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NASA NTRS1974

Design of a GN and C system to meet reliability goals

This paper analyzes the reliability of the guidance, navigation, and control (GNC) portion of an avionics system for the Space Shuttle Orbiter. This analysis shows how the GNC design is affected by the need to achieve an acceptable probability of successful completion of a mission and of safe return to an airport. It varies the redundancy of the inertial measurement unit (IMU), computers, and other time-critical elements. It also includes the reliability of the flight control electronics and of the nontime-critical sensors on a phase-by-phase basis. It shows that quadruple redundancy in certain subsystems, high quality parts, and cross-strapping on orbit are required.

Kayton, M.↗

NASA NTRS1975

Dispersion analysis and linear error analysis capabilities of the space vehicle dynamics simulation program

Previous error analyses conducted by the Guidance and Dynamics Branch of NASA have used the Guidance Analysis Program (GAP) as the trajectory simulation tool. Plans are made to conduct all future error analyses using the Space Vehicle Dynamics Simulation (SVDS) program. A study was conducted to compare the inertial measurement unit (IMU) error simulations of the two programs. Results of the GAP/SVDS comparison are presented and problem areas encountered while attempting to simulate IMU errors, vehicle performance uncertainties and environmental uncertainties using SVDS are defined. An evaluation of the SVDS linear error analysis capability is also included.

Snow, L. S.↗

NASA NTRS1976

Redundant Strapdown Laser Gyro Navigation System

For the last several years, NASA has pursued the development of low-cost high-reliability inertial navigation systems that would satisfy a broad spectrum of future space and avionics missions. Two specific programs have culminated in the construction of a Redundant Strapdown Laser Gyro Navigation System. These two programs were for development of a space ultrareliable modular computer (SUMC) and a redundant laser gyro inertial measurement unit (IMU). The SUMC is a digital computer that employs state-of-the-art large-scale integrated circuits configured in a functional modular breakdown. The redundant laser gyro IMU is a six-pack strapdown sensor package in a dodecahedron configuration which uses six laser gyros to provide incremental angular positions and six accelerometers for linear velocity outputs. The sensor arrangement allows automatic accommodation of two failures; a third failure can be tolerated provided it can be determined. The navigation system also includes redundant power supplies, built-in test-equipment (BITE) circuits for failure detection, and software which provides for navigation, redundancy management, and automatic calibration and alignment.

Mcpherson, B. W.↗

NASA NTRS1981

GPS aiding of ocean current determination

The navigational accuracy of an oceangoing vessel using conventional GPS p-code data is examined. The GPS signal is transmitted over two carrier frequencies in the L-band at 1575.42 and 1227.6 MHz. Achievable navigational uncertainties of differenced positional estimates are presented as a function of the parameters of the problem, with particular attention given to the effect of sea-state, user equivalent range error, uncompensated antenna motion, varying delay intervals, and reduced data rate examined in the unaided mode. The unmodeled errors resulting from satellite ephemeris uncertainties are shown to be negligible for the GPS-NDS (Navigation Development) satellites. Requirements are met in relatively calm seas, but accuracy degradation by a factor of at least 2 must be anticipated in heavier sea states. The aided mode of operation is examined, and it is shown that requirements can be met by using an inertial measurement unit (IMU) to aid the GPS receiver operation. Since the use of an IMU would mean higher costs, direct Doppler from the GPS satellites is presented as a viable alternative.

Mohan, S. N.↗

NASA NTRS1982

Space Shuttle Orbiter descent navigation

The entry operational sequence (OPS 3) begins approximately 2 hours prior to the deorbit maneuver and continues through atmospheric entry, terminal area energy management (TAEM), approach and landing, and rollout. During this flight phase, the navigation state vector is estimated by the Space Shuttle Orbiter onboard navigation system. This estimate is computed using a six-element sequential Kalman filter, which blends inertial measurement unit (IMU) delta-velocity data with external navaid data. The external navaids available to the filter are tactical air navigation (TACAN), barometric altimeter, and microwave scan beam landing system (MSBLS). Attention is given to the functional design of the Orbiter navigation system, the descent navigation sensors and measurement processing, predicted Kalman gains, correlation coefficients, and current flights navigation performance.

