Instrumentation and Calibration Technique for Flight Calibration of Angle-of-attack Systems on Aircraft
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Mcfadden, Norman M↗
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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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Calibration, Data Acquisition, and Post Analysis of Turbulent Fluid Flow in a Calibration Jet Using Hot-wire Anemometry
The Turbine Branch concentrates on the following areas: Computational Fluid Dynamics (CFD), and implementing experimental procedures to obtain physical modeling data. Hot-wire Anemometry is a valuable tool for obtaining physical modeling data. Hot-wire Anemometry is likely to remain the principal research tool for most turbulent air/gas flow studies. The Hot-wire anemometer consists of a fine wire heated by electric current. When placed in a fluid stream, the hot-wire loses heat to the fluid by forced convection. In forced convection, energy transfer is due to molecular motion imposed by an extraneous force moving fluid parcels. When the hot-wire is in "equilibrium", the rate of heat input to the wire is equal to the rate of heat loss at the wire ends. The equality between heat input and heat loss is the basis for King s equation, which relates the electrical parameters of the hot-wire to the flow parameters of the fluid. Hot-wire anemometry is based on convective heat transfer from a heated wire element placed in a fluid flow. Any change in the fluid flow condition that affects the heat transfer from the heated element will be detected virtually instantaneously by a constant-temperature Hot-wire anemometry system. The system implemented for this research is the IFA 300. The system is a fully-integrated, thermal anemometer-based system that measures mean and fluctuating velocity components in air, water, and other fluids. It also measures turbulence and makes localized temperature measurements. A constant-temperature anemometer is a bridge and amplifier circuit that controls a tiny wire at constant temperature. As a fluid flow passes over the heated sensor, the amplifier senses the bridge off-balance and adjusts the voltage to the top of the bridge, keeping the bridge in balance. The voltage on top of the bridge can then be related to the velocity of the flow. The bridge voltage is sensitive to temperature as well as velocity and so the built-in thermocouple circuit can be attached to a thermocouple that can measure the fluid temperature. Additional information is included in the original extended abstract.
Moreno, Michelle↗
Ionosphere Delay Calibration and Calibration Errors for Satellite Navigation of Aircraft
The Federal Aviation Administration (FAA) is implementing a satellite-based navigation system for aircraft using the Global Positioning System (GPS).
satellite-based↗
March 8, 2021: OCO-3 Calibration Update, OCO-2 Calibration Update, OCO-3 B10 Production Needs
No abstract provided
Rosenberg, Rob↗
Calibrate and Prune: Improving Reliability of Lottery Tickets Through Prediction Calibration
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Computer science↗
Exploration of Shear-Dominated Geometries for Material Characterization and Model Calibration; Part 2: Calibration.
Abstract not provided.
Corona, Edmundo↗
LOFTID Heat Flux Gauge Calibration: What is Truth?
The Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) is a demonstration of Hypersonic Inflatable Aerodynamic Decelerator (HIAD) technology, which may enable the delivery of heavy payloads to Mars, Venus, and Titan, as well as return to Earth. Unlike rigid aeroshells that are constrained by the size of the rocket’s shroud, inflatable aeroshells can be deployed to a much larger scale, thus allowing a spacecraft to begin its deceleration earlier and experience less heating. On LOFTID, there will be 4 total heat flux gauges (HFG) with a range of 70 W/cm2 and 1 radiometer with a range of 3 W/cm2, arranged as shown in Fig. 1. Both the radiometer and total HFGs are Schmidt-Boelter gauges purchased from an external vendor. Radiative calibrations were performed in-house at NASA Ames’ Sensors and TPS Advanced Research Laboratories (STAR Labs) before and after environmental testing to investigate how the testing affected the sensors' response. Additional rounds of radiative calibration at STAR Labs were also performed in order to investigate the large uncertainties associated with these tests. For example, a survey of multiple calibration facilities concluded that the uncertainty within a given facility was +/-3% [1]. An additional NIST study that calibrated heat flux gauges at 7 different facilities also found the variation in calibration coefficients to be up to ~3% within a given facility, but up to 15% between facilities, suggesting systematic differences between test setups [2]. Finally, the response of heat flux gauges to radiative versus convective heat flux has shown to differ by up to 20% [3],[4]. Because the heat flux gauges on LOFTID will predominantly experience convective heat flux during flight, a convective calibration study was performed at Boeing's Large-Core Arc Tunnel (LCAT) facility. Radiative Calibration Procedure The calibrations performed at STAR Labs utilize a quartz lamp bank (QLB) that provides a maximum heat flux of 50 W/cm2, which bounds the expected LOFTID flight environment. The calibration involves exposing a water-cooled Gardon gauge (reference) and then the unit-under-test (UUT) to 5 different heat fluxes multiple times for 10 seconds each, and then calculating a linear fit. The test setup is shown in Fig. 2. The total HFGs were calibrated at STAR Labs 3 times, denoted as STAR 1 (before environmental testing), STAR 2 (after protoflight vibration and thermal-vacuum testing), and STAR 3 (no change from previous test). All 8 flight-lot total HFGs showed a decrease in full-scale output from STAR 1 to STAR 2 by between 0.5% and 10. The first portion of this investigation was to determine whether the change could be due to differences in temperature between the two calibration runs. A typical linear fit to the calibration data was performed using Eq. 1 where q’ is the heat flux in W/cm2, c is the calibration coefficient, and mV is the sensor output. To account for temperature, the data were fit to a nonlinear function that included both the sensor output (mV) and the temperature from the thermocouple embedded inside the HFG near the surface (T): q'=mV/(c1* T + c0}. The residuals between the fits and the actual data points were calculated for every point, and proven to be much smaller for the temperature-compensated fits than for the linear fits for all sensors. An example is shown in Fig. 3. When the temperature-compensated fits from STAR 1 were applied to the STAR 2 data, the residuals did not improve, suggesting that the change in sensitivity between these two calibration runs was not due to temperature. A third round of calibration (STAR 3) was conducted to further address the temperature dependence of the total HFGs, and the resulting sensitivities matched closely to STAR 2 (within 2%). Temperature-compensated calibration curves were once again fit to the data. In this case, when the temperature-compensated fits from STAR 3 were applied to STAR 2 data, the residuals between the fits and STAR 2 data were much lower than the residuals due to the linear fits. This suggests that the changes seen between STAR 1 and STAR 2 were likely due to actual changes in the sensors caused by the environmental testing between the two calibrations. A modification of the original calibration process, in which the UUT was exposed to each heat flux for just 3 seconds (instead of 10) to reduce the temperature increase during the test, was additionally performed on several of the HFGs. In general, the sensitivities were 1-1.5% lower than from the 10-second tests, but the temperatures were also significantly lower. When the temperature-compensated fits from the 10-second tests were applied to the 3-second test data, the residuals were greatly improved than when just using the linear fits, further suggesting that the temperature-compensated fits may lead to better accuracy than the linear fits in flight. Convective Calibration The second portion of this study was to create a mapping between the radiative and convective calibration coefficients. The majority of the heating during flight will be convective, so it is important to understand how the HFG response differs under these conditions. However, there are no standardized methods for convective calibration [5]. Because the TPS aerothermal response models were validated at LCAT, the same facility was chosen for convective calibration of two of the total HFGs (Fig. 4). Preliminary results showed that the full-scale output was 3% and 8% higher in convective heat flux as compared to radiative heat flux. However, tunnel variation may have contributed to noise and uncertainty in the measurements, and more testing and analysis remains to be done. Scope of Presentation The presentation will include an overview of the changes seen in HFG calibration before and after environmental testing, differences between radiative and convective calibrations, the modeling work done to aid in understanding the sensor response to varying environments, and recommended future work.
