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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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At least 379 records · Page 21
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NASA NTRS1993

Spaceflight dynamics 1993; AAS/NASA International Symposium, 8th, Greenbelt, MD, Apr. 26-30, 1993, Parts 1 & 2

A conference on spaceflight dynamics produced papers in the areas of orbit determination, spacecraft tracking, autonomous navigation, the Deep Space Program Science Experiment Mission (DSPSE), the Global Positioning System, attitude control, geostationary satellites, interplanetary missions and trajectories, applications of estimation theory, flight dynamics systems, low-Earth orbit missions, orbital mechanics, mission experience in attitude dynamics, mission experience in sensor studies, attitude dynamics theory and simulations, and orbit-related experience. These papaers covered NASA, European, Russian, Japanese, Chinese, and Brazilian space programs and hardware.

Teles, Jerome↗
NASA NTRS2011

Ares I-X First Stage Separation Loads and Dynamics Reconstruction

The Ares I-X flight test provided NASA with the opportunity to test hardware and gather critical data to ensure the success of future Ares I flights. One of the primary test flight objectives was to evaluate the environment during First Stage separation to better understand the conditions that the J-2X second stage engine will experience at ignition [1]. A secondary objective was to evaluate the effectiveness of the stage separation motors. The Ares I-X flight test vehicle was successfully launched on October 29, 2009, achieving most of its primary and secondary test objectives. Ground based video camera recordings of the separation event appeared to show recontact of the First Stage and the Upper Stage Simulator followed by an unconventional tumbling of the Upper Stage Simulator. Closer inspection of the videos and flight test data showed that recontact did not occur. Also, the motion during staging was as predicted through CFD analysis performed during the Ares I-X development. This paper describes the efforts to reconstruct the vehicle dynamics and loads through the staging event by means of a time integrated simulation developed in TREETOPS, a multi-body dynamics software tool developed at NASA [2]. The simulation was built around vehicle mass and geometry properties at the time of staging and thrust profiles for the first stage solid rocket motor as well as for the booster deceleration motors and booster tumble motors. Aerodynamic forces were determined by models created from a combination of wind tunnel testing and CFD. The initial conditions such as position, velocity, and attitude were obtained from the Best Estimated Trajectory (BET), which is compiled from multiple ground based and vehicle mounted instruments. Dynamic loads were calculated by subtracting the inertial forces from the applied forces. The simulation results were compared to the Best Estimated Trajectory, accelerometer flight data, and to ground based video.

Demory, Lee↗
NASA NTRS2011

Machine Vision for Relative Spacecraft Navigation During Approach to Docking

This paper describes a machine vision system for relative spacecraft navigation during the terminal phase of approach to docking that: 1) matches high contrast image features of the target vehicle, as seen by a camera that is bore-sighted to the docking adapter on the chase vehicle, to the corresponding features in a 3d model of the docking adapter on the target vehicle and 2) is robust to on-orbit lighting. An implementation is provided for the case of the Space Shuttle Orbiter docking to the International Space Station (ISS) with quantitative test results using a full scale, medium fidelity mock-up of the ISS docking adapter mounted on a 6-DOF motion platform at the NASA Marshall Spaceflight Center Flight Robotics Laboratory and qualitative test results using recorded video from the Orbiter Docking System Camera (ODSC) during multiple orbiter to ISS docking missions. The Natural Feature Image Registration (NFIR) system consists of two modules: 1) Tracking which tracks the target object from image to image and estimates the position and orientation (pose) of the docking camera relative to the target object and 2) Acquisition which recognizes the target object if it is in the docking camera Field-of-View and provides an approximate pose that is used to initialize tracking. Detected image edges are matched to the 3d model edges whose predicted location, based on the pose estimate and its first time derivative from the previous frame, is closest to the detected edge1 . Mismatches are eliminated using a rigid motion constraint. The remaining 2d image to 3d model matches are used to make a least squares estimate of the change in relative pose from the previous image to the current image. The changes in position and in attitude are used as data for two Kalman filters whose outputs are smoothed estimate of position and velocity plus attitude and attitude rate that are then used to predict the location of the 3d model features in the next image.

