cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.48577/jpl.wmv95z
title: Hybrid Autonomous Global Localization in the Absence of PNT Infrastructure

description: No abstract available.
DOI: 10.48577/jpl.ftwtsi
title: Flight of Dynamic Targeting on CogniSAT-6

description: No abstract available.
DOI: 10.48577/jpl.m3szoc
title: Results from Independent Calibration and Validation of the Sentinel-6 Michael Freilich Mission

description: No abstract available.
DOI: 10.48577/jpl.rmgdcg
title: Geospatial Techniques, Data, and Open Source Software for Mission Operations

description: Geospatial techniques and software (aka ‘mapping’) provide a shared mission spatial context for science and engineering decision making. The “where” is necessary knowledge for science planning, both in terms of the vehicle location in time, the instrument pointing, and capturing new science data. Mapping shines when integrated early during mission formulation and then again in the surface mission development cycle. In a mapping context, collaboration is critical for large, globally distributed science and engineering teams, to enhance mission planning, analysis, and data fusion, to increase situational awareness to save time and effort, as well as maximize science return. At NASA/JPL, we assemble formal mapping teams, Mapping Specialists, who provide new maps and mapping data daily based on spacecraft position, targeted science, and strategic planning. We’ve built an open source, web-based, geospatial application for direct use during operations. The Multi-Mission Geographic Information System (MMGIS), created though the NASA Advanced Multi-Mission Operations System (AMMOS), was designed to support science operations for the Earth and other planets like Mars. MMGIS takes advantage of open data format standards and Free and Open Source Geospatial (FOSS4G) spatial/mapping libraries.
DOI: 10.6084/m9.figshare.29206817
title: Job satisfaction conciliated impact of operating environment health and safety measures on the performance of workers (an observational study on Maramer Construction Company)

description: This presentation explores the interconnected influence of job satisfaction, operating environment, and health and safety measures on employee performance within the construction industry. Using Maramer Construction Company as a case study, the research investigates how workplace conditions, employee well-being, and satisfaction levels impact overall productivity. Through observational methods, the study highlights key areas of concern and provides recommendations for improving worker performance through strategic enhancements in workplace management and safety protocols.
DOI: 10.6084/m9.figshare.29206817.v1
title: Job satisfaction conciliated impact of operating environment health and safety measures on the performance of workers (an observational study on Maramer Construction Company)

description: This presentation explores the interconnected influence of job satisfaction, operating environment, and health and safety measures on employee performance within the construction industry. Using Maramer Construction Company as a case study, the research investigates how workplace conditions, employee well-being, and satisfaction levels impact overall productivity. Through observational methods, the study highlights key areas of concern and provides recommendations for improving worker performance through strategic enhancements in workplace management and safety protocols.
DOI: 10.48577/jpl.ggnpuc
title: Interrogating Redox-Active Prebiotic Metal-Organic Complexes and Mineral Adsorbates via EPR Spectroscopy

description: No abstract available.
DOI: 10.15468/dl.ny364s
title: Occurrence Download

description: A dataset containing 1086 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Schizachyrium scoparium (Michx.) Nash",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 1086 records from 118 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013588-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48577/jpl.3ih5ei
title: Molecular shock modeling for YSOs

description: No abstract available.
DOI: 10.48577/jpl.ntef0g
title: Decades of Clocks in Deep Space and Outside the Solar System

description: No abstract available.
DOI: 10.15468/dl.ujf799
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptoderma macrops Vaillant, 1886",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((54.0145 -15.8532,54.1138 -16.1504,54.9312 -16.1504,55.0218 -15.961,54.8989 -15.5532,54.5521 -15.3811,54.2381 -15.4633,54.0145 -15.8532))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013589-250525065834625/datasets/export for details.
DOI: 10.48577/jpl.6r7yjl
title: OCO-2/3 Calibration Report

description: No abstract available.
DOI: 10.48577/jpl.99tcae
title: AOGS Presentation

description: No abstract available.
DOI: 10.48577/jpl.szytx9
title: Quantum Applications in Silicon Carbide and other wide band-gap semiconductors

description: No abstract available.
DOI: 10.48577/jpl.jbu83w
title: Scheduling NASA's Deep Space Network in the Artemis Era

