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At least 73 records · Page 4

Commissioning of the Mu2e Data AcQuisition System and the Vertical Slice Test of the Straw Tracker

The report discusses the commissioning of the DAQ system of the Mu2e experiment. We studied how the tracker works and especially the tracker readout. We used a generator to send pulses and we tried to understand the output and non-output of the DTC, in order to validate the event and run format and all the failure modes. In section one, we describe Charged Lepton Flavour Violation, the main purpose of Mu2e, in section two we describe Mu2e experiment. Section three presents the tracker description and readout, meanwhile section four the DAQ system and event building. In section five, we start explaining the analysis we have done on events and all the failure modes we discovered. In section six, we have done an analysis of the logger and boardreader rate, we validated the generator frequency in section seven and studied the number of hits in function of the channel number in section eight. To conclude we investigated the channel to channel time differences in section nine and in section ten we explain our Monte Carlo simulation, reproducing ROCs readout.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurement of the gas gain and understanding the gas flow in the Mu2e Tracker

The Mu2e experiment will search for the charged-lepton flavor violating (CLFV) neutrinoless conversion of a negative muon into an electron in the field of an Aluminum nucleus µ − N → e − N. The signature of this process is the emission of a monochromatic electron with an energy of 104.97 MeV. The Mu2e Tracker is a low mass straw tube detector, whose aim is to measure the position and the momentum of the electron. In past measurements, high values of currents were found in some panels of the Tracker in absence of any radioactive sources. In this report new measurements of currents, that were taken with the panel MN084 of the Mu2e Tracker are described. Moreover, the addition of a small amount of water vapour in the gas mixture and the influence of the environmental conditions on the currents of the panel are studied.

47 OTHER INSTRUMENTATION↗

Flat TBPS Integration Testing for the CMS Outer Tracker Upgrade

The upcoming High-Luminosity (HL) LHC will significantly increase luminosity, introducing more demanding operating conditions for the CMS detector. To meet these challenges, CMS is undergoing major upgrades, including a complete replacement of its tracking detector. This poster presents recent integration testing efforts conducted at Fermilab on the Flat Tracker Barrel with pixel-strip (PS) modules integration test stand, a subcomponent of the outer tracker located in the central barrel region. In this region, PS modules are mounted on structures that provide mechanical support and cooling, called planks. The testing focuses on validating the integrated system’s thermal and electrical performance. Results from these tests will be discussed, highlighting their importance for ensuring reliable tracker operation in the HL-LHC era.

Salazar Segovia, Itzelli [UC, Davis]↗

Fermilab 2025 Summer Internship Skills Learned from Working with Mu2e Tracker Team

As part of a DOE RENEW Grant, the undergraduate authors interned at Fermilab. They spent nine weeks over summer 2025 working on the tracker team for the Mu2e experiment. They gained practical experience in a multitude of new skills including electronics installation, testing, and repairs. Their work particularly increased productivity by helping repair the high voltage and calibration pre-amplifiers, over 20,000 of which are needed in the tracker. These components are very fragile and often break during the installation process. The experience also taught them several soft skills such as the importance of thoughtful data storage, record- keeping, and problem-solving skills. They learned the demands of a large, international collaboration and how to work in a team. The authors would like to acknowledge their advisor and PI of the grant, Dr. Christopher G. Fasano, and the Mu2e team lead by co- spokesperson Dr. Bob Bernstein and tracker L2 manager Dr. Brendan Kiburg.

de Zwart, Brontë↗

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↗

High Energy Astronomy Observatory star tracker search program

The development of a control system to accommodate the scientific payload of the High Energy Astronomy Observatory (HEAO) is discussed. One of the critical elements of the system is the star tracker subsystem, which defines an accurate three-axis attitude reference. A digital computer program has been developed to evaluate the ability of a particular star tracker configuration to meet the requirements for attitude reference at various vehicle orientations. Used in conjuction with an adequate star catalog, the computer program provides information on availability of stars for each tracker and on the ability of the system to maintain three-axis attitude reference throughout a representative sequence of vehicle orientations.

Weiler, W. J.↗

CCD star trackers

The application of CCDs to star trackers and star mappers is considered. Advantages and disadvantages of silicon CCD star trackers are compared with those of image dissector star trackers. It is concluded that the CCD has adequate sensitivity for most single star tracking tasks and is distinctly superior in multiple star tracking or mapping applications. The signal and noise figures of several current CCD configurations are discussed. The basic structure of the required signal processing is described, and it is shown that resolution in excess of the number of CCD elements may be had by interpolation.

Goss, W. C.↗

Combinations of 148 navigation stars and the star tracker

The angular separation of all star combinations for 148 nav star on the onboard software for space transportation system-3 flight and following missions is presented as well as the separation of each pair that satisfies the viewing constraints of using both star trackers simultaneously. Tables show (1) shuttle star catalog 1980 star position in M 1950 coordinates; (2) two star combination of 148 nav stars; and (3) summary of two star-combinations of the star tracker 5 deg filter. These 148 stars present 10,875 combinations. For the star tracker filters of plus or minus 5 deg, there are 875 combinations. Formalhaut (nav star 26) has the best number of combinations, which is 33.

