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At least 379 records · Page 21

Software Tool for Tracking & Mapping the NASA Orion AA-2 Test Flight Ejectable Data Recorders in Real Time

On 2 July 2019, the NASA Ascent Abort 2 flight took place off the Florida coast to test the emergency systems to separate the Orion Crew Module (CM) from the future Space Launch System rocket in the event of a malfunction. During this high-altitude test, instrumentation data was recorded on twelve customized buoyant Ejectable Data Recorders (EDRs) and subsequently jettisoned from the CM in mid-air. Upon release, the EDRs activated their GPS-Iridium beacon systems and began transmitting Short Burst Data (SBD) messages via the Iridium satellite network to relay their individual location and system health information. To locate, track and retrieve each EDR from the ocean surface in real-time, multiple open-source programming tools (Python and Linux shells) were developed for parsing the incoming Iridium binary SBD messages. For this, a Linux laptop was used to receive the Iridium-generated emails containing the SBD messages and autonomously execute the parsing tools. The received SBD data contained location, timestamp and health status information that was translated, saved, and subsequently used for simultaneously generating a continuously updated color-coded tabular display summary and unique KML files used with Google Earth to track their locations. Once their locations were known, dedicated recovery vessels retrieved all EDRs from the ocean. An additional tool was also developed in order to generate 5- and 10-minute geolocation predictions for each EDR by deriving the displacement distance, elapsed time, displacement heading and velocity based on the latest known information available. The recovery vessels were also tracked with the use of a separate commercial GPS beacon system. After jettison, 67% of the EDRs transmitted valid data by the time they were retrieved from the ocean. However, the real-time information presented by the plotting tool allowed for the ready depiction of EDR dispersal patterns and reference drift trajectories, which contributed to the recovery of all twelve EDRs and the AA-2 flight data. Lastly, the available data showed that the distance between the software’s reported drift/predicted locations and the recovery locations did not exceed 38 meters, therefore demonstrating the advantages of this software tool for supporting real-time tracking and recovery efforts of beacon devices.

Moxey, Lucas↗

Linear Mixed-Effects Models for Human-in-the-Loop Tracking Experiment Data

Linear mixed-effects models provide several benefits over more traditional statistical inference tests that are particularly useful for most human-in-the-loop tracking experiment data. However, surprisingly, mixed models are virtually not used for the analysis of tracking experiment data. This paper uses of linear mixed-effects models to analyze combined tracking data from two previous human-in-the-loop roll tracking experiments that compared control behavior metrics collected in both a research aircraft and a motion-base simulator. In the experiments, pilots' behavior under 10 different motion configurations with varying motion filter gains and break frequencies was evaluated and compared to that in the real aircraft. The linear mixed-effects model analysis on the combined dataset confirmed the main statistical outcomes of the individual experiments. The main benefits of mixed models for this type of data were demonstrated by successfully combining data from two experiments that used different experimental conditions and of which one had an additional apparatus and the other a missing participant. Finally, the mixed-model analysis was able to explicitly test for scientifically relevant statistical differences in the dependent measures between the aircraft and simulator, as well as both experiments.

manual control↗

Beam-Waveguide Antenna Servo Design Issues for Tracking Low-Earth-Orbiting Satellites

The upcoming NASA missions will require tracking of low-orbit satellites. As a consequence, NASA antennas will be required to track satellites at higher rates than for the current deep space missions. This paper investigates servo design issues for the 34-m beam-waveguide (BWG) antennas that track low-orbit satellites. This includes the upgrade of the servo with the feedforward loop, monopulse controller design, and tracking error reduction through proper choice of elevation pinion location, through application of a notch filter, and through the elevation drive amplifier gain adjustment. Finally, improvement of the signal-to-noise ratio through averaging of the oversampled monopulse signal is presented.

Mellstrom, J. A.↗

Next-generation wildlife tracking devices and integrated sensors for measuring species-environment interactions and advancing conservation

