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At least 1,081 records · Page 60

A noncontacting motion monitoring system for an astronaut translation aid

The development of a noncontacting motion sensing system designed to monitor the movement of a cart along a track in the low earth orbit space environment is described. The system uses Hall effect sensors to detect the position of small permanent magnets located along the track. The measurement criteria are described, the system design is discussed, and estimates of the system error are given. The system will be used on the Crew and Equipment Translation Aid (CETA) experiment scheduled for the STS37 flight in November 1990. It will allow the position, velocity, and acceleration of the cart to be determined as it moves along the track.

Finley, Tom D.↗

Improvements in navigation resulting from the use of dual spacecraft radiometric data

If two spacecraft lying along similar geocentric lines-of-sight are simultaneously tracked by two nearby ground stations (dual spacecraft two-station tracking), navigational capabilities may be substantially improved. A thorough accuracy analysis study of dual spacecraft tracking using simulated tracking data based on the trajectories of Viking and Mariner Jupiter-Saturn '77(MJS '77) missions has been carried out. Results of the study reveal the following advantages: (1) cancellation of platform parameter and transmission media modelling errors in short arc solutions, (2) accurate encounter guidance for the trailing spacecraft, (3) reduction of total tracking time requirements, and (4) rapid determination of the orbit following a maneuver on either spacecraft. It is shown that dual spacecraft data types can improve navigational capabilities by a factor of 5 to 10, under the conditions of small angular separation (not exceeding 3 degrees) of the two spacecraft and well determined trajectory of the reference spacecraft. The research to carry out and the data to obtain before the new technique can be used in interplanetary navigation are pointed out.

Chao, C. C.↗

Swarm Flyby Gravimetry

This study describes a new technology for discerning the gravity fields and mass distribution of a solar system small body, without requiring dedicated orbiters or landers. Instead of a lander, a spacecraft releases a collection of small, simple probes during a flyby past an asteroid or comet. By tracking those probes from the host spacecraft, one can estimate the asteroid's gravity field and infer its underlying composition and structure. This approach offers a diverse measurement set,equivalent to planning and executing many independent and unique flyby encounters of a single spacecraft. This report assesses a feasible hardware implementation, derives the underlying models,and analyzes the performance of this concept via simulation.In terms of hardware, a small, low mass, low cost implementation is presented, which consists of a dispenser and probes. The dispenser contains roughly 12 probes in a tube and has a total size commensurate with a 6U P-Pod. The probes are housed in disc shaped sabots. When commanded,the dispenser ejects the top-most probe using a linear motor. The ejected probe separates from its sabots and unfolds using internal springs. There are two types of probes, each designed for a particular tracking modality. The reflective probe type, tracked by a telescope, unfolds to forma diffusely reflective sphere. The retroreflector probe type, tracked by a lidar, unfolds to form a corner-cube retroreflector assembly. Both types are designed to spherical so that their attitude doesn't affect the spacecraft's tracking performance.This analysis indicates that the point-mass term of small bodies larger than roughly 500 m in diameter can be observed from a host spacecraft that tracks locally deployed probes throughout a flyby to an uncertainty of better than 5%. The conditions by which this measurement is possible depends on the characteristics of the asteroid (size, type), the flyby velocity, and the type of tracking available (angles-only or angles+ranging). For most encounters, a few (1-3) well placed probes can be very effective, with marginal improvement for additional probes. Given realistic deployment errors, an encounter may require roughly 10-12 probes to ensure that 1-3 achieve their target. Long duration tracking of probes flying by large asteroids (>5 km diameter) can sometimes provide observability of the gravity field's first spherical harmonic, J( sub 2). In summary, this method offers a feasible, affordable approach to enabling or augmenting flyby science.

Atchison, Justin↗

A preliminary error analysis of the gravity field recovery from a lunar Satellite-to-Satellite mission

A low cost lunar Satellite-to-Satellite radio tracking mission in a low-low configuration could considerably improve the existing knowledge about the lunar gravity field. The impact of various mission parameters that may contribute to the recovery of the gravity field, such as satellite altitude, satellite separation mission duration, measurement precision and sampling interval were quantified using the Jekeli-Rapp algorithm. Preliminary results indicate that the gravity field resolution up to harmonic degree 40 to 80 is feasible depending on various mission configurations. Radio tracking data from a six-month mission with a precision of 1 mm/s every 10 s and 300 km satellite separation at 150 km altitude will permit the determination of 5 deg x 5 deg mean gravity anomalies with an error of approximately 15 mgals. Consideration of other unaccounted error sources of instrumental, operational, and environmental nature may lower this resolution.