Montez, M. N.↗

NASA NTRS1982

The adaptation of a strap down formulation for processing inertial platform data

An estimator propagation formulation which ultilizes dynamic data (attitude and sensed acceleration information) from a gimballed inertial platform has been developed to aid in the Shuttle post-flight trajectory reconstruction process and aerodynamic coefficient determination studies. Unlike the classical inertial algorithms, this formulation yields a six degree-of-freedom fully coupled state and attitude estimate. Furthermore, this inertial version is shown to be independent of initial unknown platform misalignments. Results obtained using actual Inertial Measurement Unit (IMU) data and Aerodynamic Coefficient Identification Package (ACIP) strap down data from Shuttle flights are presented.

Heck, M. L.↗

NASA NTRS1983

Navigation of the Space Shuttle

Navigational systems and operations for the Space Shuttle are described. All navigational instrumentation is controlled from within the pressurized main cabin. Measurements of the state vector and the attitude are made with an inertial measurement unit (IMU), which uses data initialized at the moment of take-off. Orbital location is calculated in approximations using the initial propulsion conditions, models of the gravity field, and aerodynamic drag forces. Updates are periodically received from ground tracking stations. IMU continues attitude information, and additional references are made with an automated startracker device. Information can also be gathered by optical alignment, and future systems will include radar tracking in an approach mode. Deorbit is accompanied by IMU altitude measurements as well as calculations of altitude based on drag measurements. Barometric measurements begin at about 80,000 ft altitude. Signals are received from TACAN beginning at 145,000 ft, and the microwave scanning beam landing system is started at 20,000 ft. Various radionavigation systems are also employed in all flight phases.

Edwards, A., Jr.↗

NASA NTRS1983

Aerodynamic coefficient identification package dynamic data accuracy determinations: Lessons learned

The errors in the dynamic data output from the Aerodynamic Coefficient Identification Packages (ACIP) flown on Shuttle flights 1, 3, 4, and 5 were determined using the output from the Inertial Measurement Units (IMU). A weighted least-squares batch algorithm was empolyed. Using an averaging technique, signal detection was enhanced; this allowed improved calibration solutions. Global errors as large as 0.04 deg/sec for the ACIP gyros, 30 mg for linear accelerometers, and 0.5 deg/sec squared in the angular accelerometer channels were detected and removed with a combination is bias, scale factor, misalignment, and g-sensitive calibration constants. No attempt was made to minimize local ACIP dynamic data deviations representing sensed high-frequency vibration or instrument noise. Resulting 1sigma calibrated ACIP global accuracies were within 0.003 eg/sec, 1.0 mg, and 0.05 deg/sec squared for the gyros, linear accelerometers, and angular accelerometers, respectively.

Heck, M. L.↗

NASA NTRS1988

Integrated avionics reliability

The integrated avionics reliability task is an effort to build credible reliability and/or performability models for multisensor integrated navigation and flight control. The research was initiated by the reliability analysis of a multisensor navigation system consisting of the Global Positioning System (GPS), the Long Range Navigation system (Loran C), and an inertial measurement unit (IMU). Markov reliability models were developed based on system failure rates and mission time.

Alikiotis, Dimitri↗

NASA NTRS1988

Shuttle high resolution accelerometer package experiment results - Atmospheric density measurements between 60-160 km

Indirect or inferred values of atmospheric density encountered by the Shuttle Orbiter during reentry have been calculated from acceleration measurements made by the High Resolution Accelerometer Package (HiRAP) and the Orbiter Inertial Measurement Unit (IMU) liner accelerometers. The atmospheric density data developed from this study represent a significant gain with respect to the body of data collected to date by various techniques in the altitude range of 60 to 160 km. The data are unique in that they cover a very wide horizontal range during each flight and provide insight into the actual density variations encountered along the reentry flight path. The data, which were collected over about 3 years, are also characterized by variations in solar activity, geomagnetic index, and local solar time. Comparison of the flight-derived densities with various atmospheric models have been made, and analyses have attempted to characterize the data and to show correlation with selected physical variables.

