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

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All sourcesNASA NTRSDOE OSTI
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 NTRS2006

Comparison of Interstitial Fluid pH, PCO2, PO2 with Venous Blood Values During Repetitive Handgrip Exercise

We evaluated the use of a small, fiber optic sensor to measure pH, PCO2 and PO2 from forearm muscle interstitial fluid (IF) during handgrip dynamometry. PURPOSE: Compare pH, PCO2 and PO2 values obtained from venous blood with those from the IF of the flexor digitorum superficialis (FDS) during three levels of exercise intensity. METHODS: Six subjects (5M/1F), average age 29+/-5 yrs, participated in the study. A venous catheter was placed in the retrograde direction in the antecubital space and a fiber optic sensor (Paratrend, Diametrics Medical, Inc.) was placed through a 22 G catheter into the FDS muscle under ultrasound guidance. After a 45 min rest period, subjects performed three 5-min bouts of repetitive handgrip exercise (2s contraction/1 s relaxation) at attempted levels of 15%, 30% and 45% of maximal voluntary contraction. The order of the exercise bouts was random with the second and third bouts started after blood lactate had returned to baseline. Venous blood was sampled every minute during exercise and analyzed with an I-Stat CG-4+ cartridge, while IF fiber optic sensor measurements were obtained every 2 s. Change from pre-exercise baseline to end of exercise was computed for pH, PCO2 and PO2. Blood and IF values were compared with a paired t-test. RESULTS: Baseline values for pH, PCO2 and PO2 were 7.37+/-0.02, 46+/-4 mm Hg, and 36+/-6 mm Hg respectively in blood and 7.39+/-0.02, 44+/-6 mm Hg, and 35+/-14 mm Hg in IF. Average changes over all exercise levels are noted in the Table below. For each parameter the exercise-induced change was at least twice as great in IF as in blood. In blood and IF, pH and PCO2 increases were directly related to exercise intensity. Change in venous PO2 was unrelated to exercise intensity, while IF PO2 decreased with increases in exercise intensity. CONCLUSIONS: Measurement of IF pH, PCO2 and PO2 is more sensitive to exercise intensity than measurement of the same parameters in venous blood and provides continuous assessment during and after exercise.

Hagan, Ronald Donald↗
NASA NTRS1999

NASA Low Visibility Landing and Surface Operations (LVLASO) Atlanta Demonstration: Surveillance Systems Performance Analysis

NASA conducted a series of flight experiments at Hartsfield Atlanta International Airport as part of the Low Visibility Landing and Surface Operations (LVLASO) Program. LVLASO is one of the subelements of the NASA Terminal Area Productivity (TAP) Program, which is focused on providing technology and operating procedures for achieving clear-weather airport capacity in instrument-weather conditions, while also improving safety. LVLASO is investigating various technologies to be applied to airport surface operations, including advanced flight deck displays and surveillance systems. The purpose of this report is to document the performance of the surveillance systems tested as part of the LVLASO flight experiment. There were three surveillance sensors tested: primary radar using Airport Surface Detection Equipment (ASDE-3) and the Airport Movement Area Safety System (AMASS), Multilateration using the Airport Surface Target Identification System (ATIDS), and Automatic Dependent Surveillance - Broadcast (ADS-B) operating at 1090 MHz. The performance was compared to the draft requirements of the ICAO Advanced Surface Movement Guidance and Control System (A-SMGCS). Performance parameters evaluated included coverage, position accuracy, and update rate. Each of the sensors was evaluated as a stand alone surveillance system.

