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A system which allows the transfer of experimental data from one or more transient recorders to a digital computer, the entry of calibration data and the entry of archival data is described. The overall approach is discussed and illustrated in detail.
Developments concerning the period-luminosity (PL) relation for classical Cepheids are discussed with particular emphasis on the fact that Cepheids continue to provide the most homogeneous and reliable set of distances to many nearby galaxies. Observational programs relating to extragalactic Cepheids are also reviewed, and new distances and reddenings to individual galaxies are determined from these data using multiwavelength PL relations, based for the first time on self-consistent calibrating data sets. Three recent promising secondary extragalactic distance indicators (Tully-Fisher, planetary nebula luminosity functions, and surface-brightness fluctuations) tie their zero points to the Cepheid distance scale and give globally consistent values for the Hubble constant of about 80 km/sec/Mpc. Tying the Faber-Jackson relation and the supernova distance scales to the Leo and Virgo clusters yields similar results. Such a value for the Hubble constant is marginally inconsistent with new estimates of the ages of globular clusters, and it may prove to be a serious problem for standard cold-dark-matter models of the universe.
Blade displacement measurements using multi-camera photogrammetry techniques were acquired for a full-scale UH-60A rotor, tested in the National Full-Scale Aerodynamic Complex 40-Foot by 80-Foot Wind Tunnel. The measurements, acquired over the full rotor azimuth, encompass a range of test conditions that include advance ratios from 0.15 to 1.0, thrust coefficient to rotor solidity ratios from 0.01 to 0.13, and rotor shaft angles from -10.0 to 8.0 degrees. The objective was to measure the blade displacements and deformations of the four rotor blades and provide a benchmark blade displacement database to be utilized in the development and validation of rotorcraft prediction techniques. An overview of the blade displacement measurement methodology, system development, and data analysis techniques are presented. Sample results based on the final set of camera calibrations, data reduction procedures and estimated corrections that account for registration errors due to blade elasticity are shown. Differences in blade root pitch, flap and lag between the previously reported results and the current results are small. However, even small changes in estimated root flap and pitch can lead to significant differences in the blade elasticity values.
Since the founding of the NASA Orbital Debris Program Office (ODPO) in 1979, the knowledge that orbital debris poses a risk to operational satellites and human spaceflight has been publically available. Services that rely on satellite-based technology such as communications, internet, navigation, and weather forecasting, to name a few, are ubiquitous in modern society. The International Space Station (ISS) has been continuously inhabited by a crew of up to six astronauts since November 2000 and makes, on average, approximately one debris avoidance maneuver per year to avoid objects that are large enough to be tracked by ground-based radars. This places an increased need for understanding the current status of the debris environment (measurements), for the ability to predict the future environment (modeling), and for understanding risk factors for debris creating events (mitigation). For NASA, the measurements, modeling, and mitigation aspects of orbital debris are led by the NASA ODPO at the Johnson Space Center (JSC) in Houston, Texas.This report summarizes radar measurement data from the Haystack Ultra-wideband Satellite Imaging Radar (HUSIR) operated by the Massachusetts Institute of Technology Lincoln Laboratory (MIT/LL) and provided to the NASA ODPO. The time period covered by this report includes data collected during the U.S. government fiscal year (FY) 2014 through FY2017. The U.S. government FY begins on 1 October and lasts through 30 September of a given year (i.e., FY2014 lasts from 1 October 1 2013 through 30 September 30 2014). At this report’s release, processed data was unavailable from the Haystack Auxiliary Radar (HAX) due to errors in the calibration data for the radar and limited transmit power; a decision was made by NASA not to collect low-power HAX radar data. This is being resolved by NASA and MIT/LL and data collected during this time period will be released in a separate report.