Iz, Huseyin B.↗

Full-Carpet Design of a Low-Boom Demonstrator Concept

The Cart3D adjoint-based design framework is used to mitigate the undesirable o -track sonic boom properties of a demonstrator concept designed for low-boom directly under the flight path. First, the requirements of a Cart3D design mesh are determined using a high-fidelity mesh adapted to minimize the discretization error of the CFD analysis. Low-boom equivalent area targets are then generated at the under-track and one off-track azimuthal position for the baseline configuration. The under-track target is generated using a trim- feasible low-boom target generation process, ensuring that the final design is not only low-boom, but also trimmed at the specified flight condition. The o -track equivalent area target is generated by minimizing the A-weighted loudness using an efficient adjoint-based approach. The configuration outer mold line is then parameterized and optimized to match the off-body pressure distributions prescribed by the low-boom targets. The numerical optimizer uses design gradients which are calculated using the Cart3D adjoint- based design capability. Optimization constraints are placed on the geometry to satisfy structural feasibility. The low-boom properties of the final design are verified using the adaptive meshing approach. This analysis quantifies the error associated with the CFD mesh that is used for design. Finally, an alternate mesh construction and target positioning approach offering greater computational efficiency is demonstrated and verified.

Ordaz, Irian↗

Simulation investigation of multipactor in metal components for space application with an improved secondary emission model

Effects of the secondary electron emission (SEE) phenomenon of metal surface on the multipactor analysis of microwave components are investigated numerically and experimentally in this paper. Both the secondary electron yield (SEY) and the emitted energy spectrum measurements are performed on silver plated samples for accurate description of the SEE phenomenon. A phenomenological probabilistic model based on SEE physics is utilized and fitted accurately to the measured SEY and emitted energy spectrum of the conditioned surface material of microwave components. Specially, the phenomenological probabilistic model is extended to the low primary energy end lower than 20 eV mathematically, since no accurate measurement data can be obtained. Embedding the phenomenological probabilistic model into the Electromagnetic Particle-In-Cell (EM-PIC) method, the electronic resonant multipacting in microwave components can be tracked and hence the multipactor threshold can be predicted. The threshold prediction error of the transformer and the coaxial filter is 0.12 dB and 1.5 dB, respectively. Simulation results demonstrate that the discharge threshold is strongly dependent on the SEYs and its energy spectrum in the low energy end (lower than 50 eV). Multipacting simulation results agree quite well with experiments in practical components, while the phenomenological probabilistic model fit both the SEY and the emission energy spectrum better than the traditionally used model and distribution. The EM-PIC simulation method with the phenomenological probabilistic model for the surface collision simulation has been demonstrated for predicting the multipactor threshold in metal components for space application.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Combined Mesonet and Tracker