Blanchard, R. C.↗

NASA NTRS1986

Independent Orbiter Assessment (IOA): Analysis of the guidance, navigation, and control subsystem

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) is presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. The independent analysis results corresponding to the Orbiter Guidance, Navigation, and Control (GNC) Subsystem hardware are documented. The function of the GNC hardware is to respond to guidance, navigation, and control software commands to effect vehicle control and to provide sensor and controller data to GNC software. Some of the GNC hardware for which failure modes analysis was performed includes: hand controllers; Rudder Pedal Transducer Assembly (RPTA); Speed Brake Thrust Controller (SBTC); Inertial Measurement Unit (IMU); Star Tracker (ST); Crew Optical Alignment Site (COAS); Air Data Transducer Assembly (ADTA); Rate Gyro Assemblies; Accelerometer Assembly (AA); Aerosurface Servo Amplifier (ASA); and Ascent Thrust Vector Control (ATVC). The IOA analysis process utilized available GNC hardware drawings, workbooks, specifications, schematics, and systems briefs for defining hardware assemblies, components, and circuits. Each hardware item was evaluated and analyzed for possible failure modes and effects. Criticality was assigned based upon the severity of the effect for each failure mode.

Trahan, W. H.↗

NASA NTRS1990

A numerical algorithm to propagate navigation error covariance matrices associated with generalized strapdown inertial measurement units

The design and operation of a Strapdown Navigation Analysis Program (SNAP) developed to perform covariance analysis on spacecraft inertial-measurement-unit (IMU) navigation errors are described and demonstrated. Consideration is given to the IMU modeling subroutine (with user-specified sensor characteristics), the data input procedures, state updates and the simulation of instrument failures, the determination of the nominal trajectory, the mapping-matrix and Monte Carlo covariance-matrix propagation methods, and aided-navigation simulation. Numerical results are presented in tables for sample applications involving (1) the Galileo/IUS spacecraft from its deployment from the Space Shuttle to a point 10 to the 8th ft from the center of the earth and (2) the TDRS-C/IUS spacecraft from Space Shuttle liftoff to a point about 2 h before IUS deployment. SNAP is shown to give reliable results for both cases, with good general agreement between the mapping-matrix and Monte Carlo predictions.

Weir, Kent A.↗

NASA NTRS1990

Final shuttle-derived atmospheric database: Development and results from thirty-two flights

The final Shuttle-derived atmospheric data base is presented. The relational data base is comprised of data from 32 Space Transportation System (STS) descent flights, to include available meteorology data taken in support of each flight. For the most part, the available data are restricted to the middle atmosphere. In situ accelerations, sensed by the tri-redundant Inertial Measurement Unit (IMU) to an accuracy better than 1 mg, are combined with post-flight Best Estimate Trajectory (BET) information and predicted, flight-substantiated Orbiter aerodynamics to provide determinations up to altitudes of 95 km. In some instances, alternate accelerometry data with micro-g resolution were utilized to extend the data base well into the thermosphere. Though somewhat limited, the ensemble of flights permit a reasonable sampling of monthly, seasonal, and latitudinal variations which can be utilized for atmospheric science investigations and model evaluations and upgrades as appropriate. More significantly, the unparallel vertical resolution in the Shuttle-derived results indicate density shears normally associated with internal gravity waves or local atmospheric instabilities. Consequently, these atmospheres can also be used as stress-atmospheres for Guidance, Navigation and Control (GN and C) system development and analysis as part of any advanced space vehicle design activities.

Findlay, John T.↗

NASA NTRS1990

Investigation of Air Transportation Technology at Ohio University, 1989-1990

The activities of the participants in the Joint University Program (JUP) at Ohio University are briefly surveyed. During 1989 to 1990, five topics received emphasis. A spectrum-efficient weather data uplink system was designed, constructed, and flight tested. An integrated Global Positioning System/Inertial Navigation System (GPS/INS) study continued, utilizing the Redundant strapdown Inertial Measurement Unit (IMU) on loan from NASA. The Ridge Regression theory was refined and applied to air navigation scenarios. System Identification theory was applied to GPS data to point the way to better understanding of the effects of Selective Availability on civilian users of this navigation system. An analysis of thought-related (electroencephalographic) signals for application to control of computer systems that could have significance in aiding paraplegics or for hands-off systems control in industrial or air traffic control areas was carried out.

Lilley, Robert W.↗

NASA NTRS1991

Testing of the high accuracy inertial navigation system in the Shuttle Avionics Integration Lab

The description, results, and interpretation is presented of comparison testing between the High Accuracy Inertial Navigation System (HAINS) and KT-70 Inertial Measurement Unit (IMU). The objective was to show the HAINS can replace the KT-70 IMU in the space shuttle Orbiter, both singularly and totally. This testing was performed in the Guidance, Navigation, and Control Test Station (GTS) of the Shuttle Avionics Integration Lab (SAIL). A variety of differences between the two instruments are explained. Four, 5 day test sessions were conducted varying the number and slot position of the HAINS and KT-70 IMUs. The various steps in the calibration and alignment procedure are explained. Results and their interpretation are presented. The HAINS displayed a high level of performance accuracy previously unseen with the KT-70 IMU. The most significant improvement of the performance came in the Tuned Inertial/Extended Launch Hold tests. The HAINS exceeded the 4 hr specification requirement. The results obtained from the SAIL tests were generally well beyond the requirements of the procurement specification.

