Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “STATE VECTOR”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

OMV: A simplified mathematical model of the orbital maneuvering vehicle

A model of the orbital maneuvering vehicle (OMV) is presented which contains several simplications. A set of hand controller signals may be used to control the motion of the OMV. Model verification is carried out using a sequence of tests. The dynamic variables generated by the model are compared, whenever possible, with the corresponding analytical variables. The results of the tests show conclusively that the present model is behaving correctly. Further, this model interfaces properly with the state vector transformation module (SVX) developed previously. Correct command sentence sequences are generated by the OMV and and SVX system, and these command sequences can be used to drive the flat floor simulation system at MSFC.

Teoh, W.↗
NASA NTRS1984

A substructure coupling procedure applicable to general linear time-invariant dynamic systems

A substructure synthesis procedure applicable to structural systems containing general nonconservative terms is presented. In their final form, the non-self-adjoint substructure equations of motion are cast in state vector form through the use of a variational principle. A reduced-order model for each substructure is implemented by representing the substructure as a combination of a small number of Ritz vectors. For the method presented, the substructure Ritz vectors are identified as a truncated set of substructure eigenmodes, which are typically complex, along with a set of generalized real attachment modes. The formation of the generalized attachment modes does not require any knowledge of the substructure flexible modes; hence, only the eigenmodes used explicitly as Ritz vectors need to be extracted from the substructure eigenproblem. An example problem is presented to illustrate the method.

Howsman, T. G.↗
NASA NTRS1985

Adaptive Filtering for Large Space Structures: A Closed-Form Solution

In a previous paper Schaechter proposes using an extended Kalman filter to estimate adaptively the (slowly varying) frequencies and damping ratios of a large space structure. The time varying gains for estimating the frequencies and damping ratios can be determined in closed form so it is not necessary to integrate the matrix Riccati equations. After certain approximations, the time varying adaptive gain can be written as the product of a constant matrix times a matrix derived from the components of the estimated state vector. This is an important savings of computer resources and allows the adaptive filter to be implemented with approximately the same effort as the nonadaptive filter. The success of this new approach for adaptive filtering was demonstrated using synthetic data from a two mode system.

Rauch, H. E.↗
NASA NTRS1984

A substructure coupling procedure applicable to general linear time-invariant dynamic systems

A substructure synthesis procedure applicable to structural systems containing general nonconservative terms is presented. In their final form, the nonself-adjoint substructure equations of motion are cast in state vector form through the use of a variational principle. A reduced-order mode for each substructure is implemented by representing the substructure as a combination of a small number of Ritz vectors. For the method presented, the substructure Ritz vectors are identified as a truncated set of substructure eigenmodes, which are typically complex, along with a set of generalized real attachment modes. The formation of the generalized attachment modes does not require any knowledge of the substructure flexible modes; hence, only the eigenmodes used explicitly as Ritz vectors need to be extracted from the substructure eigenproblem. An example problem is presented to illustrate the method.

Howsman, T. G.↗
NASA NTRS1986

Rendezvous BET Program

Computes relative positions of two vehicles in concentric orbits. LRBET3 program best-estimate-of-trajectory (BET) calculation for postflight trajectory analysis of Shuttle orbital rendezvous maneuvers. LRBET3 produces estimated measurements for reconstructing relative positions of two vehicles. Kalman filter and smoothing filter applied to relative measurement input data to estimate state vector, reduce noise, and produce BET output. BET calculation minimizes variances of all trajectory estimation errors. LRBET3 written in FORTRAN IV for batch execution.

Lear, W. M.↗
NASA NTRS1986

Analyzing Shuttle Orbiter Trajectories

LRBET4 program best-estimated-of-trajectory (BET) calculation for post-flight trajectory analysis of Shuttle orbiter. Produces estimated measurements for comparing predicted and actual trajectory of Earth-orbiting spacecraft. Kalman filter and smoothing filter applied to input data to estimate state vector, reduce noise, and produce BET. LRBET4 written in FORTRAN IV for batch execution.

Lear, W. M.↗
NASA NTRS1985

Onboard rendezvous navigation for the Space Shuttle

The onboard rendezvous navigation software for Shuttle flight 41-C are described. Particular attention is given to the inputs, models, and outputs of the software. The performance of the rendezvous navigation system is compared to predicted performance profiles in connection with the relative vehicle geometry, as well as the location of the navigation sensor tracking arcs. The methods used to process navigational sensor measurements in order to update the state vector are also summarized. A table listing the sources of maneuver targeting errors is provided.