Title: Combined Mesonet and Trackers (UNL Mobile Mesonets) Authors University of Nebraska PI: Adam Houston, UNL Professor (ahouston2@unl.edu) Mailing Address: 126 Bessey Hall P.O. Box 880340 Lincoln, NE 68588-0340 CoMeT Overview The University of Nebraska-Lincoln operates three Combined Mesonet and Tracker (CoMeTs). CoMeTs are Ford Explorers (model years 2015, 2017, and 2019) with forward-mounted suites of meteorological sensors and dual moonroofs, combining the capability of a mobile mesonet to collect near-surface observations with the capability of an unmanned aircraft systems (UAS) tracker vehicle, which enables an observer in the second row of seats to see the aircraft and maintain compliance with Federal Aviation Administration policies on UAS operation. The CoMeTs collect observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155A, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, and vehicle heading using a KVH Industries C-100 fluxgate compass (Barbieri et al. 2019). The HMP155A and 109SS-L thermistor are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). This list of sensors is also included in the CoMeT data file metadata. Manufacturer specifications for these instruments are given in Table 1 of Hanft and Houston (2018). The reported measured quantities are summarized below.CoMeT-3 was funded through an equipment allocation included in the NSF TORUS award (AGS-1824649). Instrument Description The specific sensors included on each CoMeT are summarized in the table at the end of this section. In general each CoMeT collects observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210 barometer with a Gill pressure port, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, position using a Garmin 19x HVS receiver, and vehicle heading using a KVH Industries C-100 fluxgate compass. The HMP155 and 109SS are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). Fast temperature and corrected RH measurements (using sensors housed within the U-tube) have a time constant of 10-12 s based on data collected across a temperature and RH shock during the CLOUD-MAP 2017 calibration/validation tests on June 26, 2017. Vehicle speed was < 10 kts for this test. CoMeT-1 CoMeT-2 CoMeT-3 Slow Temperature Slow RH Vaisala HMP155A-L20-PT Part #: 22280-7 Vaisala HMP155E Part #: E1AA11A0B1A1A0A Vaisala HMP155E Part #: E1AA11A0B1A1A0A Fast temperature Campbell Scientific 109SS-L20-PT Part #: 21448-3 Campbell Scientific 109SS-L12-PW Part #: 21448-109 Campbell Scientific 109SS-L12-PW Part #: 21448-150 Pressure Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Wind RM Young 05103-L20-PT Part #: 18435-310 RM Young 05103-L20-PW Part #: 18435-244 RM Young 05103-L20-PW Part #: 18435-244 GPS Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Compass KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 Logger Campbell Scientific CR6-NA-XT-SW Part #: 28385-9 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Data Collection and Real-Time Processing The reported measured quantities are summarized in the table below. Quantity Units Source Epoch time Seconds GPS Latitude and longitude Degrees GPS Altitude m GPS Pressure hPa PTB210 Temperature (fast) deg C 109SS-L Temperature (slow) deg C HMP155 RH (slow) % HMP155 Vehicle speed m/s GPS Vehicle heading deg C-100 and GPS In addition to the measured variables, several derived variables are calculated. Corrected/fast relative humidity (%) Relative humidity is adjusted to the fast temperature following Richardson et al. (1998) and Houston et al. (2016). Water vapor mixing ratio (g/kg) Dew point temperature (&deg;C) Potential temperature (Kelvin) Virtual potential temperature (Kelvin) Equivalent potential temperature (Kelvin) Regular intercomparisons between all three CoMeTs were performed during TORUS 2019. Comparisons were also conducted between CoMeT-1 and CoMeT-2 during LAPSE-RATE (2018) on 14 July. In these intercomparisons, the vehicles were parked adjacent to each other aligned perpendicular to (and facing into) the wind. To minimize engine heating effects, intercomparisons were only conducted when the wind speed was >10 kts. Data Format Original data files for each deployment are saved as text files and then converted to NetCDF. NetCDF versions have units that are CF compliant and may not match the original units in the txt files. The naming convention for the NetCDF files is as follows: UNL.CoMeT3.{deployment date YYYYMMDD}.{start time of observation collection in UTC HHMM}.L2.{post-processing codes}.cdf example: UNL.CoMeT3.20190627.1931.L2.g1.f1.cdf Post-processing codes are included to track modifications to the raw data. These codes are closely connected to error flags associated with each record. Each letter corresponds to a particular instrument: g: GPS p: Barometer tf: Fast temperature ts: Slow temperature rh: Relative humidity f: Compass w: Wind monitor a: All instruments Each number corresponds to a particular post-processing action described more below. Measured and derived variables are included in the following table. Variable Heading Standard Name Units time Time seconds since 00:00:00, 01-01-1970 Alt Altitude meters lat Latitude degrees north lon Longitude degrees east fast_temp Air Temperature kelvin slow_temp Air Temperature kelvin pressure Air Pressure pascals logger_RH Relative Humidity percent calc_corr_RH Relative Humidity percent wind_speed Wind Speed meters per second wind_dir Wind From Direction degrees vehicle_dir Vehicle Direction degrees dewpoint Dew Point Temperature kelvin mixing_ratio Humidity Mixing Ratio g/g theta Air Potential Temperature kelvin theta_v Virtual Potential Temperature kelvin theta_e Equivalent Potential Temperature Kelvin error_flag The error_flag variable is a string that matches the post-processing codes listed above. All instruments will have an associated code, but will have a &ldquo;0&rdquo; if the datum is unchanged from the initial processed value. Error Codes The following table summarizes the error codes for data collected before 2020: Error Code Relevant CoMeT Description g1 1,2,3 Exact correction. GPS position and time reprocessed from raw data g2 1 As far as we can tell this is an exact correction to an error in the GPS time. During the correct time periods the time suddenly went backwards ~250s and stayed at this offset for 750s when it corrected itself. The offset was applied to the &ldquo;time warp&rdquo; period. p1 2 Approximate correction. Hole in the pressure tube connecting the pressure port to the barometer. Resulted in erroneously low air pressure measurements when the vehicle was in motion. Derived variables recalculated (dew point temperature [e depends on qv and p], water vapor mixing ratio, potential temperature, virtual potential temperature, equivalent potential temperature) a1 3 Exact correction. Missing data reprocessed from raw data a2 1 Bug fix to bias correction for ts1, ts2, and rh1: water vapor mixing ratio was off by a factor of 10 and virtual potential temperature was wrong because of this. f1 3 No correction, missing data. Fluxgate compass inoperable. Wind speed and direction calculated using GPS-derived vehicle heading instead. rh1 1 Approximate correction. Constant bias of +1.7% removed from relative humidity. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts1 1 Approximate correction. Constant bias of +0.6 K removed from slow temperature. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts2 1 Approximate correction. Constant bias of +1.0 K removed. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) References Bolton, D., 1980: The Computation of Equivalent Potential Temperature. Mon. Wea. Rev., 108, 1046&ndash;1053, https://doi.org/10.1175/1520-0493(1980)108<1046:TCOEPT>2.0.CO;2. Hanft, W., and A. L. Houston, 2018: An Observational and Modeling Study of Mesoscale Air Masses with High Theta-E. Mon. Wea. Rev., 146, 2503&ndash;2524, https://doi.org/10.1175/MWR-D-17-0389.1.Wexler Houston, A. L., R. J. Laurence III, T. W. Nichols, S. Waugh, B. Argrow, and C. L. Ziegler, 2016: Intercomparison of unmanned aircraft-borne and mobile mesonet atmospheric sensors. Journal of Atmospheric and Oceanic Technology. 33, 1569-1582, doi: 10.1175/JTECH-D-15-0178.1. Lowe, P. R., 1977: An Approximating Polynomial for the Computation of Saturation Vapor Pressure. J. Applied Meteorology, 16, 100&ndash;103. Richardson, S. J., S. E. Frederickson, F. V. Brock, and J. A. Brotzge, 1998: Combination temperature and relative humidity probes: Avoiding large air temperature errors and associated relative humidity errors. Preprints, 10th Symp. On Meteorological Observations and Instrumentation, Phoenix, AZ, Amer. Meteor. Soc., 278&ndash;283. Waugh, S., and S. E. Frederickson, 2010: An improved aspirated temperature system for mobile meteorological observations, especially in severe weather. 25th Conf. on Severe Local Storms, Denver, CO, Amer. Meteor. Soc., P5.2. [Available online at https://ams.confex.com/ams/25SLS/techprogram/paper_176205.htm.]