Cassell, Rick↗
NASA NTRS1975

Approach guidance for outer planet pioneer missions

Onboard optical approach guidance measurements for spin-stabilized Pioneer-type spacecraft are discussed. Approach guidance measurement accuracy requirements are outlined. The application concept and operation principle of the V-slit star tracker are discussed within the context of approach guidance measurements and measurables. It is shown that the accuracy of onboard optical approach guidance measurements is inherently coupled to the stability characteristics of the spacecraft spin axis. Geometrical and physical measurement parameters are presented for Pioneer entry probe missions to Uranus via Jupiter or Saturn flyby. The impact of these parameters on both sensor instrumentation and measurement system design is discussed. The need for sensing extended objects is shown. The feasibility of implementing an onboard approach guidance measurement system for Pioneer-type spacecraft is indicated. Two Pioneer 10 onboard measurement experiments performed in May-June 1974 are described.

Bejczy, A. K.↗
NASA NTRS1966

Ring laser sensor applications.

Ring laser sensor parameters and characteristics, noting application to measurement of angular rate, mass flow, navigation and guidance

LASER OUTPUT↗
NASA NTRS1989

Demonstrating system for servicing satellites

NASA has initiated a program to demonstrate a Satellite Servicer System prototype in a series of flight tests with the Space Shuttle. When the commitment to an operational system has been demonstrated, it is anticipated that a variety of missions will develop that can productively use the servicing capability. Rendezvous and proximity operations contain key enabling technologies needed for an effective operational system. Guidance, navigation and control hardware and operational techniques must be integrated into the program. Supporting sensor technology may limit or enhance the capability of the system depending on its readiness. Requirements for docking the spacecraft in the system concept development and technology requirements are reviewed. Examples of the initial assessment of technology readiness and applications opportunities are discussed. The degree of autonomy is of particular interest.

Jenkins, Lyle M.↗
NASA NTRS2017

Linear Covariance Analysis for a Lunar Lander

A next-generation lunar lander Guidance, Navigation, and Control (GNC) system, which includes a state-of-the-art optical sensor suite, is proposed in a concept design cycle. The design goal is to allow the lander to softly land within the prescribed landing precision. The achievement of this precision landing requirement depends on proper selection of the sensor suite. In this paper, a robust sensor selection procedure is demonstrated using a Linear Covariance (LinCov) analysis tool developed by Draper.

Jang, Jiann-Woei↗
NASA NTRS2000

MEMS Rate Sensors for Space

Micromachined Electro Mechanical System (MEMS) Rate Sensors are an enabling technology for Nanosatellites. The recent award of a Nanosatellite program to the Goddard Space Flight Center (GSFC) underscores the urgency of the development of these systems for space use. The Guidance Navigation and Control Center (GNCC) at the GSFC is involved in several efforts to develop this technology. The GNCC seeks to improve the performance of these sensors and develop flight ready systems for spacecraft use by partnering with industry leaders in MEMS Rate Sensor development. This paper introduces Microgyros and discusses the efforts in progress at the GNCC to improve the performance of these units and develop MEMS Rate Sensors for space use.

Gambino, Joel↗
NASA NTRS2021

The Mars 2020 Perseverance Navigation Filter

The Mars 2020 (M2020) Entry Descent and Landing (EDL) system delivered a rover named “Perseverance” at Jezero crater (Mars) on February 18th, 2021. M2020 EDL used a Guidance Navigation and Control (GN&C) system to achieve its landing target objectives. The navigation filter (NavFilter) integrated Descent Inertial Measurement Unit (DIMU) measurements to estimate position and attitude. The NavFilter also used the Terminal Descent Sensor (TDS) to es-timate surface-relative position and velocity corrections. The NavFilter provided all of the dynamic state information to the entry controller, entry guidance, Lander Vision System (LVS) and powered descent guidance and control algo-rithms. The NavFilter for Perseverance is based on Curiosity’s NavFilter with a couple of modifications.