Global land use and climate change have magnified the importance of collecting accurate animal movement and environmental data to improve our ability to model species interactions with the environment and promote effective conservation. Advanced animal tracking devices that couple cutting-edge technologies with our expanding need for ecological information is critical. In addition to further optimizing device size to monitor small, sensitive species, new paradigms for collecting, storing, and transmitting data about animals and their environments will propel wildlife tracking devices forward. Advanced telemetry capabilities will increase our ability to pair location and sensor data from tagged wildlife with remote sensing data. The USGS Western Ecological Research Center, NASA Ames Research Center, and collaborators have been developing new wildlife tracking devices and integrated environmental sensors to address these challenges. We describe a new, miniaturized solar GPS-enabled Globalstar satellite transmitter with accelerometer capability that is 20% lighter and 25% less expensive than existing commercially available tags. We also introduce a novel peer-to-peer, solar-powered network tag that uses long-range, low-power, wireless platform technology. Concurrently, we began adapting a carbon nanotube (CNT) sensor to detect dimethyl sulfide (DMS), a trace gas relevant to marine ecology and climate studies. CNT sensors offer a small, lightweight, and low-power technology that can detect changes in resistance across carbon nanotubes coated with adsorbent selected to specifically bind with a variety of reactive trace gasses. We flew a prototype sensor in a small UAS and sampled an apparent increase in DMS concentration consistent with a well-defined marine frontal boundary. Currently we are integrating project components to create a hybridized architecture of networked peer-to-peer and satellite tags with integrated CNT and additional on-board and remote sensors to advance animal tracking and to provide information for next generation wildlife conservation.

Ian G. Brosnan↗

On-Orbit Results of Pointing, Acquisition, and Tracking for the TBIRD Cubesat Mission

Since launch in May 2022, the TeraByte Infrared Delivery (TBIRD) payload on a 6U CubeSat has successfully demonstrated 100/200 Gbps laser communications and has transferred >1 TB in a pass from low Earth orbit to ground. To support the narrow downlink beam needed for high rate communications, the payload provides pointing feedback to the host spacecraft to precisely track the ground station throughout the 5-minute pass. This paper presents the on-orbit results of the pointing and tracking system for TBIRD, including initial acquisition and closed-loop tracking performance of 20–35 µrad RMS per axis. Results from on-orbit characterization of the transmit beam are also presented. Measurements of Tx/Rx alignment show stability within 20 µrad, ensuring that tracking on the uplink accurately points the downlink.

TBIRD↗

Maneuver Reconstruction, Tracking Scheduling, and Bias Estimation in the Near Rectilinear Halo Orbit (NRHO)

NASA’s Gateway program will build a crew-tended station in an Earth-Moon Near Rectilinear Halo Orbit (NRHO) to support deep space missions to the lunar surface and heliocentric space. The station in the NRHO will be tracked by the Deep Space Network (DSN) with 2-way radiometric tracking data to produce an estimated state that is utilized to target Orbit Maintenance Maneuvers (OMMs). However, the tracking data is corrupted with measurement noise and range bias, which results in state estimation error and OMM execution error. This paper reports on analysis performed to improve the geometry of the tracking data problem with the inclusion of cross-hemispheric partner sites and explores the performance impact of handovers between partner sites and DSN sites. The OMM execution error is estimated directly using a Batch Least Squares (BLS) process, and the range bias estimation is analyzed among both original DSN sites and a combined DSN + partner sites scenario.

Clark P Newman↗

Developing A Space-Based Solution to Increase Accessibility, Quality, and Utility of Animal Tracking Data for Research and Management: the Internet of Animals Project

Animal tracking technology has advanced dramatically over the last several decades, but researchers and wildlife managers still encounter technological roadblocks in the study of animal movement and acquisition of animal movement data. For example, we still lack technology that provides automated high-resolution data for small animals that travel long distances, which limits our ability to answer both theoretical and applied questions about these species. In response to these needs, NASA has initiated a five-year study of potential space-based solutions that could provide global low-latency tracking of small migratory animals. This study, named Internet of Animals (IOA), aims to 1) systematically assess the needs of animal movement researchers and ecological managers, 2) design a next-generation space-based animal tracking system, i.e. an ‘Internet of Animals’ or IoA, to meet those needs, and 3) developing science and technology needed to link animal tracking data to the many other dimensions of biodiversity that can now be mapped from space using remote sensing. Here, we present results from the first IOA workshop, which highlighted the diverse needs of researchers and managers working across systems and realms. We also provide opportunities for the community to engage in the future.