H S Alpert↗
Calibrating the SPECTACULAR constitutive model using legacy Sandia data for two filled epoxy systems: 828/CTBN/DEA/GMB and 828/DEA/GMB
The SPECTACULAR model is a development extension of the Simplified Potential Energy Clock (SPEC) model. Both models are nonlinear viscoelastic constitutive models used to predict a wide range of time-dependent behaviors in epoxies and other glass-forming materials. This report documents the procedures used to generate SPECTACULAR calibrations for two particulate-filled epoxy systems, 828/CTBN/DEA/GMB and 828/DEA/GMB. No previous SPECTACULAR or SPEC calibration exists for 828/CTBN/DEA/GMB, while a legacy SPEC calibration exists for 828/DEA/GMB. To generate the SPECTACULAR calibrations, a step-by-step procedure was executed to determine parameters in groups with minimal coupling between parameter groups. This procedure has often been deployed to calibrate SPEC, therefore the resulting SPECTACULAR calibration is backwards compatible with SPEC (i.e. none of the extensions specific to SPECTACULAR are used). The calibration procedure used legacy Sandia experimental data stored on the Polymer Properties Database website. The experiments used for calibration included shear master curves, isofrequency temperature sweeps under oscillatory shear, the bulk modulus at room temperature, the thermal strain during a temperature sweep, and compression through yield at multiple temperatures below the glass transition temperature. Overall, the calibrated models fit the experimental data remarkably well. However, the glassy shear modulus varies depending on the experiment used to calibrate it. For instance, the shear master curve, isofrequency temperature sweep under oscillatory shear, and the Young's modulus in glassy compression yield values for the glassy shear modulus at the reference temperature that vary by as much as 15 %. Also, for 828/CTBN/DEA/GMB, the temperature dependence of the glassy shear modulus when fit to the Young's modulus at different temperatures is approximately four times larger than when it is determined from the isofrequency temperature sweep under oscillatory shear. For 828/DEA/GMB, the temperature dependence of the shear modulus determined from the isofrequency temperature sweep under oscillatory shear accurately predicts the Young's modulus at different temperatures. When choosing values for the shear modulus, fitting the glassy compression data was prioritized. The new and legacy calibrations for 828/DEA/GMB are similar and appear to have been calibrated from the same data. However, the new calibration improves the fit to the thermal strain data. In addition to the standard calibrations, development calibrations were produced that take advantage of development features of SPECTACULAR , including an updated equilibrium Helmholtz free energy that eliminates undesirable behavior found in previous work. In addition to the previously mentioned experimental data, the development calibrations require data for the heat capacity during a stress-free temperature sweep to calibrate thermal terms.
36 MATERIALS SCIENCE↗
Radiometric Degradation Curves for the ASTER VNIR Processing Using Vicarious and Lunar Calibrations
The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) onboard Terra platform, which was launched in 1999, has three separate subsystems: a visible and near-infrared (VNIR) radiometer, a shortwave-infrared radiometer, and a thermal-infrared radiometer. The ASTER VNIR bands have been radiometrically corrected for approximately 14 years by the sensor degradation curves estimated from the onboard calibrator according to the original calibration plan. However, this calibration by the onboard calibrator encountered a problem; specifically, it is inconsistent with the results of vicarious calibration and cross calibration. Therefore, the ASTER VNIR processing was applied by the radiometric degradation curves calculated from the results of three calibration approaches, i.e., the onboard calibrator, the vicarious calibration, and the cross calibration since February 2014. Even though the current degradation curves were revised, the inter-band and lunar calibrations show some inconsistencies owing to the different traceability in the bands by different calibration approaches. In this study, the current degradation curves and their problems are explained, and the new curves that are derived from the vicarious calibration with lunar calibration are discussed. The new degradation curves that have the same traceability in the bands will be used for future ASTER VNIR processing.