Strachan, Russell L.↗

NASA NTRS2001

Triana Safehold: A New Gyroless, Sun-Pointing Attitude Controller

Triana is a single-string spacecraft to be placed in a halo orbit about the sun-earth Ll Lagrangian point. The Attitude Control Subsystem (ACS) hardware includes four reaction wheels, ten thrusters, six coarse sun sensors, a star tracker, and a three-axis Inertial Measuring Unit (IMU). The ACS Safehold design features a gyroless sun-pointing control scheme using only sun sensors and wheels. With this minimum hardware approach, Safehold increases mission reliability in the event of a gyroscope anomaly. In place of the gyroscope rate measurements, Triana Safehold uses wheel tachometers to help provide a scaled estimation of the spacecraft body rate about the sun vector. Since Triana nominally performs momentum management every three months, its accumulated system momentum can reach a significant fraction of the wheel capacity. It is therefore a requirement for Safehold to maintain a sun-pointing attitude even when the spacecraft system momentum is reasonably large. The tachometer sun-line rate estimation enables the controller to bring the spacecraft close to its desired sun-pointing attitude even with reasonably high system momentum and wheel drags. This paper presents the design rationale behind this gyroless controller, stability analysis, and some time-domain simulation results showing performances with various initial conditions. Finally, suggestions for future improvements are briefly discussed.

Chen, J.↗

NASA NTRS2003

The Application of Lidar to Synthetic Vision System Integrity

One goal in the development of a Synthetic Vision System (SVS) is to create a system that can be certified by the Federal Aviation Administration (FAA) for use at various flight criticality levels. As part of NASA s Aviation Safety Program, Ohio University and NASA Langley have been involved in the research and development of real-time terrain database integrity monitors for SVS. Integrity monitors based on a consistency check with onboard sensors may be required if the inherent terrain database integrity is not sufficient for a particular operation. Sensors such as the radar altimeter and weather radar, which are available on most commercial aircraft, are currently being investigated for use in a real-time terrain database integrity monitor. This paper introduces the concept of using a Light Detection And Ranging (LiDAR) sensor as part of a real-time terrain database integrity monitor. A LiDAR system consists of a scanning laser ranger, an inertial measurement unit (IMU), and a Global Positioning System (GPS) receiver. Information from these three sensors can be combined to generate synthesized terrain models (profiles), which can then be compared to the stored SVS terrain model. This paper discusses an initial performance evaluation of the LiDAR-based terrain database integrity monitor using LiDAR data collected over Reno, Nevada. The paper will address the consistency checking mechanism and test statistic, sensitivity to position errors, and a comparison of the LiDAR-based integrity monitor to a radar altimeter-based integrity monitor.

Campbell, Jacob L.↗

NASA NTRS2003

Light Detection and Ranging-Based Terrain Navigation: A Concept Exploration

This paper discusses the use of Airborne Light Detection And Ranging (LiDAR) equipment for terrain navigation. Airborne LiDAR is a relatively new technology used primarily by the geo-spatial mapping community to produce highly accurate and dense terrain elevation maps. In this paper, the term LiDAR refers to a scanning laser ranger rigidly mounted to an aircraft, as opposed to an integrated sensor system that consists of a scanning laser ranger integrated with Global Positioning System (GPS) and Inertial Measurement Unit (IMU) data. Data from the laser range scanner and IMU will be integrated with a terrain database to estimate the aircraft position and data from the laser range scanner will be integrated with GPS to estimate the aircraft attitude. LiDAR data was collected using NASA Dryden's DC-8 flying laboratory in Reno, NV and was used to test the proposed terrain navigation system. The results of LiDAR-based terrain navigation shown in this paper indicate that airborne LiDAR is a viable technology enabler for fully autonomous aircraft navigation. The navigation performance is highly dependent on the quality of the terrain databases used for positioning and therefore high-resolution (2 m post-spacing) data was used as the terrain reference.

Campbell, Jacob↗