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At least 145 records · Page 8

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.↗

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.↗

On the flight derived/aerodynamic data base performance comparisons for the NASA Space Shuttle entries during the hypersonic regime

Aerodynamic performance data from the first four Shuttle reentry flights are compared with preflight predictions covering hypersonic longitudinal mode down to Mach 2. The extraction of the flight coefficients, as measured by the spacecraft angular rates and the linear accelerations, derived from the inertial measurement unit, the best estimate trajectory, and the remotely measured atmosphere are discussed. The ground predictions were developed from 30,000 hr of wind tunnel testing. Actual flight data are presented for 80-260 kft, from Mach 2-26, comprising the dynamic pressure, the vehicle air relative attitude angles, control surface deflections, reaction jet activity, and body axis rates and accelerations. The second and fourth flights gave results which deviated from predictions between 230-260 kft. The accuracy limits of the derived atmospheric densities are considered, together with potential data base updates in the light of limitations imposed on the corrections by available flight data.

Findlay, J. T.↗

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.↗

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.↗

The reliability analysis of a separated, dual fail operational redundant strapdown IMU

A methodology for quantitatively analyzing the reliability of redundant avionics systems, in general, and the dual, separated Redundant Strapdown Inertial Measurement Unit (RSDIMU), in particular, is presented. The RSDIMU is described and a candidate failure detection and isolation system presented. A Markov reliability model is employed. The operational states of the system are defined and the single-step state transition diagrams discussed. Graphical results, showing the impact of major system parameters on the reliability of the RSDIMU system, are presented and discussed.

Motyka, P.↗

Evolution of shuttle avionics redundancy management/fault tolerance

The challenge of providing redundancy management (RM) and fault tolerance to meet the Shuttle Program requirements of fail operational/fail safe for the avionics systems was complicated by the critical program constraints of weight, cost, and schedule. The basic and sometimes false effectivity of less than pure RM designs is addressed. Evolution of the multiple input selection filter (the heart of the RM function) is discussed with emphasis on the subtle interactions of the flight control system that were found to be potentially catastrophic. Several other general RM development problems are discussed, with particular emphasis on the inertial measurement unit RM, indicative of the complexity of managing that three string system and its critical interfaces with the guidance and control systems.

Boykin, J. C.↗

Flight test configuration for verifying inertial sensor redundancy management techniques

The Redundant Strapdown Inertial Measurement Unit presently tested in flight configuration consists of a semioctahedral array of four dynamically tuned, two-degree-of-freedom (TDOF) gyros and four TDOF accelerometers which can provide dual, fail-operational performance for integrated avionics systems. Attention is given to the multilevel algorithm used for the detection and isolation of three ranges of sensor failure in an integrated avionics context. A technique for the generation of accelerometer and gyro error thresholds which is sensitive to dynamic sensor errors and separation effects is presented, together with simulation results. Emphasis is placed on the ensuring of highly reliable data for flight control/navigation functions, while minimizing false or missed alarms.

Bryant, W. H.↗

Shuttle derived atmosphere

The shuttle descends along a rather shallow path, thus providing some information on the horizontal structure of the atmosphere. Small scale structures were suggested (shears, potholes). The best estimates of the shuttle drag coefficient and projected areas are used to go from accelerometer data to density through the use of BET's (Best Estimated Trajectories). Data are from the IMU's (Inertial Measurement Unit) and the HiRAP (High Resolution Accelerometer Package).

Findlay, John↗

Middle atmosphere density and models

The 80 to 130 km altitude region is our old ignorosphere, the region of the atmosphere that no one seems to be interested in and yet the critical region for shuttle entry and atmospheric braking. Comparison between the Air Force reference atmosphere and Shuttle Inertial Measurement Units data shows large fluctuations at high latitudes. New data sources are available now, such as the Arecibo and Millstone Hill ionospheric scatter radars. In the 20 to 80 km altitude range there is a reasonable quantity of data on the mean atmosphere, however, infomation on diurnal variability is needed. In the 20 to 80 km altitude range data is needed to identify systematic variations and models for the regions are preliminary. Unpredictable variations are observed: turbulence, storm effects, gravity waves.