Chien, Chiun-Hong↗
NASA NTRS2019

Performance Improvements for the Lunar Reconnaissance Orbiter Gyroless Extended Kalman Filter

In late 2017, the laser intensity monitor (LIM) current began to decline on the Lunar Reconnaissance Orbiter (LRO) miniature inertial measurement unit (MIMU). The MIMU was powered off in March 2018 and has only been used during extended eclipses, a pre-eclipse orbit phasing maneuver, and critical momentum unloads. Science slews were suspended, and the onboard extended Kalman filter (EKF) was disabled. A coarse rate was estimated through star tracker quaternion differentiation, and attitude was provided directly from a single star tracker. A complementary filter, combining the differentiated quaternions with the integrated acceleration derived from the attitude control torque, was developed, tested, and uploaded to the spacecraft in December 2018. The EKF has been enabled, using the complementary filter rate in place of the MIMU and science slews are now being performed. This paper presents an overview of the complementary filter rate estimation and EKF changes, fault detection updates without the MIMU, and inflight performance improvements.

Halverson, Julie↗
NASA NTRS1980

Attitude determination of Galileo spacecraft from star data

An entirely autonomous attitude determination algorithm has been developed for the dual spin Galileo spacecraft in its mission to Jupiter. A batch mode process is established which identifies three stars within the scanner's field-of-view based on the criteria of intensity and geometry. This is followed by a continuous star acquisition procedure which provides star transit times and a spacecraft spin rate estimate. A least-squares estimator then sequentially determines the spacecraft's attitude from successive star crossings by minimizing an error derived using the necessary condition of star and scanner slit normal orthogonality. Simulation results are presented, showing successful star identification and attitude convergence in the presence of nutation and star transit time uncertainty.

Wong, E. C.↗
NASA NTRS1992

Attitude stability of LDEF: Refinement of results from the silver pinhole camera

A measurement was previously described of the angular offset and attitude stability of the LDEF spacecraft using a simple pinhole camera device in the UAH experiment A0114. This device uses a silver surface to record the impact zone of atmospheric atomic oxygen passing through a small pinhole on the front surface of the satellite. The shape and size of this zone are well defined if the satellite velocity and gas temperature are known. The circular symmetry of the zone would be distorted by oscillation of the LDEF about its stable attitude, or by the effect of the co-rotation of the Earth's atmosphere for cases of satellites in nonequatorial orbits. The observed ellipticity of 1.05 with the major axis in the yaw direction is equivalent to an oscillation of + or - 0.2 deg about the stable attitude. The uncertainty in that measurement was estimated at about 0.1 deg. A refined analysis based on summing distributions of flux versus incidence angle for a large number of orbital positions, and including a co-rotating atmosphere, indicates that the combined distributions produce a result consistent with the measured exposed spot. It is suggested that, within the precision of the measurements, no actual oscillation of the LDEF is required to produce the results. Thus, the LDEF may have maintained a stable attitude to better than 0.1 deg, even under conditions of maximum aerodynamic perturbation when the silver oxygen record was made. This error is some two orders of magnitude lower than the predicted uncertainty in yaw oscillation and may indicate that the predict methodologies are too conservative.

Peters, P. N.↗
NASA NTRS2012

Nonlinear Estimation Approach to Real-Time Georegistration from Aerial Images

When taking aerial images, it is important to know locations of specific points of interest in an Earth-centered coordinate system (latitude, longitude, height). The correspondence between a pixel location in the image and its Earth coordinate is known as georegistration. There are two main technical challenges arising in the intended application. The first is that no known features are assumed to be available in any of the images. The second is that the intended applications are real time. Here, images are taken at regular intervals (i.e. once per second), and it is desired to make decisions in real time based on the geolocation of specific objects seen in the images as they arrive. This is in sharp contrast to most current methods for geolocation that operate "after-the-fact" by processing, on the ground, a database of stored images using computationally intensive methods. The solution is a nonlinear estimation algorithm that combines processed realtime camera images with vehicle position and attitude information ob tained from an onboard GPS receiver. This approach provides accurate georegistration estimates (latitude, longitude, height) of arbitrary features and/or points of interest seen in the camera images. This solves the georegistration problem at the modest cost of augmenting the camera information with a GPS receiver carried onboard the vehicle.