Casoliva, Jordi↗
NASA NTRS1982

Shuttle navigation overview

Space Shuttle onboard navigation system tasks are related to position and velocity determination, attitude determination, sensor management, sensor Redundancy Management (RM), and navigation-related functions such as transformations, timing system utilization, and user processing for displays, guidance, and flight control. It is pointed out that Shuttle navigation is different in at least two areas from previous manned space flight navigation. The differences are related to the use of multiple units to provide protection from increased risk of failure of off-the-shelf-type equipment used for more than one flight, and the need to land at a runway. Attention is given to the navigation sensor system, the Shuttle Inertial Measurement Units, the Shuttle Star Tracker, the Crew Optical Alinement Sight, the Shuttle Tacan, the Air Data Subsystem, and aspects of navigation system mechanization.

Savely, R. T.↗
NASA NTRSDate not supplied

Post-Flight Performance Analysis of Navigation and Advanced Guidance Algorithms on a Terrestrial Suborbital Rocket Flight

There is currently renewed interest in robotic and crewed landers for a return to the lunar surface. Advanced guidance and navigation algorithms are essential to accurately delivering cargo and crew safely to the moon successfully. This paper reports the overall performance of an integrated set of navigation and guidance algorithms flown on a terrestrial suborbital rocket up to an altitude of approximately 100km. The navigation algorithm consists of an onboard extended Kalman Filter (EKF) that ingests multiple sensor measurements, one of which is the output from a terrain relative navigation (TRN) algorithm that cross-references camera images to on-board satellite imagery to perform feature correlation within the camera image. The guidance algorithm solves for a 6-degree-of-freedom (DoF) optimal trajectory using a successive convexification method during powered descent. The altitude range as well as the landing dynamics experienced during this test flight are realistic for an extraterrestrial landing and provide an invaluable data set to gauge the current development of these landing algorithms in an effort to advance the overall software readiness levels (SRL). This paper will delve into different aspects of each algorithm and present an analysis of the in-flight performance of the algorithms. This flight was conducted under the National Aeronautics and Space Administration (NASA) Safe and Precise Landing Integrated Capabilities Evolution (SPLICE) project focused on technology advancement for landing applications.

Guidance↗
NASA NTRS1990

Computer vision techniques for rotorcraft low altitude flight

Rotorcraft operating in high-threat environments fly close to the earth's surface to utilize surrounding terrain, vegetation, or manmade objects to minimize the risk of being detected by an enemy. Increasing levels of concealment are achieved by adopting different tactics during low-altitude flight. Rotorcraft employ three tactics during low-altitude flight: low-level, contour, and nap-of-the-earth (NOE). The key feature distinguishing the NOE mode from the other two modes is that the whole rotorcraft, including the main rotor, is below tree-top whenever possible. This leads to the use of lateral maneuvers for avoiding obstacles, which in fact constitutes the means for concealment. The piloting of the rotorcraft is at best a very demanding task and the pilot will need help from onboard automation tools in order to devote more time to mission-related activities. The development of an automation tool which has the potential to detect obstacles in the rotorcraft flight path, warn the crew, and interact with the guidance system to avoid detected obstacles, presents challenging problems. Research is described which applies techniques from computer vision to automation of rotorcraft navigtion. The effort emphasizes the development of a methodology for detecting the ranges to obstacles in the region of interest based on the maximum utilization of passive sensors. The range map derived from the obstacle-detection approach can be used as obstacle data for the obstacle avoidance in an automatic guidance system and as advisory display to the pilot. The lack of suitable flight imagery data presents a problem in the verification of concepts for obstacle detection. This problem is being addressed by the development of an adequate flight database and by preprocessing of currently available flight imagery. The presentation concludes with some comments on future work and how research in this area relates to the guidance of other autonomous vehicles.