description: Scheduling NASA’s Deep Space Network (DSN) is inherently challenging under nominal circumstances. However, the additional stress of supporting the Artemis 1 mission, along with the expectations for future flights in the Artemis series, introduces another level of complexity and demand. The Artemis 1 mission was accompanied by a number of smallsats, which further complicated the task of providing communications and navigation support to all the launching missions. Even if future missions do not include DSN-supported smallsats, the primary Artemis scheduling support remains complicated by uncertainties in the launch date and the exact launch time within a specified window — a window during which the support geometry can change significantly. This complexity is further compounded by post-launch trajectory updates, and by the need to balance any impacts on other DSN users, including those who could potentially be seriously impacted by last-minute schedule changes. This paper outlines the nominal DSN scheduling process and tools, and then details how the Artemis 1 mission requirements (and the accompanying smallsats) impacted that nominal process. Lessons learned from this experience have been collected and converted into a set of potential future improvements designed to both lessen the impact and streamline future support timelines. In this paper we will describe the rationale behind the proposed improvements, how they will better support Artemis missions, and the architecture and design considerations, specific to the DSN, that come into play.
DOI: 10.48577/jpl.dknbnh
title: Open Source Community-Built Software Standards for Space and Ground SoftwareAn Overview of the SLIM Project from NASA JPL

description: No abstract available.
DOI: 10.48577/jpl.tcwynf
title: Rapid Trajectory Design for Spacecraft within Ice Giant Systems

description: No abstract available.
DOI: 10.48577/jpl.hfwdco
title: A Transformer-Based Deep Learning Approach to Anomaly Detection of High-Bandwidth Multivariate Time-Series Satellite Communications

description: Monitoring incoming spacecraft data to detect anomalies is essential for the continuation of a successful mission. Spacecraft Operations Engineers have traditionally relied on manual monitoring of satellite data, with limited statistical support for anomaly detection, focusing primarily on threshold-based monitoring of individual data items to identify and resolve any anomalous behavior; however, as the number of satellites launched increases exponentially every year with growing bandwidth per new satellite, the amount of data Operations Engineers need to monitor is increasing at an alarming rate. There is a pressing concern of monitoring all the incoming data without increasing operating costs. In this paper, we demonstrate that modern deep-learning anomaly detection methods can aid existing Spacecraft Operations Engineers. Previous research has explored the use of machine learning to monitor incoming data and alert Operations Engineers about potential anomalies. We build upon the literature by taking a multivariate time-series dataset (DSN spacecraft monitor data) and feeding it into a transformer-based deep learning algorithm. Whereas previous work uses complete data with a single data type, this dataset proves challenging due to various data types per time-step and missing data. We refine the data preprocessing and architecture of the TranAD algorithm to improve its performance on both the DSN dataset and existing public anomaly detection datasets. We demonstrate that the modified TranAD algorithm improves performance over MTAD-GAT, OmniAnomaly, and USAD on the DSN dataset. We also tested some public datasets, including SMAP, MSL, SWaT, SMD, and WADI, and demonstrated improved performance on SMAP, SWaT, and SMD. The improved performance promises the ability for Spacecraft Operations Engineers to instantaneously detect anomalies in the high-bandwidth regime of modern satellite communications.
DOI: 10.48577/jpl.dprjw6
title: Geodesy and Space situational awareness: How geodetic ground infrastructure enables navigation

description: Geodesy, the science of measuring and understanding the Earth's shape, orientation, and gravitational field, plays a crucial role in the field of spacecraft navigation and space situational awareness. As the number of spacecraft constellations increase, the integration of geodetic techniques with navigation systems has become essential to ensure precise trajectory planning, positioning, and orbit determination. This presentation explores the fundamental links between geodesy and space navigation and space situational awareness, examining how geodetic infrastructure is key to positioning in space and on earth. Key areas of focus include the use of geodetic reference frames, global navigation systems (like GPS) and Earth orientation parameters. Two examples using Very long base Interferometry and Satellite Laser ranging will be presented to explain the contribution of global geodetic observatory systems to the parameters required for navigation and their role in determining accurate satellite orbits and in tracking variations in the Earth’s center of mass. We will discuss how these techniques contribute to the definition of the reference frames required for navigation and to the increasing demands on accuracy for positioning. Additionally, we will explain how these techniques offer unique data required for navigation and their strengths. By unveiling the not-so evident link between terrestrial geodetic infrastructure and satellite operations, we aim to highlight why this infrastructure is essential for space navigation, collision avoidance and to improve our ability to provide more accurate positioning standards. The presentation concludes by explaining why Global Navigation Satellite Systems like GPS aren’t sufficient to define these parameters and the challenges posed by an increasing number of satellites in space, signal interference and aging ground infrastructure.
DOI: 10.48577/jpl.couxgw
title: CloudSat Lights Out - End of Life Operations