ASTER; Vicarious calibration; Lunar calibration; R↗
Calibration verification for stochastic agent-based disease spread models
Accurate disease spread modeling is crucial for identifying the severity of outbreaks and planning effective mitigation efforts. To be reliable when applied to new outbreaks, model calibration techniques must be robust. However, current methods frequently forgo calibration verification (a stand-alone process evaluating the calibration procedure) and instead use overall model validation (a process comparing calibrated model results to data) to check calibration processes, which may conceal errors in calibration. In this work, we develop a stochastic agent-based disease spread model to act as a testing environment as we test two calibration methods using simulation-based calibration, which is a synthetic data calibration verification method. The first calibration method is a Bayesian inference approach using an empirically-constructed likelihood and Markov chain Monte Carlo (MCMC) sampling, while the second method is a likelihood-free approach using approximate Bayesian computation (ABC). Simulation-based calibration suggests that there are challenges with the empirical likelihood calculation used in the first calibration method in this context. These issues are alleviated in the ABC approach. Despite these challenges, we note that the first calibration method performs well in a synthetic data model validation test similar to those common in disease spread modeling literature. We conclude that stand-alone calibration verification using synthetic data may benefit epidemiological researchers in identifying model calibration challenges that may be difficult to identify with other commonly used model validation techniques.
60 APPLIED LIFE SCIENCES↗
Wind Tunnel Balance Calibration: Are 1,000,000 Data Points Enough?
Measurement systems are typically calibrated based on standard practices established by a metrology standards laboratory, for example the National Institute for Standards and Technology (NIST), or dictated by an organization's metrology manual. Therefore, the calibration is designed and executed according to an established procedure. However, for many aerodynamic research measurement systems a universally accepted standard, traceable approach does not exist. Therefore, a strategy for how to develop a calibration protocol is left to the developer or user to define based on experience and recommended practice in their respective industry. Wind tunnel balances are one such measurement system. Many different calibration systems, load schedules and procedures have been developed for balances with little consensus on a recommended approach. Especially lacking is guidance the number of calibration data points needed. Regrettably, the number of data points tends to be correlated with the perceived quality of the calibration. Often, the number of data points is associated with ones ability to generate the data rather than by a defined need in support of measurement objectives. Hence the title of the paper was conceived to challenge recent observations in the wind tunnel balance community that shows an ever increasing desire for more data points per calibration absent of guidance to determine when there are enough. This paper presents fundamental concepts and theory to aid in the development of calibration procedures for wind tunnel balances and provides a framework that is generally applicable to the characterization and calibration of other measurement systems. Questions that need to be answered are for example: What constitutes an adequate calibration? How much data are needed in the calibration? How good is the calibration? This paper will assist a practitioner in answering these questions by presenting an underlying theory on how to evaluate a calibration based on objective measures. This will enable the developer and user to design calibrations with quantified performance in terms of their capability to meet the user's objectives and a basis for comparing existing calibrations that may have been developed in an ad-hoc manner.
Rhew, Ray D.↗
Specifying Calibration of Energy-Measuring Equipment
Instruments and standards need to be calibrated periodically to ensure that their use yields accurate measurements. Calibration needs, however, vary in sophistication, based on user expectations. This white paper reviews calibration terminology and standards, and describes best practices that have been developed for a) calibrating measurement equipment to ensure some known level of accuracy, and b) accrediting calibration service providers. Calibration is discussed in the context of metrological traceability, and excerpts from laboratory scopes of accreditation are shared to reveal the diversity of terminology and format among them. In an effort to aid those who currently calibrate measuring equipment or who have new or changing needs for calibrating measuring equipment, rationale is provided for why a specification might be used to request calibration services that meet specific test needs. Given the growing interest in using data to manage the energy consumption of systems, and the increasing number and variety of systems (e.g., building, computing) that can report such information, use cases requiring energy data are used to facilitate further discussion and provide examples. Commercially available service providers who are accredited for energy-measuring equipment calibration are compared and contrasted, and a specification template that might be used for requesting this calibration is presented. The specification template should be tailored to meet each user’s needs. To illustrate, an example set of energy-measuring-equipment test conditions (reflecting the planned usage of the device to be calibrated) is used to develop a customized calibration specification, and commercially available service providers are assessed in terms of their qualifications for calibration to that particular implementation of the specification template.