remote sensing↗

EVA SPACESUIT INCIDENCE TRACKING

INTRODUCTION: Extravehicular Activity (EVA)suit-related injuries to crew during training and inflight operations are not uncommon. Systematic tracking of these issues has waxed and waned throughout NASA’s history. Given two new EVA suits in development and an increase in EVA training, the need for dutiful recording of this data is critical. The Suited User Incident Tracking System (SUITS) was developed in the last decade to track all suited exposures, recording exposure details and any related issues, pains, or injuries that arise. METHODS: SUITS data collected from 2017 to 2022 was analyzed for issue frequency and severity for each body location and plotted to visualize where issues were occurring. Clustering techniques using a k-modes approach were also applied to the data set to generate profiles of populations that experienced issues in the suit, and populations that did not. RESULTS:A key finding from SUITS is that discomfort and pain observed in the new planetary spacesuits are occurring in new body locations than those experienced in the microgravity space suit (Extravehicular Mobility Unit (EMU)).To date, the lower body and torso regions account for most pain reports in planetary spacesuits whereas most reports in EMU were shoulders and hands. DISCUSSION:SUITS will continue to be used to capture exposures for all suit types. As training suit availability improves and training cadence increases in preparation for planetary missions, it is critical to capture and assess all suit incidences. Further, a Suited Anomaly Assessment Team (SAAT) consisting of a broad range of EVA stakeholders was formed to share and act on SUITS data with the goal of developing robust solutions to issues/injuries as they arise. Understanding the types and locations of injuries that occur during suited operations will help inform future work related to EVA fitness training requirements, suit design, and modeling efforts to avoid injury. LEARNING OBJECTIVES: 1. Systematic tracking of suited exposures and issues is critical for understanding the complex interaction between the human and the EVA spacesuit. 2. As EVA suit issues/injuries arise it is important to share that data with a broad group to ensure robust strategies are developed.

N Newby↗

Tracking and Recovery of the Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) Reentry Vehicle (RV)

The LOFTID mission launched from Vandenberg on Nov 10, 2022, and successfully demonstrated the reentry of a 6m diameter inflatable aeroshell from low Earth orbit. This paper will cover the design features implemented to enable recovery of the flight vehicle, and will discuss the splashdown calculations, in-flight tracking, recovery from the ocean, and post-flight inspection of the flight vehicle. To support recovery of the RV and ejected data recorder after splashdown, a recovery ship was pre-positioned near the predicted splashdown ellipse in the Pacific Ocean. The splashdown ellipse was repeatedly updated as launch approached. In-flight tracking included transmission from the RV of GPS data through both the Iridium satellite network and the LoRa direct RF link, along with IR video cameras on the recovery ship and airborne imagery from the SCIFLI Team. Using both the GPS data and the IR imagery, the recovery ship tracked down the RV, and deployed an inflatable boat to approach the RV and attach it to the ship’s crane, after which the RV was hoisted on board and secured in its GSE recovery stand. The ship then tracked down the ejected data recorder, which was also broadcasting its GPS data, and pulled it from the water. Once the ship returned to port, the RV was hoisted ashore for additional inspection, removal of the data recorders, and repackaging for shipment back to NASA Langley.

Robert A. Dillman↗

Tracking and Recovery of the LOFTID RV (Low-Earth Orbit Flight Test of an Inflatable Decelerator Reentry Vehicle)

The LOFTID mission launched from Vandenberg on Nov 10, 2022, and successfully demonstrated the reentry of a 6m diameter inflatable aeroshell from low Earth orbit. This paper will cover the design features implemented to enable recovery of the flight vehicle, and will discuss the splashdown calculations, in-flight tracking, recovery from the ocean, and post-flight inspection of the flight vehicle. To support recovery of the RV and ejected data recorder after splashdown, a recovery ship was pre-positioned near the predicted splashdown ellipse in the Pacific Ocean. The splashdown ellipse was repeatedly updated as launch approached. In-flight tracking included transmission from the RV of GPS data through both the Iridium satellite network and the LoRa direct RF link, along with IR video cameras on the recovery ship and airborne imagery from the SCIFLI Team. Using both the GPS data and the IR imagery, the recovery ship tracked down the RV, and deployed an inflatable boat to approach the RV and attach it to the ship’s crane, after which the RV was hoisted on board and secured in its GSE recovery stand. The ship then tracked down the ejected data recorder, which was also broadcasting its GPS data, and pulled it from the water. Once the ship returned to port, the RV was hoisted ashore for additional inspection, removal of the data recorders, and repackaging for shipment back to NASA Langley.

Robert A Dillman↗

Development and Application of Weld Track Thermal Analysis for the Exploration Extravehicular Mobility Unit