description: Abstract The CloudSat Mission proposal was selected by National Aeronautics and Space Administration (NASA) in 1999 from an Announcement of Opportunity for the Earth Science System Pathfinder program. CloudSat was proposed to fly as part of a joint mission between NASA and the Centre National D'Etudes Spatiales (CNES), where CNES provided the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. They were designed to be launched together and flown in on-orbit formation to provide near-coincident observations. Cloudsat carried a single science instrument payload, the Cloud Profiling Radar (CPR), capable of observing the vertical distribution of all but the thinnest clouds, while CALIPSO carried a Lidar instrument used to study thinner clouds and aerosols. The satellites were co-manifested and launched on April 28, 2006 from Vandenburg Air Force Base in California. Following launch, both spacecraft were maneuvered into the NASA’s Afternoon Constellation of satellites (A-Train), where they operated for many years. Originally designed for a 22-month mission, CloudSat far exceeded expectations and ultimately operated for nearly eighteen years. CloudSat had a complicated on-orbit operational history due to spacecraft anomalies that frequently challenged the operations team. The inflight anomalies necessitated changes to spacecraft operations, changes to formation flying with CALIPSO and finally changes to the orbits of both satellites. Through it all, CloudSat continued formation flying operations with CALIPSO until both satellites reached end of life. When CALIPSO’s mission ended in mid-2023, the combined radar-lidar measurements could no longer be achieved and plans for CloudSat End of Mission (EOM) activities began. There was a strong desire to perform an engineering test on the redundant CPR subsystems, as the instrument had operated exclusively on the primary hardware side since launch. EOM plans were carefully laid out to include a 3-month CPR engineering test on the redundant hardware and a 2-month orbit lowering campaign. The success-oriented plan had sufficient margin to ensure successful execution within the required schedule. EOM activities were challenged by operating an aging spacecraft and altered concepts of operations to deal with limitations imposed by previous inflight anomalies. True to the history of the CloudSat mission, the plan encountered an additional obstacle that interrupted the orbit lowering and satellite disposal campaign. This paper will provide a brief overview of the mission, but discussion will focus on the decision to terminate the CloudSat mission, planning for and execution of the CPR engineering test, the orbit lowering maneuver campaign and finally spacecraft passivation.
DOI: 10.48577/jpl.axpovh
title: AGU: Intrinsic Dimensionality and Spectral Diversity

description: No abstract available.
DOI: 10.48577/jpl.bvbzit
title: A First-in-Flight Demonstration of the Deep Space Network's Multiple Uplinks Per Antenna Capability

description: No abstract available.
DOI: 10.48577/jpl.xufmdq
title: Hybrid Autonomous Global Localization in the Absence of PNT Infrastructure

description: Typical global positioning methods require a network of multiple satellites for localization. When such a GPS-like infrastructure is unavailable or when its direct line-of-sight communications with Earth are not warranted, a user on the far side of the moon or near the polar regions would need to rely on other autonomous navigation techniques such as celestial positions, local radiometric infrastructure network, altimetry, and terrain-relative measurements, etc. to determine its in-situ position and orientation. This paper proposes a hybrid scheme combining IMU sensors, star trackers (ST), and surrounding terrain outline (STO) for real-time autonomous localization. The lack of oceans and plateaus and the excess of craters and ridges on the moon help make an STO a signature unique to its location. Due to the absence of vegetation, seasons, weather, and artificial human-made structures on the moon, STOs remain unchanged over time. In addition, since all rovers are equipped with onboard panoramic cameras, STOs can be obtained readily and reasonably inexpensive. Some cameras have infrared capabilities, enabling the rover to self-localize in complete darkness or low-lighting conditions. Due to the contrast between the cold sky background, the moon's diffusing hot body temperature, and the unavailability of the atmosphere, an STO can be obtained very crisply and distinguishably. Once collected, the STO can be matched with a database of constructed STOs for a specific region to determine the position and orientation of the user. The STO database is built in advance using NASA's high-resolution digital elevation map (DEM), acquired by the Lunar Orbiter Laser Altimeter (LOLA) instrument on the Lunar Reconnaissance Orbiter (LRO). Our previous investigations show that, with appropriate instrument calibration and performance, the average self-localization errors can be a few meters to tens of meters, and the average orientation errors are within half a degree. For high accuracy results, the terrain outline matching method requires high-resolution DEM, and thus intensive computational effort and large memory storage. On the other hand, recent advanced star trackers can provide the user's attitude and position within a few seconds, even in lost-in-space mode. However, their three-sigma position errors could be as high as tens of meters. Our proposed scheme first employs the ST technique to attain a quick approximate position and then applies the STO method on a high-resolution DEM but small area enclosing the approximate position. This way, we can achieve accuracy and speed by combining the ST and the STO techniques. Our results show that even at the worst tilting and terrain uncertainties and half of the field of view being blocked, the 3σ positioning error for the STO is less than 5m. When 75% of the field of view is obstructed, the 3σ positioning errors never exceed 25m. Most importantly, the STO method works in areas with relatively flat local terrain.
DOI: 10.48577/jpl.lzp0jf
title: Automating the Request Process for the Deep Space Network