47 OTHER INSTRUMENTATION↗
Specifying Calibration of Environmental Sensors
The emergence of the Internet of Things is resulting in an increased ability of devices and systems to share data and is generating increasing interest in integrating sensors into a variety of devices deployed in the built environment. The value of such data is a function of how the data can be used. Data-producing devices and systems that enable valuable use-cases in turn can be seen as more valuable. Lighting systems are particularly interesting platforms for integrated sensors. Both indoor and outdoor lighting devices are becoming more connected, and their location is often ideally suited for hosting environmental sensors that can characterize the properties of indoor or outdoor spaces in ways that support a wide variety of use cases, from improving air quality to supporting fault diagnostics and prediction. The value of environmental-sensor-driven use-cases and the lighting systems that house them is dependent to some degree on sensor accuracy. Environmental sensors utilize a wide variety of sensing techniques or technologies and have varying accuracy. More-accurate, laboratory-grade products or reference standards are often used to characterize, refine, calibrate, adjust, and monitor devices that are deployed, or are intended to be deployed, in physical spaces of interest. Sensors or reference standards need to be calibrated periodically to ensure that their use yields accurate measurements. Calibration needs, however, vary in sophistication, based on user and use-case requirements. This paper provides guidance for evaluating the performance of environmental sensors so as to ensure that they meet user or use-case needs. It describes best practices that have been developed for a) calibrating sensors to ensure some known level of accuracy, and b) determining whether calibration-laboratory accreditation meets user or use-case needs. Excerpts from laboratory scopes of accreditation are shared to reveal the diversity of terminology and format among them. In an effort to aid those who currently have sensors calibrated or who have new or changing needs for sensor calibration, rationale is provided for why a specification might be used to request calibration services that meet specific needs. Commercially available calibration-service providers that are accredited for environmental-sensor calibration are compared and contrasted, and a specification template that might be used for requesting this calibration is presented. The specification template should be tailored to meet each user’s needs. To illustrate, an example set of environmental-sensor test conditions (reflecting the planned usage of the device to be calibrated) is used to develop a customized calibration specification, and commercially available service providers are assessed in terms of their qualifications for calibration to that particular implementation of the specification template.
42 ENGINEERING↗
On the Accuracy of the ALMA Flux Calibration in the Time Domain and across Spectral Windows
A diverse array of science goals requires accurate flux calibration of observations with the Atacama Large Millimeter/submillimeter array (ALMA); however, this goal remains challenging due to the stochastic time-variability of the “grid” quasars ALMA uses for calibration. In this work, we use 343.5 GHz (Band 7) ALMA Atacama Compact Array observations of four bright and stable young stellar objects over seven epochs to independently assess the accuracy of the ALMA flux calibration and to refine the relative calibration across epochs. The use of these four extra calibrators allows us to achieve an unprecedented relative ALMA calibration accuracy of ~3%. On the other hand, when the observatory calibrator catalog is not up to date, the Band 7 data calibrated by the ALMA pipeline may have a flux calibration poorer than the nominal 10%, which can be exacerbated by weather-related phase decorrelation when self-calibration of the science target is either not possible or not attempted. We also uncover a relative flux calibration uncertainty between spectral windows of 0.8%, implying that measuring spectral indices within a single ALMA band is likely highly uncertain. We thus recommend various methods for science goals requiring high flux accuracy and robust calibration, in particular, the observation of additional calibrators combined with a relative calibration strategy, and observation of solar system objects for high absolute accuracy.