Champion, K.↗

Development of N-version software samples for an experiment in software fault tolerance

The report documents the task planning and software development phases of an effort to obtain twenty versions of code independently designed and developed from a common specification. These versions were created for use in future experiments in software fault tolerance, in continuation of the experimental series underway at the Systems Validation Methods Branch (SVMB) at NASA Langley Research Center. The 20 versions were developed under controlled conditions at four U.S. universities, by 20 teams of two researchers each. The versions process raw data from a modified Redundant Strapped Down Inertial Measurement Unit (RSDIMU). The specifications, and over 200 questions submitted by the developers concerning the specifications, are included as appendices to this report. Design documents, and design and code walkthrough reports for each version, were also obtained in this task for use in future studies.

Lauterbach, L.↗

NAVSIM 2: A computer program for simulating aided-inertial navigation for aircraft

NAVSIM II, a computer program for analytical simulation of aided-inertial navigation for aircraft, is described. The description is supported by a discussion of the program's application to the design and analysis of aided-inertial navigation systems as well as instructions for utilizing the program and for modifying it to accommodate new models, constraints, algorithms and scenarios. NAVSIM II simulates an airborne inertial navigation system built around a strapped-down inertial measurement unit and aided in its function by GPS, Doppler radar, altimeter, airspeed, and position-fix measurements. The measurements are incorporated into the navigation estimate via a UD-form Kalman filter. The simulation was designed and implemented using structured programming techniques and with particular attention to user-friendly operation.

Bjorkman, William S.↗

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↗

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.↗

Shuttle-derived densities in the middle atmosphere

NASA Space Shuttle flights have furnished a basis for the derivation of middle-atmosphere densities with unprecedented vertical resolution; an archival data base is now available that furnishes extensive information for the evaluation of existing model estimates for latitudinal and seasonal effects, as well as the improvement of mean monthly predictions. The High Resolution Accelerometry Package results yield extensive large-amplitude, low-frequency density variations throughout the thermosphere. The Inertial Measurement Unit results show abrupt density shifts at all latitudes, with visible shears being observed that can be correlated to summer activity.

Gamble, Joe D.↗

An onboard navigation system which fulfills Mars aerocapture guidance requirements

The development of a candidate autonomous onboard Mars approach navigation scheme capable of supporting aerocapture into Mars orbit is discussed. An aerocapture guidance and navigation system which can run independently of the preaerocapture navigation was used to define a preliminary set of accuracy requirements at entry interface. These requirements are used to evaluate the proposed preaerocapture navigation scheme. This scheme uses optical sightings on Deimos with a star tracker and an inertial measurement unit for instrumentation as a source for navigation nformation. Preliminary results suggest that the approach will adequately support aerocaputre into Mars orbit.

Brand, Timothy J.↗

A new adaptive control approach for aerospace vehicles with parameter uncertainties

A new stochastic adaptive control structure is developed for the problem of combined parameter estimation and control of aerospace vehicles with changing parameters. Parameter uncertainties are modeled as first-order Gauss-Markov processes, and are introduced to the system dynamics through a small parameter. It is assumed that an accurate inertial measurement unit gives perfect measurements of the state variables. Since the stochastic system is assumed to be Gauss-Markov, the density function of the parameters given these measurements is conditionally Gaussian. Based on this conditionally Gaussian density, the problem of minimizing a quadratic cost over an infinite time horizon can be set up within the framework of stochastic optimal control theory. The optimal feedback control law is derived from a straightforward expansion of the Hamilton-Jacobi-Bellman equation, based on the LQG solution. The resulting nonlinear controller is applied to the pitch axis control of a space platform with uncertain moments of inertia and is shown to produce marked improvement over a fixed controller.

Hahn, Yungsun↗

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.↗