NASA is studying the next generation of space suit for safe operations in space, from the International Space Station to the lunar surface as part of the Exploration Extravehicular Mobility Unit project. The backplate structure of the portable life support system (PLSS) serves as the attachment point for assembly of the PLSS and contains embedded cooling channels. The thermal loop plumbing assembly and backplate are combined into a single component such that the fluid lines run through the midplane of the backplate. The manufacturing of the Ti-6Al-4V backplate consists of machining channels into a plate, welding cover plates on each channel using an electron beam, and additional machining for excess material removal and final detail. Careful control of the electron beam weld process is necessary to completely seal cover plates, produce consistent weld tracks, and produce channels with uniform cross sections free of debris and defects. The backplate contains multiple weld channels with unique geometries. The weld process parameters include choosing the beam current and focus, accelerating voltage, travel speed, pause times between weld tracks, and sequence of weld tracks. A transient finite element thermal analysis was developed to provide support for choosing and controlling the weld process parameters to maintain a consistent melt pool along each of the weld tracks. A moving distributed heat source is modeled to represent the heat input generated by the electron beam. The heat source model is a critical input to the analysis for accurate temperature predictions during the weld process. A modified conical heat source was developed to account for the change in working distance between the backplate and cover plates. The geometry of the material being welded must be accounted for by the heat source model to define the correct energy input. The weld process control is designed according to the predicted thermal history and melt pool dimensions for each of the weld channels. The analysis model, modified heat source, temperature and melt pool predictions, application of the thermal data to the weld parameters, and comparison with micrograph cross-sections from weld trials will be discussed in this presentation.

Electron Beam Welding↗

Safe Tracking Control of an Uncertain Euler-Lagrange System with Full-State Constraints using Barrier Functions

This paper presents a novel, safe tracking control design method that learns the parameters of an uncertain Euler-Lagrange (EL) system online using adaptive learning laws. A barrier function (BF) is first used to transform the full-state constrained EL-dynamics into an equivalent unconstrained dynamics. An adaptive tracking controller is then developed along with the parameter update law in the transformed state space such that the states remain bounded for all time within a prescribed bound. A stability analysis is developed that considers the EL-dynamics’ uncertainty, yielding a semi-globally uniformly ultimately bounded (SGUUB) tracking error and the parameter estimation error. The controller design is validated in simulations using a two-link planar manipulator. The results show the proposed method’s ability to track the reference trajectory while remaining inside each of the predefined state bounds.

Robots↗

Tracking the Hunga Tonga-Hunga Ha’apai Eruption Stratospheric Aerosol and Trace Gas Plumes Using Machine Learning

The Hunga Tonga-Hunga Ha’apai (HTHH) submarine volcano had an explosive eruption phase on January 15, 2022, that thrusted ash, gases, and water vapor through the troposphere and into the stratosphere. The stratospheric volcanic plume included aerosol precursor gases such as SO2 and H2S as well as anomalously high water vapor concentrations due to the submarine oceanic origin. With these atmospheric constituents, the sulfuric gases and water vapor formed sulfate (SO4) particles via gas-to-particle reactions and these aerosols likely increased in size due to hygroscopic growth within anomalously humid regions. Strong easterlies and gravity waves propagated the volcanic impacts throughout the stratosphere. Orbital and suborbital passive sensor retrievals detected changes in the aerosol and trace gas characteristics within the atmospheric column for cloud-free regions over the southern hemisphere. While the CALIPSO lidar can detect aerosol layers in the stratosphere, passive sensors such as MODIS retrieved the total column aerosol abundance and characteristics. Previous studies used manual tracking methods to determine volcanic plume positions and compared them to ground observations. In this study, we examine the machine learning (ML) approaches including segmentation, object detection, and object tracking to identify and track aerosol and trace gas plumes using orbital and suborbital sensor data. This ML implementation strives to provide a more systematic approach to separate total column effects from those of the stratosphere. Similar ML tracking may be useful for stratospheric impact events observed historically by CALIPSO and in the future with EarthCare and the Atmosphere Observing System (AOS) lidar-capable missions.

Rhys Leahy↗

Analysis of the ''Range and Range Rate'' Tracking System

The "Range and Range Rate" (r(sub j) + r ̇(sub j)) System in its very simplest form is described. In particular, the errors in position and velocity are treated usingpessimistic values of the measured quantities r(sub j) and r ̇(sub j). Thus, a realistic evaluation of tracking qualities can be made for different orbits over certain tracking stations. The Range and Range Rate System briefly described in this report is a high precision tracking system. Knowledge of the uncertainty in position δ (sub x(sub i) is important, but knowledge of the uncertainty of the velocity vector δ (sub x(sub i) is of the utmost importance. Thus the use of coherent Doppler measurements to determine the velocity has a great advantage over any pulsed system and, in addition, permits extremely narrow frequency bands (in the order of 10 to 100 cps) to be employed, reducing the power requirements considerably. The basis for using range r(sub j) and range rate r ̇(sub j) only is the fact that r(sub j) and r ̇(sub j) can be measured to very high precision, thus furnishing r and r with low errors. The nature of these errors is discussed.