79 ASTRONOMY AND ASTROPHYSICS↗
Calibrating Laser Gas Measurements by Use of Natural CO2
An improved method of calibration has been devised for instruments that utilize tunable lasers to measure the absorption spectra of atmospheric gases in order to determine the relative abundances of the gases. In this method, CO2 in the atmosphere is used as a natural calibration standard. Unlike in one prior calibration method, it is not necessary to perform calibration measurements in advance of use of the instrument and to risk deterioration of accuracy with time during use. Unlike in another prior calibration method, it is not necessary to include a calibration gas standard (and the attendant additional hardware) in the instrument and to interrupt the acquisition of atmospheric data to perform calibration measurements. In the operation of an instrument of this type, the beam from a tunable diode laser or a tunable quantum-cascade laser is directed along a path through the atmosphere, the laser is made to scan in wavelength over an infrared spectral region that contains one or two absorption spectral lines of a gas of interest, and the transmission (and, thereby, the absorption) of the beam is measured. The concentration of the gas of interest can then be calculated from the observed depth of the absorption line(s), given the temperature, pressure, and path length. CO2 is nearly ideal as a natural calibration gas for the following reasons: CO2 has numerous rotation/vibration infrared spectral lines, many of which are near absorption lines of other gases. The concentration of CO2 relative to the concentrations of the major constituents of the atmosphere is well known and varies slowly and by a small enough amount to be considered constant for calibration in the present context. Hence, absorption-spectral measurements of the concentrations of gases of interest can be normalized to the concentrations of CO2. Because at least one CO2 calibration line is present in every spectral scan of the laser during absorption measurements, the atmospheric CO2 serves continuously as a calibration standard for every measurement point. Figure 1 depicts simulated spectral transmission measurements in a wavenumber range that contains two absorption lines of N2O and one of CO2. The simulations were performed for two different upper-atmospheric pressures for an airborne instrument that has a path length of 80 m. The relative abundance of CO2 in air was assumed to be 360 parts per million by volume (approximately its natural level in terrestrial air). In applying the present method to measurements like these, one could average the signals from the two N2O absorption lines and normalize their magnitudes to that of the CO2 absorption line. Other gases with which this calibration method can be used include H2O, CH4, CO, NO, NO2, HOCl, C2H2, NH3, O3, and HCN. One can also take advantage of this method to eliminate an atmospheric-pressure gauge and thereby reduce the mass of the instrument: The atmospheric pressure can be calculated from the temperature, the known relative abundance of CO2, and the concentration of CO2 as measured by spectral absorption. Natural CO2 levels on Mars provide an ideal calibration standard. Figure 2 shows a second example of the application of this method to Mars atmospheric gas measurements. For sticky gases like H2O, the method is particularly powerful, since water is notoriously difficult to handle at low concentrations in pre-flight calibration procedures.
Webster, Chris↗
Landsat-8 TIRS Thermal Radiometric Calibration Status
The Landsat-8 Thermal Infrared Sensor (TIRS) has been acquiring two-band thermal infrared images of the Earth’s surface since 2013. The calibration of the two-band system has been monitored using the on-board calibrator and validated with vicarious calibration performed by NASA/JPL and RIT since launch. Soon after launch, it was discovered that the instrument had a significant stray light effect that was affecting the radiometric calibration. The stray light was corrected in the processing system in 2017. Since then, it has become apparent that there was an additional radiometric error, based on the vicarious calibration results. With a failure within the primary electronic system and subsequent switch to the redundant electronic system, the TIRS instrument effectively has two separate calibration regimes. The vicarious calibration found a statistically significant calibration error, primarily a constant over time, in Band 11 on the primary electronics (Feb 11,2013 through March 5,2015) of about -0.6K at 300K. The calibration error in Band 10 was smaller though still statistically significant at about 0.2K at 300K. On the redundant side(March 5,2015 to present), the calibration error is more signal dependent than time dependent. Both bands are affected, with Band 10 having an error between 1K and -0.4K (between 273-320K) and Band 11 having an error between 0.8K and -1.44K (between 273-320K).This calibration error will be corrected within the USGS Landsat Product Generation System with the release of Landsat Collection-2 products. The Collection-2 release also includes a correction to the relative radiometric calibration of TIRS data. Striping as a result of poor detector-to-detector normalization has been increasing in the imagery since launch. The TIRS relative radiometric calibration will be updated based on internal calibrator data to remove the stripes on a quarterly basis. The visible stripes are generally at 0.1-0.2% level, though there are some detectors in each band that have changed by 1% or more. The Collection-2 release will result in much more uniform TIRS images.