54 ENVIRONMENTAL SCIENCES↗

The autotrack system

The autotrack system accurately senses the direction of arrival, at the horn-reflector antenna, of the microwave beacon signal from the communications satellite. When this direction does not coincide with the horn-reflector pointing direction, error correcting voltages are automatically generated to enable the antenna direction system to steer the antenna toward the satellite. This paper presents a simple analysis of error voltage generation, a description of the system, and a brief discussion of system performance. Measurements at Andover, Maine, have shown that an angular pointing error of less than 0.005 degree is maintained by the antenna when using the autotrack system to follow the Telstar communications satellite.

SATELLITE COMMUNICATION↗

Multipath performance of a TDRS system employing wideband FM VHF signals

An approximate theoretical analysis is presented for the effects of specular reflection multipath on the performance of a one-way tracking and data relay satellite-to-user link. The analysis pertains to the wideband FM system employing a sinusoidal subcarrier to achieve spectrum spreading. Bounds on multipath effects are derived for receivers with and without limiters and for data modulated on the carrier or the subcarrier. For data modulation, performance is evaluated in terms of an additive lowpass signal at the data detection filter. Doppler and range tracking performance is evaluated in terms of root-mean-square (RMS) error of carrier frequency in a carrier PLL and rms phase jitter in a subcarrier PLL.

Sohn, S. J.↗

Hybrid carrier and modulation tracking loops.

The tracking loops presented herein exploit the coherency of the observed data sidebands at the carrier frequency for improvements in phase-coherent tracking, telemetry, and command system performance. The loop is motivated by one aspect of generalized harmonic analysis, viz., the so-called cross spectrum. The basic idea of the loop centers around using the power in the composite received signal (sidebands including cross-modulation components) to enhance the signal-to-noise ratio in the carrier tracking loop, thereby reducing the noisy reference loss and ultimately the subcarrier reference jitter, the symbol sync jitter, and the error probability of the data detector. The modulation from the extracted sidebands is removed in such a way that the coherence power in the data sidebands can be used for tracking at the carrier frequency.