Wylie, A. D.↗
NASA NTRS1986

Identification of nonlinear system parameters in joints using the force-state mapping technique

A procedure is presented for identifying the potentially strong nonlinear properties of structural members, such as joints, by expressing the force transmitted by the member as a function of its mechanical state. By explicitly including position and rate dependent effects, the surface of transmitted force versus state, the force-state map, has distinct, unique, superposable features for common structural nonlinearities, even those which appear to indicate hysteresis on a force-stroke presentation. An analysis is performed on the influence of true memory effects, transient response, and uncertainty in the measurements and system mass on the precision of the procedure. The successful identification of simulated data verifies the accuracy of the identification algorithm. Tests are then conducted on three actual joint models, with incomplete state measurements typical of an actual testing environment. The ability of the procedure to estimate the complete state vector and to analyze and reconstruct the measured nonlinear characteristics is demonstrated.

Crawley, E. F.↗
NASA NTRS1986

The flight and impact dispersion of the Comet Nucleus Penetrator - A six-degree-of-freedom simulation

The flight dynamics of a Penetrator probe which, as part of a Comet Rendezvous and Asteroid Flyby mission will impact a known periodic comet, possibly Hempel 2, and penetrate beneath the surface to obtain measurements, is discussed. The mission is described, including the penetrator-separation dynamics, the dynamics during initial coast and rocket thrust phase, and the final coast to impact. The effects on the results that may be caused by the comet nucleus gravity field variations, uncertainty in the spacecraft state vector, the spacecraft pointing accuracy, initial separation errors, and rocket motor thrust errors are examined.

Mascy, A. C.↗
NASA NTRS1986

Engineering description of the ascent/descent bet product

The Ascent/Descent output product is produced in the OPIP routine from three files which constitute its input. One of these, OPIP.IN, contains mission specific parameters. Meteorological data, such as atmospheric wind velocities, temperatures, and density, are obtained from the second file, the Corrected Meteorological Data File (METDATA). The third file is the TRJATTDATA file which contains the time-tagged state vectors that combine trajectory information from the Best Estimate of Trajectory (BET) filter, LBRET5, and Best Estimate of Attitude (BEA) derived from IMU telemetry. Each term in the two output data files (BETDATA and the Navigation Block, or NAVBLK) are defined. The description of the BETDATA file includes an outline of the algorithm used to calculate each term. To facilitate describing the algorithms, a nomenclature is defined. The description of the nomenclature includes a definition of the coordinate systems used. The NAVBLK file contains navigation input parameters. Each term in NAVBLK is defined and its source is listed. The production of NAVBLK requires only two computational algorithms. These two algorithms, which compute the terms DELTA and RSUBO, are described. Finally, the distribution of data in the NAVBLK records is listed.

Seacord, A. W., II↗
NASA NTRS1987

Teleoperator and robotics system analysis

The Orbital Maneuvering Vehicle (OMV) was designed to operate as a remotely controlled space teleoperator. The design and implementation of OMM (a mathematical model of the OMV) are discussed. The State Vector Transformation Module (SVX), an interface between the OMV simulation model and the mobile base (TOM-B) of the flat floor simulation system is described. A summary of testing procedures and conclusions are presented together with the test data obtained.

Teoh, William↗
NASA NTRS1988

A Design Study of Onboard Navigation and Guidance During Aerocapture at Mars

The navigation and guidance of a high lift-to-drag ratio sample return vehicle during aerocapture at Mars are investigated. Emphasis is placed on integrated systems design, with guidance algorithm synthesis and analysis based on vehicle state and atmospheric density uncertainty estimates provided by the navigation system. The latter utilizes a Kalman filter for state vector estimation, with useful update information obtained through radar altimeter measurements and density altitude measurements based on IMU-measured drag acceleration. A three-phase guidance algorithm, featuring constant bank numeric predictor/corrector atmospheric capture and exit phases and an extended constant altitude cruise phase, is developed to provide controlled capture and depletion of orbital energy, orbital plane control, and exit apoapsis control. Integrated navigation and guidance systems performance are analyzed using a four degree-of-freedom computer simulation. The simulation environment includes an atmospheric density model with spatially correlated perturbations to provide realistic variations over the vehicle trajectory. Navigation filter initial conditions for the analysis are based on planetary approach optical navigation results. Results from a selection of test cases are presented to give insight into systems performance.

Fuhry, Douglas Paul↗
NASA NTRS1988

OMV docking simulator

The Boeing Orbital Maneuvering Vehicle (OMV) Docking and Proximity Operation System (DAPOS) was completed. The system constructed involves the use of four separate processors. Appropriate software was developed that drives each of these four processors. The hand controller logic coordinates all the activities in the control station, and communicates with the OMV mathematical model. The state vector generated by the model is in turn transmitted to the control station as well as the POLY 2000 (via the ALCYON host computer) for real time graphics generation. The OMV characteristics are stored in a data file which may be easily updated and modified without disturbing the software, thereby making the system very flexible. The current system supports two types of hand controllers. The system was flown by several volunteers, some of whom are airplane pilots. A user manual is also enclosed.