Julia A Barsi↗
Calibration of passive remote observing optical and microwave instrumentation; Proceedings of the Meeting, Orlando, FL, Apr. 3-5, 1991
Various papers on the calibration of passive remote observing optical and microwave instrumentation are presented. Individual topics addressed include: on-board calibration device for a wide field-of-view instrument, calibration for the medium-resolution imaging spectrometer, cryogenic radiometers and intensity-stabilized lasers for EOS radiometric calibrations, radiometric stability of the Shuttle-borne solar backscatter ultraviolet spectrometer, ratioing radiometer for use with a solar diffuser, requirements of a solar diffuser and measurements of some candidate materials, reflectance stability analysis of Spectralon diffuse calibration panels, stray light effects on calibrations using a solar diffuser, radiometric calibration of SPOT 23 HRVs, surface and aerosol models for use in radiative transfer codes. Also addressed are: calibrated intercepts for solar radiometers used in remote sensor calibration, radiometric calibration of an airborne multispectral scanner, in-flight calibration of a helicopter-mounted Daedalus multispectral scanner, technique for improving the calibration of large-area sphere sources, remote colorimetry and its applications, spatial sampling errors for a satellite-borne scanning radiometer, calibration of EOS multispectral imaging sensors and solar irradiance variability.
Guenther, Bruce W.↗
Towards Automating Spacecraft Attitude Sensor Calibration
With a view towards reducing cost and complexity for spacecraft early mission support at the NASA Goddard Space Flight Center (GSFC), efforts are being made to automate the attitude sensor calibration process. This paper addresses one of the major components needed by such a system. The beneficiaries of an improved calibration process are missions that demand moderate to high precision attitude knowledge or that need to perform accurate attitude slews. Improved slew accuracy reduces the time needed for re-acquisition of fine-pointing after each attitude maneuver, Rapid target acquisition can be very important for astronomical targeting or for off-nadir surface feature targeting by Earth-oriented spacecraft. The normal sequence of on-orbit calibration starts with alignment calibration of the star trackers and possibly the Sun sensor. Their relative alignment needs to be determined using a sufficiently large data set so their fields of view are adequately sampled. Next, the inertial reference unit (IRU) is calibrated for corrections to its alignment and scale factors. The IRU biases are estimated continuously by the onboard attitude control system, but the IRU alignment and scale factors are usually determined on the ground using a batch-processing method on a data set that includes several slews sufficient to give full observability of all the IRU calibration parameters. Finally, magnetometer biases, alignment, and its coupling to the magnetic torquers are determined in order io improve momentum management and occasionally for use in the attitude determination system. The detailed approach used for automating calibrations will depend on whether the automated system resides on the ground or on the spacecraft with an ultimate goal of autonomous calibration. Current efforts focus on a ground-based system driving subsystems that could run either on the ground or onboard. The distinction is that onboard calibration should process the data sequentially rather than in a single large batch since onboard computer data storage is limited. Very good batch- processing calibration utilities have been developed and used extensively at NASA/GSFC for mission support but no sequential calibration utilities are available. To meet this need, this paper presents the mathematical description of a sequential IRU calibration system. The system has been tested using flight data from the Rossi X-ray Timing Explorer (RXTE) during a series of attitude slews. The paper also discusses the current state of the overall automated system and describes plans for adding sequential alignment calibration and other additions that will reduce the amount of analyst time and input.
Sedlak, Joseph↗