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NASA NTRSDate not supplied

Hazard Boresight Relative Navigation for Safe Lunar Landing

In the area of planetary landing, hazard detection and avoidance is the act of driving a vehicle to a safe landing area using onboard resources. A hazard detection sensor is used to scan the terrain and these measurements are evaluated to determine where the safe landing sites are located. The selected site is generally not the same as the nominal target, so the vehicle must divert to the new site. This activity involves the interaction between several components, including a suite of onboard GNC algorithms that work together to efficiently choose and divert to a new site. This paper presents the Hazard Boresight Relative Navigation concept, which is a method that provides a common interface between the hazard scan, safe-site selection algorithm, size of the target-relative landing ellipse, divert offset distance and guidance targeting algorithm. After the safe-site is selected from the hazard scan, the original inertial target is replaced with a vehicle-relative target, which is initialized by a measurement from the hazard scan. The new target-relative position state is estimated over time in the navigation filter, and is fed to the guidance algorithm to perform the divert maneuver. In addition to detailing the Hazard Boresight Relative Navigation concept, this paper also presents some general landing terms that can be used in the greater discussion, as well as analysis on how to estimate and predict the vehicle footprint dispersion ellipse during flight, which is used in the safe-site selection algorithm.

Stephen R. Steffes↗
NASA NTRSDate not supplied

Hazard Boresight Relative Navigation for Safe Lunar Landing

In the area of planetary landing, hazard detection and avoidance is the act of driving a vehicle to a safe landing area using onboard resources. A hazard detection sensor is used to scan the terrain and these measurements are evaluated to determine where the safe landing sites are located. The selected site is generally not the same as the nominal target, so the vehicle must divert to the new site. This activity involves the interaction between several components, including a suite of onboard GNC algorithms that work together to efficiently choose and divert to a new site. This paper presents the Hazard Boresight Relative Navigation concept, which is a method that provides a common interface between the hazard scan, safe-site selection algorithm, size of the target-relative landing ellipse, divert offset distance and guidance targeting algorithm. After the safe-site is selected from the hazard scan, the original inertial target is replaced with a vehicle-relative target, which is initialized by a measurement from the hazard scan. The new target-relative position state is estimated over time in the navigation filter, and is fed to the guidance algorithm to perform the divert maneuver. In addition to detailing the Hazard Boresight Relative Navigation concept, this paper also presents some general landing terms that can be used in the greater discussion, as well as analysis on how to estimate and predict the vehicle footprint dispersion ellipse during flight, which is used in the safe-site selection algorithm.

Stephen Steffes↗
NASA NTRS1979

Navigation systems for approach and landing of VTOL aircraft

The formulation and implementation of navigation systems used for research investigations in the V/STOLAND avionics system are described. The navigation systems prove position and velocity in a cartestian reference frame aligned with the runway. They use filtering techniques to combine the raw position data from navaids (e.g., TACAN, MLS) with data from onboard inertial sensors. The filtering techniques which use both complementary and Kalman filters, are described. The software for the navigation systems is also described.

Schmidt, S. F.↗
NASA NTRS2022

Real-World Testing of LiDAR-Inertial Based Navigation and Mapping for Precision Landing

The fusion of LiDAR and inertial measurements duringspacecraft descent and landing can be used to estimate alander’s navigation state and map the terrain below. Together,these data products can be used to enable safe and preciselanding on celestial bodies for which a priori orbital reconnaissanceis insufficient for hazard detection and avoidance.Unlike camera images used in visual terrain relative navigation,LiDAR scans are insensitive to changes in illumination; as aresult, the technique can be used to land in poorly lit areas,or at times of day when the lighting conditions are incongruentwith existing orbital imagery. In this paper, we extend previouswork in which we introduced a factor graph based smoothingapproach for LiDAR-inertial navigation and mapping. Whereasthe algorithms were previously tested on simulated data, thispaper presents testing on real-world data. Data from theAutonomous Landing Hazard Avoidance Technology (ALHAT)airplane flight tests in the Yucca Flats and Death Valley in2009 (FT3), the Morpheus vertical take off and landing flighttests at Kennedy Space Center in 2014 (FT6), and the landingof Perseverance and Ingenuity on Mars in 2021 (M2020) wereused to evaluate algorithm performance. In this paper, weextend our LiDAR-inertial technique to work with a variety ofranging technologies: single point laser altimetry (FT3), denseflash LiDAR (FT6), and six-beam radar (M2020). A thoroughperformance analysis for all three datasets is presented. Datasetpreparation, improvements in algorithm robustness, and outlierrejection, which were necessitated by the transition to realworlddata, are discussed.