Bayard, David S.↗
NASA NTRS2006

Accurate State Estimation and Tracking of a Non-Cooperative Target Vehicle

Autonomous space rendezvous scenarios require knowledge of the target vehicle state in order to safely dock with the chaser vehicle. Ideally, the target vehicle state information is derived from telemetered data, or with the use of known tracking points on the target vehicle. However, if the target vehicle is non-cooperative and does not have the ability to maintain attitude control, or transmit attitude knowledge, the docking becomes more challenging. This work presents a nonlinear approach for estimating the body rates of a non-cooperative target vehicle, and coupling this estimation to a tracking control scheme. The approach is tested with the robotic servicing mission concept for the Hubble Space Telescope (HST). Such a mission would not only require estimates of the HST attitude and rates, but also precision control to achieve the desired rate and maintain the orientation to successfully dock with HST.

Thienel, Julie K.↗
NASA NTRS2006

Accurate State Estimation and Tracking of a Non-Cooperative Target Vehicle

Autonomous space rendezvous scenarios require knowledge of the target vehicle state in order to safely dock with the chaser vehicle. Ideally, the target vehicle state information is derived from telemetered data, or with the use of known tracking points on the target vehicle. However, if the target vehicle is non-cooperative and does not have the ability to maintain attitude control, or transmit attitude knowledge, the docking becomes more challenging. This work presents a nonlinear approach for estimating the body rates of a non-cooperative target vehicle, and coupling this estimation to a tracking control scheme. The approach is tested with the robotic servicing mission concept for the Hubble Space Telescope (HST). Such a mission would not only require estimates of the HST attitude and rates, but also precision control to achieve the desired rate and maintain the orientation to successfully dock with HST.

Thienel, Julie K.↗
NASA NTRS1978

Laboratory demonstration of aircraft estimation using low-cost sensors

Four nonlinear state estimators were devised which provide techniques for obtaining the angular orientation (attitude) of the aircraft. An extensive FORTRAN computer program was developed to demonstrate and evaluate the estimators by using recorded flight test data. This program simulates the estimator operation, and it compares the state estimates with actual state measurements. The program was used to evaluate the state estimators with data recorded on the NASA Ames CV-990 and CESSNA 402B aircraft. A preliminary assessment was made of the memory, word length, and timing requirements for implementing the selected state estimator on a typical microcomputer.

Sorensen, J. A.↗
NASA NTRS1994

Building complex simulations rapidly using MATRIX(x): The Space Station redesign

MSFC's quick response to the Space Station redesign effort last year required the development of a computer simulation to model the attitude and station-keeping dynamics of a complex body with rotating solar arrays in orbit around the Earth. The simulation was written using a rapid-prototyping graphical simulation and design tool called MATRIX(x) and provided the capability to quickly remodel complex configuration changes by icon manipulation using a mouse. The simulation determines time-dependent inertia properties, and models forces and torques from gravity-gradient, solar radiation, and aerodynamic disturbances. Surface models are easily built from a selection of beams, plates, tetrahedrons, and cylinders. An optimization scheme was written to determine the torque equilibrium attitudes that balance gravity-gradient and aerodynamic torques over an orbit, and propellant-usage estimates were determined. The simulation has been adapted to model the attitude dynamics for small spacecraft.

