developed for operation of the system in the Gateway Near-Rectilinear Halo Orbit (NRHO). The results indicate that GPS can provide an autonomous, realtime navigation capability with comparable, or superior, performance to traditional Deep Space Network approach with eight hours of tracking per day.
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To support a wide variety of lunar missions in a condensed regime, solutions are needed outside of the use of Earth-based orbit determination. This research presents an alternate approach to in-situ navigation through the use of beacons, similar to that used on Earth as well as under technology development efforts. An overview of the current state of navigation aids included as well as discussion of the Lunar Node – 1 payload being built at NASA/Marshall Space Flight Center. Expected navigation results of this beacon payload for planned operation from the lunar surface are provided. Applications of navigation beacons to multiple stages of the proposed human lunar landing architecture are given, with initial analysis showing performance gains from the use of this technology. This work provides a starting point for continued analysis and design, laying out the foundation of how navigation beacons can be incorporated into the architecture to enable continued analysis, design, and future expanded capability.
NASA has set the ambitious goal of establishing a sustainable human presence on the Moon. Diverse commercial and international partners are engaged in this effort to catalyze scientific discovery, lunar resource utilization and economic development on both the Earth and at the Moon. Lunar development will serve as a critical proving ground for deeper exploration into the solar system. Space communications and navigation infrastructure will play an integral part in realizing this goal. This paper provides a high-level description of an extensible and scalable lunar communications and navigation architecture, known as LunaNet. LunaNet is a services network to enable lunar operations. Three LunaNet service types are defined: networking services, position, navigation and timing services, and science utilization services. The LunaNet architecture encompasses a wide variety of topology implementations, including surface and orbiting provider nodes. In this paper several systems engineering considerations within the service architecture are highlighted. Additionally, several alternative LunaNet instantiations are presented. Extensibility of the LunaNet architecture to the solar system internet is discussed.
NASA has set the ambitious goal of establishing a sustainable human presence on the Moon. Diverse commercial and international partners are engaged in this effort to catalyze scientific discovery, lunar resource utilization and economic development on both the Earth and at the Moon. Lunar development will serve as a critical proving ground for deeper exploration into the solar system. Space communications and navigation infrastructure will play an integral part in realizing this goal. This paper provides a high-level description of an extensible and scalable lunar communications and navigation architecture, known as LunaNet. LunaNet is a services network to enable lunar operations. Three LunaNet service types are defined: networking services, position, navigation and timing services, and science utilization services. The LunaNet architecture encompasses a wide variety of topology implementations, including surface and orbiting provider nodes. In this paper several systems engineering considerations within the service architecture are highlighted. Additionally, several alternative LunaNet instantiations are presented. Extensibility of the LunaNet architecture to the solar system internet is discussed.
Measurement schedules effect on work load of astronaut performing navigation function, stressing tradeoff between number of measurements and accuracy level
The Orion Crew Exploration Vehicle (CEV) will replace the Space Shuttle and serve as the next-generation spaceship to carry humans back to the Moon for the first time since the Apollo program. For nominal lunar mission operations, the Mission Control Navigation team will utilize radiometric measurements to determine the position and velocity of Orion and uplink state information to support Lunar return. However, in the loss of communications contingency return scenario, Orion must safely return the crew to the Earth's surface. The navigation design solution for this loss of communications scenario is optical navigation consisting of lunar landmark tracking in low lunar orbit and star- horizon angular measurements coupled with apparent planetary diameter for Earth return trajectories. This paper describes the optical measurement errors and the navigation filter that will process those measurements to support navigation for safe crew return.
The driving precision landing requirement for the Autonomous Landing and Hazard Avoidance Technology project is to autonomously land within 100m of a predetermined location on the lunar surface. Traditional lunar landing approaches based on inertial sensing do not have the navigational precision to meet this requirement. The purpose of Terrain Relative Navigation (TRN) is to augment inertial navigation by providing position or bearing measurements relative to known surface landmarks. From these measurements, the navigational precision can be reduced to a level that meets the 100m requirement. There are three different TRN functions: global position estimation, local position estimation and velocity estimation. These functions can be achieved with active range sensing or passive imaging. This paper gives a survey of many TRN approaches and then presents some high fidelity simulation results for contour matching and area correlation approaches to TRN using active sensors. Since TRN requires an a-priori reference map, the paper concludes by describing past and future lunar imaging and digital elevation map data sets available for this purpose.
A LunaNet Lunar Augmented Navigation Service (LANS) is being developed to enable a position, navigation, and timing service for future Lunar operations. The signal includes two components. An in-phase data channel signal is spread by a 1.023 MCPS ranging code that provides a high-rate data message at 250 bps and is encoded by a strong Low Density Parity Check (LDPC) code. A pilot channel with a 5.115 MCPS spreading code is also provided. The pilot code is configured with a secondary (overlay) code that does not currently provide absolute time or frame Synchronization as is the case for L1C. This work shows the advantage of implementing an overlay structure that provides absolute time for the LunaNet LANS signal structure known as the Augmented Forward Signal (AFS). The LunaNet AFS structure was developed to service two classes of user receivers. The first class is a low-complexity user receiver that only receives the 1.023 MCPS signal and does not use the 5.115 MCPS pilot channel. For this class of user, a data frame Sync word is needed. The second class of receiver is a high-end receiver that can processes both data and pilot channels to take advantage of the higher chip rate pilot channel for enhanced robustness and improved accuracy. In the current draft LunaNet LANS AFS design, these users must employ the frame Sync word in the data channel and obtain absolute time after decoding the AFS navigation message. The signal structure would greatly benefit from the addition of a pilot overlay structure that provides absolute time and robust frame Sync for high-end users as done for L1C. To provide a more robust and interoperable AFS structure, this work summarizes a study and recommends alternatives for a new overlay code on the pilot channel that provides absolute time and a Sync word approach on the data channel. The overlay code and Sync word are designed to allow for flexible and robust data synchronization for both low- complexity and high-end user receivers. The new overlay code structure permits frame synchronization performance that is as good as or better than the L1 C signal, while enabling a determination of absolute time upon frame Sync to aid high-end assisted LANS AFS user receivers at low signal to noise levels. We also present the design of rate-matched 5G new radio (5GNR) LDPC codes that fit within the current 6000-symbol frame size along with a time of interval (TOI) word, frame ID (FID) word, and the remaining LunaNet AFS data message blocks. The paper describes and demonstrates robust frame Synchronization performance of the overlay code and Synch word approaches. The results are described in terms of probability of missed detection and probability of false alarm for a correct frame Synchronization at low Eb/No levels expected for decoding the TOI word and LDPC encoded data. Advantages of the proposed data Synchronization structure will be described along with use cases for low-end and high-end receivers. Practical implementation considerations will also be described.
The driving precision landing requirement for the Autonomous Landing and Hazard Avoidance Technology project is to autonomously land within 100m of a predetermined location on the lunar surface. Traditional lunar landing approaches based on inertial sensing do not have the navigational precision to meet this requirement. The purpose of Terrain Relative Navigation (TRN) is to augment inertial navigation by providing position or bearing measurements relative to known surface landmarks. From these measurements, the navigational precision can be reduced to a level that meets the 100m requirement. There are three different TRN functions: global position estimation, local position estimation and velocity estimation. These functions can be achieved with active range sensing or passive imaging. This paper gives a survey of many TRN approaches and then presents some high fidelity simulation results for contour matching and area correlation approaches to TRN using active sensors. Since TRN requires an a-priori reference map, the paper concludes by describing past and future lunar imaging and digital elevation map data sets available for this purpose.
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.
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