The aerosol optical depth over the Konza Prairie, near Manhattan, Kansas, was recorded at various locations by five separate teams. These measurements were made in support of the First ISLSCP Field Experiment (FIFE) and used to correct imagery from a variety of satellite and aircraft sensors for the effects of atmospheric scattering and absorption. The results from one instrument are reported here for 26 days in 1987 and for 7 in 1989. Daily averages span a range of 0.05 to 0.28 in the midvisible wavelengths. In addition, diurnal variations are noted in which the afternoon optical depths are greater than those of the morning by as much as 0.07. A comparison between instruments and processing techniques used to determine these aerosol optical depths is provided. The first comparisons are made using summer 1987 data. Differences of as much as 0.05 (midvisible) are observed. Although these data allow reasonable surface reflectance retrievals, they do not agree to within the performance limits typically associated with these types of instruments. With an accuracy goal of 0.02 a preseason calibration/comparison experiment was conducted at a mountain site prior to the final field campaign in 1989. Good calibration data were obtained, and good agreement (0.01, midvisible) was observed in the retrieved optical depth acquired over the Konza. By comparing data from the surface instruments at different locations, spatial inhomogeneities are determined. Then, data from the airborne tracking sunphotometer allow one to determine variations as a function of altitude. Finally, a technique is proposed for using the in situ data to establish an instrument calibration.
Equilibrium position and orientation of acoustically-levitated weightless object determined by calibration technique on Earth. From calibration data, possible to calculate equilibrium position and orientation in presence of Earth gravitation. Sample not levitated acoustically during calibration. Technique relies on Boltzmann-Ehrenfest adiabatic-invariance principle. One converts resonant-frequency-shift data into data on normalized acoustical potential energy. Minimum of energy occurs at equilibrium point. From gradients of acoustical potential energy, one calculates acoustical restoring force or torque on objects as function of deviation from equilibrium position or orientation.
Descriptions of the energetic particle detector are offered with calibration data, as part of a user's guide to the data obtained by ATS 6. Information on instrumental and operational anomalies and a description of the procedures used to reduce the data are also presented along with a description of the format of the data.
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.
Construction and calibration are reported for a 6-sq m scintillation counter consisting of two pieces of clear Lucite optically joined along a common edge, sixteen squares of plastic scintillator optically coupled on top of the Lucite, and eight photomultiplier tubes for light collection. Calibration of this counter using an anticoincidence counter to exclude multiple particle events is described. Theoretical calculations for purely electromagnetic extensive air showers indicate that this counter should detect an average of 2.5 particles per event, while the calibration data yield about 1.8 particles per event. It is shown that the anticoincidence-counter calibration method must be used for counters with areas of more than a few square meters if calibration on the response from a single particle of an extensive air shower is desired.
A NICMOS II array, a NIR (0.80 - 2.6 micron) imaging system, was integrated into the California Institute of Technology Palomar Observatory camera. The Palomar camera system which consists of six discrete subsystems including a focal plane, an electrical interface, data acquisition electronics, a dewar, dewar optics, and the software is described. The performance and calibration data for each subsystem are presented. Emphasis is placed on test data on the focal plane performance.