Trawny, Nikolas↗
NASA NTRS2001

The design and navigation of the NEAR-Shoemaker landing on Eros

This paper discusses the design, navigation and the Monte Carlo error analyses that were critical to the design of this landing scenario. Also described is the reconstruction of the landing trajectory using radio metric, optical landmark and laser ranging tracking data, which determined the characteristics of the landing to be well within the error analyses.

NEAR↗
NASA NTRS2010

Reactive Sequencing for Autonomous Navigation Evolving from Phoenix Entry, Descent, and Landing

Virtual Machine Language (VML) is an award-winning advanced procedural sequencing language in use on NASA deep-space missions since 1997, and was used for the successful entry, descent, and landing (EDL) of the Phoenix spacecraft onto the surface of Mars. Phoenix EDL utilized a state-oriented operations architecture which executed within the constraints of the existing VML 2.0 flight capability, compatible with the linear "land or die" nature of the mission. The intricacies of Phoenix EDL included the planned discarding of portions of the vehicle, the complex communications management for relay through on-orbit assets, the presence of temporally indeterminate physical events, and the need to rapidly catch up four days of sequencing should a reboot of the spacecraft flight computer occur shortly before atmospheric entry. These formidable operational challenges led to new techniques for packaging and coordinating reusable sequences called blocks using one-way synchronization via VML sequencing global variable events. The coordinated blocks acted as an ensemble to land the spacecraft, while individually managing various elements in as simple a fashion as possible. This paper outlines prototype VML 2.1 flight capabilities that have evolved from the one-way synchronization techniques in order to implement even more ambitious autonomous mission capabilities. Target missions for these new capabilities include autonomous touch-and-go sampling of cometary and asteroidal bodies, lunar landing of robotic missions, and ultimately landing of crewed lunar vehicles. Close proximity guidance, navigation, and control operations, on-orbit rendezvous, and descent and landing events featured in these missions require elaborate abort capability, manifesting highly non-linear scenarios that are so complex as to overtax traditional sequencing, or even the sort of one-way coordinated sequencing used during EDL. Foreseeing advanced command and control needs for small body and lunar landing guidance, navigation and control scenarios, work began three years ago on substantial upgrades to VML that are now being exercised in scenarios for lunar landing and comet/asteroid rendezvous. The advanced state-based approach includes coordinated state transition machines with distributed decision-making logic. These state machines are not merely sequences - they are reactive logic constructs capable of autonomous decision making within a well-defined domain. Combined with the JPL's AutoNav software used on Deep Space 1 and Deep Impact, the system allows spacecraft to autonomously navigate to an unmapped surface, soft-contact, and either land or ascend. The state machine architecture enabled by VML 2.1 has successfully performed sampling missions and lunar descent missions in a simulated environment, and is progressing toward flight capability. The authors are also investigating using the VML 2.1 flight director architecture to perform autonomous activities like rendezvous with a passive hypothetical Mars sample return capsule. The approach being pursued is similar to the touch-and-go sampling state machines, with the added complications associated with the search for, physical capture of, and securing of a separate spacecraft. Complications include optically finding and tracking the Orbiting Sample Capsule (OSC), keeping the OSC illuminated, making orbital adjustments, and physically capturing the OSC. Other applications could include autonomous science collection and fault compensation.

asteroid↗
NASA NTRS1997

Detection of Obstacles in Monocular Image Sequences

The ability to detect and locate runways/taxiways and obstacles in images captured using on-board sensors is an essential first step in the automation of low-altitude flight, landing, takeoff, and taxiing phase of aircraft navigation. Automation of these functions under different weather and lighting situations, can be facilitated by using sensors of different modalities. An aircraft-based Synthetic Vision System (SVS), with sensors of different modalities mounted on-board, complements the current ground-based systems in functions such as detection and prevention of potential runway collisions, airport surface navigation, and landing and takeoff in all weather conditions. In this report, we address the problem of detection of objects in monocular image sequences obtained from two types of sensors, a Passive Millimeter Wave (PMMW) sensor and a video camera mounted on-board a landing aircraft. Since the sensors differ in their spatial resolution, and the quality of the images obtained using these sensors is not the same, different approaches are used for detecting obstacles depending on the sensor type. These approaches are described separately in two parts of this report. The goal of the first part of the report is to develop a method for detecting runways/taxiways and objects on the runway in a sequence of images obtained from a moving PMMW sensor. Since the sensor resolution is low and the image quality is very poor, we propose a model-based approach for detecting runways/taxiways. We use the approximate runway model and the position information of the camera provided by the Global Positioning System (GPS) to define regions of interest in the image plane to search for the image features corresponding to the runway markers. Once the runway region is identified, we use histogram-based thresholding to detect obstacles on the runway and regions outside the runway. This algorithm is tested using image sequences simulated from a single real PMMW image.