description: NASA’s Deep Space Network (DSN) is responsible for tracking and communications with over 50 missions using 14 large antennas across three global sites. The scheduling process for DSN is intricate, requiring extensive manual input and negotiation among multiple stakeholders. To improve efficiency and reduce delays, the DSN Intelligent Virtual Assistant (DIVA) has been developed to provide assistance to DSN schedulers in multiple ways. DIVA is designed to automate scheduling request generation, and change proposal monitoring and response handling. This paper describes the architecture, design, and benefits of DIVA, along with opportunities for future enhancements.
DOI: 10.48577/jpl.ozvebe
title: Automating the Request Process for the Deep Space Network

description: No abstract available.
DOI: 10.48577/jpl.ecjofu
title: Considerations in Building a DSN-Affiliated Ground Station in Economical and Sustainable Ways

description: The 21-m ground station at the Morehead State University became operational in 2021 as an affiliated node of the NASA Deep Space Network (DSN). The station was developed to support NASA-sponsored CubeSat missions such as CAPSTONE and the Artemis-1 Cubesats (e.g., Lunar IceCube). Since then, it has been used to support other lunar commercial missions such as Intuitive Machine’s IM-1 and IM-2 landers. Continued support for future missions both commercially and NASA-owed missions is expected. This paper will discuss some of the desirable characteristics of a DSN-affiliated station. Given that the affiliated station is likely owned and operated by a university as in the case of Morehead, funding is often limited. The approach taken during the development to realize an operational ground station within the available budget is discussed. More importantly the need to maintain such an operational system post-deployment is challenging. Different strategies employed by the Morehead State University team are discussed. They include expanding the station capabilities and offering services to other potential mission users to sustain operational funding.
DOI: 10.15468/dl.jthuv7
title: Occurrence Download

description: A dataset containing 158994 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Beta vulgaris L."
 ]
}

 The dataset includes 158994 records from 752 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013571-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48577/jpl.zp9cgo
title: Open Source Community-Built Software Standards for Space and Ground Software. An Overview of the Software Lifecycle Improvement Modernization (SLIM) Project from NASA’s Jet Propulsion Laboratory

description: The Software Lifecycle Improvement Modernization (SLIM) initiative at NASAs Jet Propulsion Laboratory (JPL), sponsored by the NASA’s Advanced Multi-Mission Operations System (AMMOS) effort, represents an advancement in the rapid infusion of software development best practices for space and ground software. It is a shared, open-source resource for discussing, iterating, and referencing best practices for software development. It draws on strategic insights from NASA JPL’s internal and external open-source initiatives, and it has been field- tested widely at JPL across hundreds of software project repositories. SLIM champions the development, iteration, and widespread dissemination of standardized software development best practices and is aimed at collectively maturing sub-topics such as project governance, software lifecycle automation, and software documentation through a participatory and open community model. SLIMs methodology harnesses a standards-as-code philosophy, where best practices are not only developed openly through community contributions and feedback but are patchable directly into project codebases or deployable via infrastructure enhancements, including using generative artificial intelligence techniques. This unique approach allows for the scalable dissemination of improvements makes a tangible impact on space-related software project performance and significantly reduces infusion barriers for software user, developer, and stakeholder communities. SLIM’s best practices, encompassing artifacts like templates, workflow automation, or software starter kits are open-source licensed and free to use and iterate. We explore the SLIM initiative in detail, focusing on its three-phase process for infusing best practices: soliciting input and feedback from a community of projects, developing actionable standards encodable as patched improvements, and directly pushing these improvements into active project codebases through software pull requests and issue tickets. We also highlight the community-driven aspect of SLIM, discussing the network of contributors who are pivotal in curating and advancing the SLIM repository of best practices, as well as the results of our overall process.
DOI: 10.48577/jpl.jrnfba
title: ECCO Summer School 2025 (Fukumori Lectures)

description: No abstract available.
DOI: 10.48577/jpl.gxhtfo
title: OCO-3 B11 and Onwards

description: No abstract available.
DOI: 10.48577/jpl.eisz9t
title: ODYSEA: a satellite mission to advance knowledge of ocean dynamics and air-sea interaction

description: No abstract available.
DOI: 10.48577/jpl.bajgph
title: On the Size of the Mission Suite Enabled by NASA's Deep Space Network

description: No abstract available.
DOI: 10.48577/jpl.a98ssl
title: Multi-Asset New Observing Systems Flight Demonstration

description: No abstract available.
DOI: 10.48577/jpl.apxcvq
title: FLOAT -- Flexible Levitation on a Track (NIAC Phase I, Final Report)

description: No abstract available.
DOI: 10.48577/jpl.riahwv
title: Welcome to the 2025 Quantum Engineering Workshop

description: No abstract available.