Tracking system↗

360-Degree Visual Detection and Target Tracking on an Autonomous Surface Vehicle

This paper describes perception and planning systems of an autonomous sea surface vehicle (ASV) whose goal is to detect and track other vessels at medium to long ranges and execute responses to determine whether the vessel is adversarial. The Jet Propulsion Laboratory (JPL) has developed a tightly integrated system called CARACaS (Control Architecture for Robotic Agent Command and Sensing) that blends the sensing, planning, and behavior autonomy necessary for such missions. Two patrol scenarios are addressed here: one in which the ASV patrols a large harbor region and checks for vessels near a fixed asset on each pass and one in which the ASV circles a fixed asset and intercepts approaching vessels. This paper focuses on the ASV's central perception and situation awareness system, dubbed Surface Autonomous Visual Analysis and Tracking (SAVAnT), which receives images from an omnidirectional camera head, identifies objects of interest in these images, and probabilistically tracks the objects' presence over time, even as they may exist outside of the vehicle's sensor range. The integrated CARACaS/SAVAnT system has been implemented on U.S. Navy experimental ASVs and tested in on-water field demonstrations.

ASV (AUTONOMOUS SEA SURFACE VEHICLE)↗

Spectral Study of Water Tracks as an Analog for Recurring Slope Lineae

Liquid water is a key requirement for life on Earth, and serves as an important constraint on present day habitability on Mars. Recurring Slope Lineae (RSL) are a unique phenomenon on Mars that may be formed by brine seeps. Their morphological, seasonal and temporal characteristics support this hypothesis; however, spectral evidence has been lacking. Ojha et al., 2013 recently analyzed CRISM images from all confirmed RSL in the southern mid-latitudes and equatorial regions and found no spectro-scopic evidence for water. Instead, enhanced abun-dances or distinct grain sizes of both ferric and ferrous minerals are observed at most sites. The strength of these spectral signatures changes as a function of sea-son, possibly indicating removal of a fine-grained sur-face component during RSL flow, precipitation of fer-ric oxides, and/or wetting of the substrate. Water tracks (WT) have been suggested as a terrestrial analog for RSL by Levy et al., 2011. WT are defined as dark surface features that extend downslope in a linear or branching fashion, usually oriented along the steepest local gradient, in the Dry Valleys of Antarctica. They can be 1-3 m in width and can have lengths up to 2 km. They share many morphological and seasonal characteristics with RSL including active growth during summer seasons and fading during winter. Snowmelt, ground ice melt and deliquescence by hygroscopic salts have been suggested as possible formation mechanisms for water tracks. No spectral work to date has been reported for water tracks.

volumet-ric water content (VWC)↗

Generation of Simulated Tracking Data for LADEE Operational Readiness Testing

Operational Readiness Tests were an important part of the pre-launch preparation for the LADEE mission. The generation of simulated tracking data to stress the Flight Dynamics System and the Flight Dynamics Team was important for satisfying the testing goal of demonstrating that the software and the team were ready to fly the operational mission. The simulated tracking was generated in a manner to incorporate the effects of errors in the baseline dynamical model, errors in maneuver execution and phenomenology associated with various tracking system based components. The ability of the mission team to overcome these challenges in a realistic flight dynamics scenario indicated that the team and flight dynamics system were ready to fly the LADEE mission. Lunar Atmosphere and Dust Environment.

Tracking↗

Automated Storm Tracking and the Lightning Jump Algorithm Using GOES-R Geostationary Lightning Mapper (GLM) Proxy Data

This study develops a fully automated lightning jump system encompassing objective storm tracking, Geostationary Lightning Mapper proxy data, and the lightning jump algorithm (LJA), which are important elements in the transition of the LJA concept from a research to an operational based algorithm. Storm cluster tracking is based on a product created from the combination of a radar parameter (vertically integrated liquid, VIL), and lightning information (flash rate density). Evaluations showed that the spatial scale of tracked features or storm clusters had a large impact on the lightning jump system performance, where increasing spatial scale size resulted in decreased dynamic range of the system's performance. This framework will also serve as a means to refine the LJA itself to enhance its operational applicability. Parameters within the system are isolated and the system's performance is evaluated with adjustments to parameter sensitivity. The system's performance is evaluated using the probability of detection (POD) and false alarm ratio (FAR) statistics. Of the algorithm parameters tested, sigma-level (metric of lightning jump strength) and flash rate threshold influenced the system's performance the most. Finally, verification methodologies are investigated. It is discovered that minor changes in verification methodology can dramatically impact the evaluation of the lightning jump system.

lightning jump↗