Kasturi, Rangachar↗
NASA NTRS2008

Overview of Terrain Relative Navigation Approaches for Precise Lunar Landing

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.

Terrain Relative Navigation (TRN)↗
NASA NTRS1995

Flight test evaluation of the E-systems Differential GPS category 3 automatic landing system

Test flights were conducted to evaluate the capability of Differential Global Positioning System (DGPS) to provide the accuracy and integrity required for International Civil Aviation Organization (ICAO) Category (CAT) III precision approach and landings. These test flights were part of a Federal Aviation Administration (FAA) program to evaluate the technical feasibility of using DGPS based technology for CAT III precision approach and landing applications. An IAI Westwind 1124 aircraft (N24RH) was equipped with DGPS receiving equipment and additional computing capability provided by E-Systems. The test flights were conducted at NASA Ames Research Center's Crows Landing Flight Facility, Crows Landing, California. The flight test evaluation was based on completing 100 approaches and landings. The navigation sensor error accuracy requirements were based on ICAO requirements for the Microwave Landing System (MLS). All of the approaches and landings were evaluated against ground truth reference data provided by a laser tracker. Analysis of these approaches and landings shows that the E-Systems DGPS system met the navigation sensor error requirements for a successful approach and landing 98 out of 100 approaches and landings, based on the requirements specified in the FAA CAT III Level 2 Flight Test Plan. In addition, the E-Systems DGPS system met the integrity requirements for a successful approach and landing or stationary trial for all 100 approaches and landings and all ten stationary trials, based on the requirements specified in the FAA CAT III Level 2 Flight Test Plan.

Kaufmann, David N.↗
NASA NTRS1979

LED display for solo aircraft instrument navigation

Solo pilot's task is made easier through convenient display of landing and navigation data. Use of display shows promise as more efficient means of presenting sequential instructions and data, such as course heading, altitude, and radio frequency, to minimize pilot's workload during solo instrument flight.

Crouch, R. K.↗
NASA NTRS2006

A Low Cost Spacecraft Architecture for Robotic Lunar Exploration Projects

A program of frequent, capable, but affordable lunar robotic missions prior to return of humans to the moon can contribute to the Vision for Space Exploration (VSE) NASA is tasked to execute. The Lunar Reconnaissance Orbiter (LRO) and its secondary payload are scheduled to orbit the moon, and impact it, respectively, in 2008. It is expected that the sequence of missions occurring for approximately the decade after 2008 will place an increasing emphasis on soft landed payloads. These missions are requited to explore intrinsic characteristics of the moon, such as hydrogen distribution in the regolith, and levitated dust, to demonstrate the ability to access and process in-situ resources, and to demonstrate functions critical to supporting human presence, such as automated precision navigation and landing. Additional factors governing the design of spacecraft to accomplish this diverse set of objectives are: operating within a relatively modest funding profile, the need tb visit multiple sites (both polar and equatorial) repeatedly, and to use the current generation of launch vehicles. In the US, this implies use of the Evolved Expendable Launch Vehicles, or EELVs, although this design philosophy may be extended to launch vehicles of other nations, as well. Many of these factors are seemingly inconsistent with each other. For example, the cost of a spacecraft usually increases with mass; therefore the desire to fly frequent, modestly priced spacecraft seems to imply small spacecraft (< 1 Mt, injected mass). On the other hand, the smallest of the EELVs will inject approx. 3 Mt. on a Trans Lunar Injection (TLI) trajectory md would therefore be wasteful or launching a single, small spacecraft. Increasing the technical capability of a spacecraft (such as autonomous navigation and soft landing) also usually increases cost. A strategy for spacecraft design that meets these conflicting requirements is presented. Taken together, spacecraft structure and propulsion subsystems constitute the majority of spacecraft mass; saving development and integration cost on these elements is critical to controlling cost. Therefore, a low cost, modular design for spacecraft structure and propulsion subsystems is presented which may be easily scaled up or down for either insertion into lunar orbit or braking for landing on the lunar surface. In order to effectively use the approx.3 Mt mass-to-TLI of the EELV, two low cost spacecraft will be manifested on the same launch. One spacecraft will be located on top of the other for launch and the two will have to be released in sequence in order to achieve all mission objectives. The two spacecraft could both be landers, both orbiters, or one lander and one orbiter. In order to achieve mass efficiency, the body of the spacecraft will serve the dual purposes of carrying launch loads and providing attachment points for all the spacecraft subsystems. In order to avoid unaffordable technology development costs, small liquid propulsion components and autonomous, scene-matching navigation cameras may be adapted from military missile programs in order to execute precision soft landings.