A semi-analytical algorithm was tested with a total of 733 points of either unpackaged or packaged-pigment data, with corresponding algorithm parameters for each data type. The 'unpackaged' type consisted of data sets that were generally consistent with the Case 1 CZCS algorithm and other well calibrated data sets. The 'packaged' type consisted of data sets apparently containing somewhat more packaged pigments, requiring modification of the absorption parameters of the model consistent with the CalCOFI study area. This resulted in two equally divided data sets. A more thorough scrutiny of these and other data sets using a semianalytical model requires improved knowledge of the phytoplankton and gelbstoff of the specific environment studied. Since the semi-analytical algorithm is dependent upon 4 spectral channels including the 412 nm channel, while most other algorithms are not, a means of testing data sets for consistency was sought. A numerical filter was developed to classify data sets into the above classes. The filter uses reflectance ratios, which can be determined from space. The sensitivity of such numerical filters to measurement resulting from atmospheric correction and sensor noise errors requires further study. The semi-analytical algorithm performed superbly on each of the data sets after classification, resulting in RMS1 errors of 0.107 and 0.121, respectively, for the unpackaged and packaged data-set classes, with little bias and slopes near 1.0. In combination, the RMS1 performance was 0.114. While these numbers appear rather sterling, one must bear in mind what mis-classification does to the results. Using an average or compromise parameterization on the modified global data set yielded an RMS1 error of 0.171, while using the unpackaged parameterization on the global evaluation data set yielded an RMS1 error of 0.284. So, without classification, the algorithm performs better globally using the average parameters than it does using the unpackaged parameters. Finally, the effects of even more extreme pigment packaging must be examined in order to improve algorithm performance at high latitudes. Note, however, that the North Sea and Mississippi River plume studies contributed data to the packaged and unpackaged classess, respectively, with little effect on algorithm performance. This suggests that gelbstoff-rich Case 2 waters do not seriously degrade performance of the semi-analytical algorithm.
Intelligent sensor technology and systems are increasingly becoming attractive means to serve as frameworks for intelligent rocket test facilities with embedded intelligent sensor elements, distributed data acquisition elements, and onboard data acquisition elements. Networked intelligent processors enable users and systems integrators to automatically configure their measurement automation systems for analog sensors. NASA and leading sensor vendors are working together to apply the IEEE 1451 standard for adding plug-and-play capabilities for wireless analog transducers through the use of a Transducer Electronic Data Sheet (TEDS) in order to simplify sensor setup, use, and maintenance, to automatically obtain calibration data, and to eliminate manual data entry and error. A TEDS contains the critical information needed by an instrument or measurement system to identify, characterize, interface, and properly use the signal from an analog sensor. A TEDS is deployed for a sensor in one of two ways. First, the TEDS can reside in embedded, nonvolatile memory (typically flash memory) within the intelligent processor. Second, a virtual TEDS can exist as a separate file, downloadable from the Internet. This concept of virtual TEDS extends the benefits of the standardized TEDS to legacy sensors and applications where the embedded memory is not available. An HTML-based user interface provides a visual tool to interface with those distributed sensors that a TEDS is associated with, to automate the sensor management process. Implementing and deploying the IEEE 1451.1-based Network-Capable Application Process (NCAP) can achieve support for intelligent process in Integrated Systems Health Management (ISHM) for the purpose of monitoring, detection of anomalies, diagnosis of causes of anomalies, prediction of future anomalies, mitigation to maintain operability, and integrated awareness of system health by the operator. It can also support local data collection and storage. This invention enables wide-area sensing and employs numerous globally distributed sensing devices that observe the physical world through the existing sensor network. This innovation enables distributed storage, distributed processing, distributed intelligence, and the availability of DiaK (Data, Information, and Knowledge) to any element as needed. It also enables the simultaneous execution of multiple processes, and represents models that contribute to the determination of the condition and health of each element in the system. The NCAP (intelligent process) can configure data-collection and filtering processes in reaction to sensed data, allowing it to decide when and how to adapt collection and processing with regard to sophisticated analysis of data derived from multiple sensors. The user will be able to view the sensing device network as a single unit that supports a high-level query language. Each query would be able to operate over data collected from across the global sensor network just as a search query encompasses millions of Web pages. The sensor web can preserve ubiquitous information access between the querier and the queried data. Pervasive monitoring of the physical world raises significant data and privacy concerns. This innovation enables different authorities to control portions of the sensing infrastructure, and sensor service authors may wish to compose services across authority boundaries.