Duncan, R.↗

Post flight analysis of NASA standard star trackers recovered from the solar maximum mission

The flight hardware returned after the Solar Maximum Mission Repair Mission was analyzed to determine the effects of 4 years in space. The NASA Standard Star Tracker would be a good candidate for such analysis because it is moderately complex and had a very elaborate calibration during the acceptance procedure. However, the recovery process extensively damaged the cathode of the image dissector detector making proper operation of the tracker and a comparison with preflight characteristics impossible. Otherwise, the tracker functioned nominally during testing.

Newman, P.↗

Intelligent robotic tracker

An intelligent tracker capable of robotic applications requiring guidance and control of platforms, robotic arms, and end effectors has been developed. This packaged system capable of supervised autonomous robotic functions is partitioned into a multiple processor/parallel processing configuration. The system currently interfaces to cameras but has the capability to also use three-dimensional inputs from scanning laser rangers. The inputs are fed into an image processing and tracking section where the camera inputs are conditioned for the multiple tracker algorithms. An executive section monitors the image processing and tracker outputs and performs all the control and decision processes. The present architecture of the system is presented with discussion of its evolutionary growth for space applications. An autonomous rendezvous demonstration of this system was performed last year. More realistic demonstrations in planning are discussed.

Otaguro, W. S.↗

EOS attitude determination and next generation star tracker enhancements

The pointing knowledge required for the Earth Observing System (EOS) AM mission is at the limit of the current generation of star trackers, with little margin. Techniques for improving the performance of existing star trackers are explored, with performance sensitivities developed for each alternative. These are extended to define the most significant performance enhancements for a next generation star tracker. Since attitude determination studies tend to be computationally intensive, an approach for using a simpler one degree of freedom formulation is contrasted with a full three degree of freedom formulation. Additionally, covariance analysis results are compared with time domain simulation performance results.

Kudva, P.↗

Measurement and calibration of static distortion of position data from 3D trackers

Three-dimensional trackers are becoming increasingly important as user inputs in interactive computer systems. These trackers output the three-dimensional position, and often the orientation, of a sensor in space. The three-dimensional tracking is often, however, highly distorted and inaccurate. The purpose of this paper is to discuss methods for the measurement and characterization of the static distortion of the position data. When the distortion is constant, various methods can be used to calibrate the data from the tracker to increase accuracy. Several preliminary methods are discussed in this paper, including polynomial and weighted lookup methods. The measurement and calibration methods are applied to the Polhemus electromagnetic tracking system, but are applicable to tracking systems based on other technologies.

Bryson, Steve↗

Miniature wide field-of-view star trackers for spacecraft attitude sensing and navigation

Introducing a family of miniature, wide field-of-view star trackers for low cost, high performance spacecraft attitude determination and navigation applications. These devices, derivative of the WFOV Star Tracker Camera developed cooperatively by OCA Applied Optics and the Lawrence Livermore National Laboratory for the Brilliant Pebbles program, offer a suite of options addressing a wide range of spacecraft attitude measurement and control requirements. These sensors employ much wider fields than are customary (ranging between 20 and 60 degrees) to assure enough bright stars for quick and accurate attitude determinations without long integration intervals. The key benefit of this approach are light weight, low power, reduced data processing loads and high information carrier rates for wide ACS bandwidths. Devices described range from the proven OCA/LLNL WFOV Star Tracker Camera (a low-cost, space-qualified star-field imager utilizing the spacecraft's own computer and centroiding and position-finding), to a new autonomous subsystem design featuring dual-redundant cameras and completely self-contained star-field data processing with output quaternion solutions accurate to 100 micro-rad, 3 sigma, for stand-alone applications.

Mccarty, William↗

Monitoring with Trackers Based on Semi-Quantitative Models

In three years of NASA-sponsored research preceding this project, we successfully developed a technology for: (1) building qualitative and semi-quantitative models from libraries of model-fragments, (2) simulating these models to predict future behaviors with the guarantee that all possible behaviors are covered, (3) assimilating observations into behaviors, shrinking uncertainty so that incorrect models are eventually refuted and correct models make stronger predictions for the future. In our object-oriented framework, a tracker is an object which embodies the hypothesis that the available observation stream is consistent with a particular behavior of a particular model. The tracker maintains its own status (consistent, superceded, or refuted), and answers questions about its explanation for past observations and its predictions for the future. In the MIMIC approach to monitoring of continuous systems, a number of trackers are active in parallel, representing alternate hypotheses about the behavior of a system. This approach is motivated by the need to avoid 'system accidents' [Perrow, 1985] due to operator fixation on a single hypothesis, as for example at Three Mile Island. As we began to address these issues, we focused on three major research directions that we planned to pursue over a three-year project: (1) tractable qualitative simulation, (2) semiquantitative inference, and (3) tracking set management. Unfortunately, funding limitations made it impossible to continue past year one. Nonetheless, we made major progress in the first two of these areas. Progress in the third area as slower because the graduate student working on that aspect of the project decided to leave school and take a job in industry. I enclosed a set of abstract of selected papers on the work describe below. Several papers that draw on the research supported during this period appeared in print after the grant period ended.