Teoh, W.↗
NASA NTRS1989

Range Filtering For Navigation By Satellite

Less processing and storage of data needed. Mathematical basis developed for Kalman filtering of sequential measurements of range from single-channel receiver in Global Positioning System (GPS) to each of several navigation satellites. Range filtering involves separate applications of kinematic Kalman tracking filter to measurements of signal from each satellite in use. State vector consists of pseudorange and time derivatives. Main advantages: simplification of tuning and decreases in required amounts of storage and processing of data for navigation in ships, airplanes, and ground vehicles.

Paielli, Russell↗
NASA NTRS1988

Preliminary Orbit Determination System (PODS) for Tracking and Data Relay Satellite System (TDRSS)-tracked target Spacecraft using the homotopy continuation method

The Preliminary Orbit Determination System (PODS) provides early orbit determination capability in the Trajectory Computation and Orbital Products System (TCOPS) for a Tracking and Data Relay Satellite System (TDRSS)-tracked spacecraft. PODS computes a set of orbit states from an a priori estimate and six tracking measurements, consisting of any combination of TDRSS range and Doppler tracking measurements. PODS uses the homotopy continuation method to solve a set of nonlinear equations, and it is particularly effective for the case when the a priori estimate is not well known. Since range and Doppler measurements produce multiple states in PODS, a screening technique selects the desired state. PODS is executed in the TCOPS environment and can directly access all operational data sets. At the completion of the preliminary orbit determination, the PODS-generated state, along with additional tracking measurements, can be directly input to the differential correction (DC) process to generate an improved state. To validate the computational and operational capabilities of PODS, tests were performed using simulated TDRSS tracking measurements for the Cosmic Background Explorer (COBE) satellite and using real TDRSS measurements for the Earth Radiation Budget Satellite (ERBS) and the Solar Mesosphere Explorer (SME) spacecraft. The effects of various measurement combinations, varying arc lengths, and levels of degradation of the a priori state vector on the PODS solutions were considered.

Kirschner, S. M.↗
NASA NTRS1989

Modeling the missile-launch tube problem in DYSCO

DYSCO is a versatile, general purpose dynamic analysis program which assembles equations and solves dynamics problems. The executive manages a library of technology modules which contain routines that compute the matrix coefficients of the second order ordinary differential equations of the components. The executive performs the coupling of the equations of the components and manages the solution of the coupled equations. Any new component representation may be added to the library if, given the state vector, a FORTRAN program can be written to compute M, C, K, and F. The problem described demonstrates the generality of this statement.

Berman, Alex↗
NASA NTRS1988

Shuttle rendezvous radar performance evaluation and simulation

The US Space Shuttle's Ku-band system was specifically designed for communications and tracking functions which are required during on-orbit operations with other spacecraft. Operating modes permit search and acquisition to be accomplished by computer designation or under manual control by the astronaut. Ku-band system data channels drive on-board dedicated displays and are incorporated into state vector updates by Shuttle guidance and navigation computers. Radar-cross-section estimates were used in computer simulations to predict the range at which radar detection and acquisition can be expected. Validity of the simulationi model and the radar design and performance were verified by flight tests on the White Sands test range. It is concluded that results of the testing established confidence in the capability of the system to provide the relative position and rate information which is needed for Shuttle work involving other spacecraft.

Griffin, John W.↗
NASA NTRS1989

Lifetime predictions for the Solar Maximum Mission (SMM) and San Marco spacecraft

Lifetime prediction techniques developed by the Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD) are described. These techniques were developed to predict the Solar Maximum Mission (SMM) spacecraft orbit, which is decaying due to atmospheric drag, with reentry predicted to occur before the end of 1989. Lifetime predictions were also performed for the Long Duration Exposure Facility (LDEF), which was deployed on the 1984 SMM repair mission and is scheduled for retrieval on another Space Transportation System (STS) mission later this year. Concepts used in the lifetime predictions were tested on the San Marco spacecraft, which reentered the Earth's atmosphere on December 6, 1988. Ephemerides predicting the orbit evolution of the San Marco spacecraft until reentry were generated over the final 90 days of the mission when the altitude was less than 380 kilometers. The errors in the predicted ephemerides are due to errors in the prediction of atmospheric density variations over the lifetime of the satellite. To model the time dependence of the atmospheric densities, predictions of the solar flux at the 10.7-centimeter wavelength were used in conjunction with Harris-Priester (HP) atmospheric density tables. Orbital state vectors, together with the spacecraft mass and area, are used as input to the Goddard Trajectory Determination System (GTDS). Propagations proceed in monthly segments, with the nominal atmospheric drag model scaled for each month according to the predicted monthly average value of F10.7. Calibration propagations are performed over a period of known orbital decay to obtain the effective ballistic coefficient. Progagations using plus or minus 2 sigma solar flux predictions are also generated to estimate the despersion in expected reentry dates. Definitive orbits are compared with these predictions as time expases. As updated vectors are received, these are also propagated to reentryto continually update the lifetime predictions.

Smith, E. A.↗