As part of a joint partnership between the NASA Aviation Safety Program (AvSP) and the University of Tennessee Space Institute (UTSI), research on advanced air data calibration methods has been in progress. This research was initiated to expand a novel pitot-static calibration method that was developed to allow rapid in-flight calibration for the NASA Airborne Subscale Transport Aircraft Research (AirSTAR) facility. This approach uses Global Positioning System (GPS) technology coupled with modern system identification methods that rapidly computes optimal pressure error models over a range of airspeed with defined confidence bounds. Subscale flight tests demonstrated small 2-σ error bounds with significant reduction in test time compared to other methods. Recent UTSI full scale flight tests have shown airspeed calibrations with the same accuracy or better as the Federal Aviation Administration (FAA) accepted GPS 'four-leg' method in a smaller test area and in less time. The current research was motivated by the desire to extend this method for inflight calibration of angle of attack (AOA) and angle of sideslip (AOS) flow vanes. An instrumented Piper Saratoga research aircraft from the UTSI was used to collect the flight test data and evaluate flight test maneuvers. Results showed that the output-error approach produces good results for flow vane calibration. In addition, maneuvers for pitot-static and flow vane calibration can be integrated to enable simultaneous and efficient testing of each system.
Data from a five-component semi-span balance is used to perform a systematic comparison of the load prediction accuracy of two load prediction methods. Both methods independently obtain the load prediction equations from multivariate least squares fits of balance calibration data. The first method is called the Non-Iterative Method. This approach directly uses regression models of the individual load components of a balance for the load prediction. The second method is called the Iterative Method. This alternate approach uses a load iteration equation for the load prediction that is constructed from the regression coefficients of the gage outputs of the balance. Basic characteristics of the two methods are reviewed. Afterwards, both methods are applied to calibration, check load, and wind tunnel test data of a five-component semi-span balance. Selected analysis results are compared. These comparisons confirm that the accuracy of the two methods is the same for all practical purposes.
Sun calibration data from Landsat-2 are presented and compared with those from Landsat-1 (ERTS-1). The data support the hypothesis that organic contamination caused the poor performance of the Landsat-1 sun calibration mirror, since extra cleanliness precautions were taken with the Landsat-2 mirror. These precautions are described; of particular importance was the aluminum foil covering kept close to the reflective surfaces of the second mirror during the prelaunch period.
Since the launch of the Hubble Space Telescope (HST) the secondary mirror of the telescope has been moved several times in order to collimate the telescope and also to define a position of best focus. In addition to these moves the focus position changes over time because of water desorption by the graphite epoxy in the metering truss. The authors report here the focus history of the telescope based on a knowledge of the mirror moves made and an analysis of desorption monitoring data obtained by the Faint Object Camera (FOC) in the F/96 mode and of the routine calibration data obtained by the Wide Field and Planetary Cameras. Focus values are extracted using two different methods. In the first method the distance between the center of the point spread function (PSF) and the shadows of the pads supporting the HST primary mirror are related to the focus error. In the second method an analytical formula for the PSF with variable aberration coefficients is fitted to the data. Focus positions derived from the two methods show good agreement. The data show that a desorption of about 83 microns has taken place since Aug. 16, 1990. The desorption has clearly not leveled off as expected from the trend of the earlier data. Long term variations of the secondary mirror position of approximately 3-15 microns from the 'best' focus position have been observed. Variations of the order of 2-5 microns over an orbital period have also been noted. Focus changes resulting from secondary mirror movements greater than approximately 5 microns changes the point spread function significantly and makes deconvolution and quantitative measurements difficult.