Kuipers, Benjamin↗

Compensation for Time-Dependent Star Tracker Thermal Deformation on the Aqua Spacecraft

Analysis of attitude sensor data from the Aqua mission showed small but systematic differences between batch least-squares and extended Kalman filter attitudes. These differences were also found to be correlated with star tracker residuals, gyro bias estimates, and star tracker baseplate temperatures. This paper describes the analysis that shows that these correlations are all consistent with a single cause: time-dependent thermal deformation of star tracker alignments. These varying alignments can be separated into relative and common components. The relative misalignments can be determined and compensated for. The common misalignments can only be determined in special cases.

Hashmall, Joseph A.↗

Combined Feature Based and Shape Based Visual Tracker for Robot Navigation

We have developed a combined feature based and shape based visual tracking system designed to enable a planetary rover to visually track and servo to specific points chosen by a user with centimeter precision. The feature based tracker uses invariant feature detection and matching across a stereo pair, as well as matching pairs before and after robot movement in order to compute an incremental 6-DOF motion at each tracker update. This tracking method is subject to drift over time, which can be compensated by the shape based method. The shape based tracking method consists of 3D model registration, which recovers 6-DOF motion given sufficient shape and proper initialization. By integrating complementary algorithms, the combined tracker leverages the efficiency and robustness of feature based methods with the precision and accuracy of model registration. In this paper, we present the algorithms and their integration into a combined visual tracking system.

Deans, J.↗

2D/3D Visual Tracker for Rover Mast

A visual-tracker computer program controls an articulated mast on a Mars rover to keep a designated feature (a target) in view while the rover drives toward the target, avoiding obstacles. Several prior visual-tracker programs have been tested on rover platforms; most require very small and well-estimated motion between consecutive image frames a requirement that is not realistic for a rover on rough terrain. The present visual-tracker program is designed to handle large image motions that lead to significant changes in feature geometry and photometry between frames. When a point is selected in one of the images acquired from stereoscopic cameras on the mast, a stereo triangulation algorithm computes a three-dimensional (3D) location for the target. As the rover moves, its body-mounted cameras feed images to a visual-odometry algorithm, which tracks two-dimensional (2D) corner features and computes their old and new 3D locations. The algorithm rejects points, the 3D motions of which are inconsistent with a rigid-world constraint, and then computes the apparent change in the rover pose (i.e., translation and rotation). The mast pan and tilt angles needed to keep the target centered in the field-of-view of the cameras (thereby minimizing the area over which the 2D-tracking algorithm must operate) are computed from the estimated change in the rover pose, the 3D position of the target feature, and a model of kinematics of the mast. If the motion between the consecutive frames is still large (i.e., 3D tracking was unsuccessful), an adaptive view-based matching technique is applied to the new image. This technique uses correlation-based template matching, in which a feature template is scaled by the ratio between the depth in the original template and the depth of pixels in the new image. This is repeated over the entire search window and the best correlation results indicate the appropriate match. The program could be a core for building application programs for systems that require coordination of vision and robotic motion.

Bajracharya, Max↗

Tracker Toolkit

This software can track multiple moving objects within a video stream simultaneously, use visual features to aid in the tracking, and initiate tracks based on object detection in a subregion. A simple programmatic interface allows plugging into larger image chain modeling suites. It extracts unique visual features for aid in tracking and later analysis, and includes sub-functionality for extracting visual features about an object identified within an image frame. Tracker Toolkit utilizes a feature extraction algorithm to tag each object with metadata features about its size, shape, color, and movement. Its functionality is independent of the scale of objects within a scene. The only assumption made on the tracked objects is that they move. There are no constraints on size within the scene, shape, or type of movement. The Tracker Toolkit is also capable of following an arbitrary number of objects in the same scene, identifying and propagating the track of each object from frame to frame. Target objects may be specified for tracking beforehand, or may be dynamically discovered within a tripwire region. Initialization of the Tracker Toolkit algorithm includes two steps: Initializing the data structures for tracked target objects, including targets preselected for tracking; and initializing the tripwire region. If no tripwire region is desired, this step is skipped. The tripwire region is an area within the frames that is always checked for new objects, and all new objects discovered within the region will be tracked until lost (by leaving the frame, stopping, or blending in to the background).

Lewis, Steven J.↗