Sridhar, Banavar↗
NASA NTRSDate not supplied

Distributed Sensing and Computer Vision Methods for Advanced Air Mobility Approach and Landing

Advanced Air Mobility (AAM) aircraft require precision approach and landing systems (PALS) in several types of environments such as urban, suburban, and rural. It is difficult to implement current state-of-the-art methods approved for automated approach and landing for AAM operations. However, existing technology and systems that use vision, IR, radar, and GPS methods provide baseline perception and sensing requirements for AAM aircraft approach and landing. This paper focuses on vision-based PAL and computer vision feature correspondence methods to demonstrate a baseline navigation system while adhering to the Federal Aviation Administration requirements and regulations. The coplanar algorithm determines pose estimation, which feeds into an Extended Kalman filter that combines IMU with vision to create a sensor fusion navigation solution for GPS-denied environments. The state estimate leads to glideslope and localizer error computations, which will be pertinent for designing and deriving guidance laws and control laws for AAM PALS. The IMU and vision navigation solution provides promising simulation results for AAM PALS. This paper builds on previous work by incorporating high fidelity simulations with computer graphics rendering to demonstrate a distributed sensor network to track an AAM aircraft during approach and landing to compare with the aircraft's onboard navigation solution.

Evan Kawamura↗
NASA NTRS2014

High-Fidelity Flash Lidar Model Development

NASA's Autonomous Landing and Hazard Avoidance Technologies (ALHAT) project is currently developing the critical technologies to safely and precisely navigate and land crew, cargo and robotic spacecraft vehicles on and around planetary bodies. One key element of this project is a high-fidelity Flash Lidar sensor that can generate three-dimensional (3-D) images of the planetary surface. These images are processed with hazard detection and avoidance and hazard relative navigation algorithms, and then are subsequently used by the Guidance, Navigation and Control subsystem to generate an optimal navigation solution. A complex, high-fidelity model of the Flash Lidar was developed in order to evaluate the performance of the sensor and its interaction with the interfacing ALHAT components on vehicles with different configurations and under different flight trajectories. The model contains a parameterized, general approach to Flash Lidar detection and reflects physical attributes such as range and electronic noise sources, and laser pulse temporal and spatial profiles. It also provides the realistic interaction of the laser pulse with terrain features that include varying albedo, boulders, craters slopes and shadows. This paper gives a description of the Flash Lidar model and presents results from the Lidar operating under different scenarios.

Hines, Glenn D.↗
NASA NTRS2017

Open-Loop Flight Testing of COBALT GN&C Technologies for Precise Soft Landing

A terrestrial, open-loop (OL) flight test campaign of the NASA COBALT (CoOperative Blending of Autonomous Landing Technologies) platform was conducted onboard the Masten Xodiac suborbital rocket testbed, with support through the NASA Advanced Exploration Systems (AES), Game Changing Development (GCD), and Flight Opportunities (FO) Programs. The COBALT platform integrates NASA Guidance, Navigation and Control (GN&C) sensing technologies for autonomous, precise soft landing, including the Navigation Doppler Lidar (NDL) velocity and range sensor and the Lander Vision System (LVS) Terrain Relative Navigation (TRN) system. A specialized navigation filter running onboard COBALT fuzes the NDL and LVS data in real time to produce a precise navigation solution that is independent of the Global Positioning System (GPS) and suitable for future, autonomous planetary landing systems. The OL campaign tested COBALT as a passive payload, with COBALT data collection and filter execution, but with the Xodiac vehicle Guidance and Control (G&C) loops closed on a Masten GPS-based navigation solution. The OL test was performed as a risk reduction activity in preparation for an upcoming 2017 closed-loop (CL) flight campaign in which Xodiac G&C will act on the COBALT navigation solution and the GPS-based navigation will serve only as a backup monitor.

Carson, John M., III↗
NASA NTRS1977

Adaptive control of a robotic manipulator

A control hierarchy for a robotic manipulator is described. The hierarchy includes perception and robot/environment interaction, the latter consisting of planning, path control, and terminal guidance loops. Environment-sensitive features include the provision of control governed by proximity, tactile, and visual sensors as well as the usual kinematic sensors. The manipulator is considered as part of an overall robot system. 'Adaptive control' in the present context refers to both the hierarchical nature of the control system and to its environment-responsive nature.

Lewis, R. A.↗