We present the formation of a new global-ground based eye-safe lidar network, the NASA Micro-Pulse Lidar Network (MPLNET). The aim of MPLNET is to acquire long- term observations of aerosol and cloud vertical profiles at unique geographic sites within the NASA Aerosol Robotic Network (AERONET). MPLNET utilizes standard instrumentation and data processing algorithms for efficient network operations and direct comparison of data between each site. The micro-pulse lidar is eye-safe, compact, and commercially available, and most easily allows growth of the network without sacrificing standardized instrumentation goals. Network growth follows a federated approach, pioneered by AERONET, wherein independent research groups may join MPLNET with their own instrument and site. MPLNET sites produce not only vertical profile data, but also column-averaged products already available from AERONET (aerosol optical depth, sky radiance, size distributions). Algorithms are presented for each MPLNET data product. Real-time Level 1 data products (next-day) include daily lidar signal images from the surface to -2Okm, and Level 1.5 aerosol extinction profiles at times co-incident with AERONET observations. Quality assured Level 2 aerosol extinction profiles are generated after screening the Level 1.5 results and removing bad data. Level 3 products include continuous day/night aerosol extinction profiles, and are produced using Level 2 calibration data. Rigorous uncertainty calculations are presented for all data products. Analysis of MPLNET data show the MPL and our analysis routines are capable of successfully retrieving aerosol profiles, with the strenuous accounting of uncertainty necessary for accurate interpretation of the results.
The Advanced Technology Microwave Sounder (ATMS) microwave radiometer instrument is utilized on-board NOAA’s Joint Polar Satellite System (JPSS) fleet of spacecraft to perform temperature and water vapor soundings of Earth’s atmosphere. Consisting of 22 channels over a frequency range from 22 to 183 GHz, ATMS provides high-impact observations for numerical weather prediction (NWP) models. A general description of the ATMS instrument is discussed in [1]. There are five ATMS flight units in the polar-orbiting JPSS program; three are currently on-orbit and two are pending launch. The first ATMS was flown on the Suomi National Polar-orbiting Partnership (SNPP) satellite, launched in 2011. The second ATMS was launched on the NOAA-20 (previously JPSS-1) satellite in 2017. The third ATMS was launched on the NOAA-21 (previously JPSS-2) satellite in 2022. The SNPP and NOAA-20 ATMS units are operational. The NOAA-21 ATMS unit is completing on-orbit commissioning and checkout, having achieved provisional maturity status in December 2022 with validated maturity expected in May 2023 [2]. The fourth and fifth ATMS units are planned for the JPSS-3 (launch ~2028) and JPSS-4 (launch ~2032) satellites [3]. This paper will focus on trending performance characteristics of each JPSS ATMS build from the pre-launch activities. Pre-launch trending of some parameters have been previously published up to the JPSS-3 mission [4][5]. This paper differs from and expands the scope of the prior work as it will include all five of the JPSS ATMS builds. The entire suite of JPSS ATMS units have completed their pre-ship instrument-level I&T and verification activities. These activities include a radiometric performance characterization of each instrument. In addition to comparing the performance across builds, the performance will also be compared to requirements and specifications where applicable. The on-orbit performance of the launched units will be excluded from the scope of this paper in order to focus on evaluations that are common across all builds. The post-launch performance of SNPP ATMS is detailed in [1][6][7][8]. The post-launch performance of NOAA-20 ATMS is detailed in [6][8][9]. The pre-launch characterization of the ATMS occurs at both subassembly-level and instrument-level testing. The antenna subsystem is tested at Northrop Grumman’s Compact Antenna Test Range (CATR) in Azusa, CA [9]. This testing characterizes the antenna pattern and the pointing performance of the scan drive mechanism and antenna subsystem. Trended parameters from this evaluation will include beam pointing accuracy, beamwidth, and beam efficiency. These parameters are captured in each instrument’s Calibration Data Book [10]. Instrument-level radiometric performance evaluation is primarily done during thermal vacuum (TVAC) calibration testing at Northrop Grumman’s Azusa, CA facility [9]. A general description of the calibration activities is presented in [1][9]. The testing involves inferring a scene target brightness temperature (TB) and comparing it to the actual scene TB while the instrument is at flight-like temperature and pressure environmental conditions. Trended parameters from this activity will include Noise Equivalent Delta Temperature (NEDT), nonlinearity, radiometric accuracy, gain stability, striping, and inter-channel noise correlation. The trending evaluation will allow for a direct comparison of the ATMS performance across builds. The paper will highlight observed performance improvements.