Carrington, C. K.↗
NASA NTRS1995

Modal Correction Method For Dynamically Induced Errors In Wind-Tunnel Model Attitude Measurements

This paper describes a method for correcting the dynamically induced bias errors in wind tunnel model attitude measurements using measured modal properties of the model system. At NASA Langley Research Center, the predominant instrumentation used to measure model attitude is a servo-accelerometer device that senses the model attitude with respect to the local vertical. Under smooth wind tunnel operating conditions, this inertial device can measure the model attitude with an accuracy of 0.01 degree. During wind tunnel tests when the model is responding at high dynamic amplitudes, the inertial device also senses the centrifugal acceleration associated with model vibration. This centrifugal acceleration results in a bias error in the model attitude measurement. A study of the response of a cantilevered model system to a simulated dynamic environment shows significant bias error in the model attitude measurement can occur and is vibration mode and amplitude dependent. For each vibration mode contributing to the bias error, the error is estimated from the measured modal properties and tangential accelerations at the model attitude device. Linear superposition is used to combine the bias estimates for individual modes to determine the overall bias error as a function of time. The modal correction model predicts the bias error to a high degree of accuracy for the vibration modes characterized in the simulated dynamic environment.

Buehrle, R. D.↗
NASA NTRS1959

A Weight Comparison of Several Attitude Controls for Satellites

A brief theoretical study has been made for the purpose for estimating and comparing the weight of three different types of controls that can be used to change the attitude of a satellite. The three types of controls are jet reaction, inertia wheel, and a magnetic bar which interacts with the magnetic field of the earth. An idealized task which imposed severe requirements on the angular motion of the satellite was used as the basis for comparison. The results showed that a control for one axis can be devised which will weigh less than 1 percent of the total weight of the satellite. The inertia-wheel system offers weight-saving possibilities if a large number of cycles of operation are required, whereas the jet system would be preferred if a limited number of cycles are required. The magnetic-bar control requires such a large magnet that it is impractical for the example application but might be of value for supplying small trimming moments about certain axes.

Adams, James J.↗
NASA NTRS1981

Autonomous attitude determination from star data for a dual-spin planetary spacecraft

A batch mode process which identifies three reference stars within a rotor-mounted star scanner's field-of-view based on the criteria of intensity and geometry was established. The sequential mode which continuously tracks the reference stars provides star transit times and estimates of rotor's spin rate. A least-square estimator was formulated which sequentially determines the spacecraft attitude from sucessive star crossings by minimizing the error in the star and scanner slit normal orthogonality. This spacecraft attitude also provides intermittent updates for the gyro propagated inertial attitude of the despun science platform. Simulation results are presented, showing successful star identification and attitude convergence in the presence of nutation and star transit time uncertainty.

Wong, E. C.↗
NASA NTRS2008

Generalized Linear Covariance Analysis

We review and extend in two directions the results of prior work on generalized covariance analysis methods. This prior work allowed for partitioning of the state space into "solve-for" and "consider" parameters, allowed for differences between the formal values and the true values of the measurement noise, process noise, and a priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and a priori solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator s anchor time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the "variance sandpile" and the "sensitivity mosaic," and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.

Carpenter, J. Russell↗
NASA NTRS2014

Generalized Linear Covariance Analysis

This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.

Navagation↗
NASA NTRS2014

Generalized Linear Covariance Analysis

This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.

n/a↗
NASA NTRS1992

A real-time recursive filter for the attitude determination of the Spacelab instrument pointing subsystem

A real-time estimation filter which reduces sensitivity to system variations and reduces the amount of preflight computation is developed for the instrument pointing subsystem (IPS). The IPS is a three-axis stabilized platform developed to point various astronomical observation instruments aboard the shuttle. Currently, the IPS utilizes a linearized Kalman filter (LKF), with premission defined gains, to compensate for system drifts and accumulated attitude errors. Since the a priori gains are generated for an expected system, variations result in a suboptimal estimation process. This report compares the performance of three real-time estimation filters with the current LKF implementation. An extended Kalman filter and a second-order Kalman filter are developed to account for the system nonlinearities, while a linear Kalman filter implementation assumes that the nonlinearities are negligible. The performance of each of the four estimation filters are compared with respect to accuracy, stability, settling time, robustness, and computational requirements. It is shown, that for the current IPS pointing requirements, the linear Kalman filter provides improved robustness over the LKF with less computational requirements than the two real-time nonlinear estimation filters.

West, M. E.↗