Lindsey, W. C.↗

Conditioning of MVM '73 radio-tracking data

An extensive effort was undertaken to edit Mariner 10 radiometric tracking data. Interactive computer graphics were used for the first time by an interplanetary mission to detect blunder points and spurious signatures in the data. Interactive graphics improved the former process time by a factor of 10 to 20, while increasing reliability. S/X dual Doppler data was used for the first time to calibrate charged particles in the tracking medium. Application of the charged particle calibrations decreased the orbit determination error for a short data arc following the 16 March 1974 maneuver by about 80%. A new model was developed to calibrate the earth's troposphere with seasonal adjustments. The new model has a 2% accuracy and is 5 times better than the old model.

Koch, R. E.↗

Tracker implementation for the orbiter Ku-band communications antenna

Possible implementations and recommendations for the Space Shuttle Ku-Band integrated communications/radar antenna tracking system were evaluated. Communication aspects involving the Tracking Data Relay Satellite (TDRS)/Orbiter Ku-Band link are emphasized. Detailed analysis of antenna sizes, gains and signal-to-noise ratios shows the desirability of using maximum size 36-inch diameter dish and a triple channel monopulse. The use of the original baselined 20 inch dish is found to result in excessive acquisition time since the despread signal would be used in the tracking loop. An evaluation of scan procedures which includes vehicle dynamics, designation error, time for acquisition and probability of acquisition shows that the conical scan is preferred since the time for lock-on for relatively slow look angle rates will be significantly shorter than the raster scan. Significant improvement in spherical coverage may be obtained by reorienting the antenna gimbal to obtain maximum blockage overlap.

Rudnicki, J. F.↗

Integrated source and channel encoded digital communication system design study

The analysis of the forward link signal structure for the shuttle orbiter Ku-band communication system was carried out, based on the assumptions of a 3.03 Mcps PN code. It is shown that acquisition requirements for the forward link can be met at the acquisition threshold C/N0 sub 0 value of about 60 dB-Hz, which corresponds to a bit error rate (BER) of about 0.001. It is also shown that the tracking threshold for the forward link is at about 57 dB-Hz. The analysis of the bent pipe concept for the orbiter was carried out, along with the comparative analysis of the empirical data. The complexity of the analytical approach warrants further investigation to reconcile the empirical and theoretical results. Techniques for incorporating a text and graphics capability into the forward link data stream are considered and a baseline configuration is described.

Udalov, S.↗

A numerical model for low-latitude ionospheric TEC

A numerical model of total electron content (TEC) at low latitudes has been constructed from the Faraday rotation data recorded at a number of locations in India during the period Oct. 1975-July 1976 when the geostationary satellite ATS-6 was located at 35 deg E. In all, 36 coefficients for each season are required to represent the model. The model can be used for satellite tracking systems in estimating quickly the range, range rate and angular refraction errors. The present model is an improvement over the previously constructed model based on orbiting satellite data.

Sethia, G.↗

MAGSAT data processing: A report for investigators

The in-flight attitude and vector magnetometer data bias recovery techniques and results are described. The attitude bias recoveries are based on comparisons with a magnetic field model and are thought to be accurate to 20 arcsec. The vector magnetometer bias recoveries are based on comparisons with the scalar magnetometer data and are thought to be accurate to 3 nT or better. The MAGSAT position accuracy goals of 60 m radially and 300 m horizontally were achieved for all but the last 3 weeks of Magsat lifetime. This claim is supported by ephemeris overlap statistics and by comparisons with ephemerides computed with an independent orbit program using data from an independent tracking network. MAGSAT time determination accuracy is estimated at 1 ms. Several errors in prelaunch assumptions regarding data time tags, which escaped detection in prelaunch data tests, and were discovered and corrected postlaunch are described. Data formats and products, especially the Investigator-B tapes, which contain auxiliary parameters in addition to the basic magnetometer and ephemeris data, are described.

Langel, R. A.↗

The detailed chemistry and thermodynamics of sodium in oxygen-rich flames

Measurement of sodium and OH concentrations in ten oxygen-rich H2/O2/N2 flames by respective saturated and low-power laser induced fluorescence techniques have permitted a detailed examination of the pronounced flame chemistry of sodium in such oxygen rich media. Previous interpretations have been shown to be largely incomplete or in error. The flame downstream profiles indicate that the amount of free sodium tracks the decay of H-atom and as the flame radicals decay sodium becomes increasingly bound in a molecular form. A detailed kinetic model indicates that the sodium is distributed between NaOH and NaO2 species. Concentrations of NaO are very small and NaH negligible. The actual distribution is controlled by the state of equilibrium of the flames' basic free radicals. Na, NaO2 and NaOH are all coupled to one another by fast reactions which can rapidly interconvert one to another as flame conditions vary. Above about 2000K, NaOH becomes dominant whereas NaO2 plays an increasingly important contribution at lower temperatures.

Hynes, A. J.↗