Lemke, Lawrence G.↗
NASA NTRSDate not supplied

Lidar-Based Safe Site Relative Navigation

Established Safe and Precise Landing–Integrated Capability Evolution (SPLICE) project precision landing requirements necessitate a navigation filter architecture and underlying models developed specifically with these needs in mind. To date, test flights to characterize SPLICE guidance and navigation (GN) system performance have not provided a means to divert from the a priori selected landing site (LS) due to hazardous conditions. With the inclusion of a new sensor type, the Hazard Detection Lidar (HDL) coupled with safe landing site selection algorithms, GN can divert from the originally planned trajectory and navigate relative to the new targeted landing site. This discussion covers the navigation filter developments necessary to perform this estimation and process the resulting HDL measurements to meet project safe landing goals.

Navigation↗
NASA NTRSDate not supplied

Evaluation of Precision Landing Performance Using A Generalized Aerospace Simulation in Simulink Framework

NASA’s science and exploration goals to return to the Moon and beyond will need to perform precision landings to place humans and cargo supplies near places of scientific interest, surface resources, or pre-established basecamps. With the maturation of new navigation technology, such as terrain relative navigation, precision landing is now feasible, enabling new exploration sites, such as the lunar poles. However, verification of precision landing performance becomes crucial since not reaching the designated landing site would have a high risk of loss of mission. Therefore, having a high-fidelity simulation platform to evaluate six degrees of freedom vehicle performance during high-risk phases of flight such landing is a fundamental part of the system verification and risk reduction. The NASA Marshall Space Flight Center has developed the GeneraLized Aerospace Simulation in Simulink® (GLASS) tool which incorporates guidance, navigation, and control algorithms, as well as vehicle and environmental models, such as gravity, vehicle mass properties, navigation sensors, propulsion, and terrain models. GLASS uses the MathWorks® Simulink® environment which provides a model-based design framework that allows the incorporation of vehicle models in a modular architecture. The Simulink® environment provides seamless integration with all the MathWorks® capabilities and toolboxes, such as control design toolboxes and Simscape™ Multibody™ dynamics toolbox. The MathWorks® environment also allows for guidance, navigation, and control algorithms to be auto coded in C language, enabling quick software and hardware in the loop testing. This paper provides an overview of GLASS capabilities for analyzing precision landing performance, including navigation trades applied to a NASA human lander reference design architecture.

Guidance↗
NASA NTRS2008

Overview of terrain relative navigation approaches for Precise Lunar Landing

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.

Montgomery, James F.↗
NASA NTRS2010

Altair Navigation During Trans-Lunar Cruise, Lunar Orbit, Descent and Landing

The Altair lunar lander navigation system is driven by a set of requirements that not only specify a need to land within 100 m of a designated spot on the Moon, but also be capable of a safe return to an orbiting Orion capsule in the event of loss of Earth ground support. These requirements lead to the need for a robust and capable on-board navigation system that works in conjunction with an Earth ground navigation system that uses primarily ground-based radiometric tracking. The resulting system relies heavily on combining a multiplicity of data types including navigation state updates from the ground based navigation system, passive optical imaging from a gimbaled camera, a stable inertial measurement unit, and a capable radar altimeter and velocimeter. The focus of this paper is on navigation performance during the trans-lunar cruise, lunar orbit, and descent/landing mission phases with the goal of characterizing knowledge and delivery errors to key mission events, bound the statistical delta V costs for executing the mission, as well as the determine the landing dispersions due to navigation. This study examines the nominal performance that can be obtained using the current best estimate of the vehicle, sensor, and environment models. Performance of the system under a variety sensor outages and parametric trades is also examined.

lunar lander↗