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All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Robust Vision-based Multi-spacecraft Guidance Navigation and Control using CNN-based Pose Estimation

In this paper, we present an end-to-end simulation framework for tracking an uncooperative Target spacecraft in Low Earth Orbit using a CubeSat-class Ego spacecraft outfitted with a camera. Currently, capturing high-fidelity realistic images in space for this scenario is difficult and exorbitantly expensive. Therefore, we developed a framework to simulate the spacecraft orbits in Basilisk software and generate high-fidelity realistic images of spacecraft in Unreal Engine, including the effects from Sun, Earth, Moon and stars. The Ego spacecraft uses cameras to capture images of the uncooperative Target and estimates its position and attitude using a CNN based 6DOF pose estimation pipeline, eliminating need for large SWAP-C(Size, Weight, Power and Cost) sensors like LIDAR or reliance on inter-spacecraft communication, This CNN, which is motivated by ESA’s Pose Estimation challenge of 2019, is trained using simulated data from our end-to-end simulation framework. We compare the performance of two distinct CNNbased algorithms for pose estimation along a nominal trajectory. In presence of non-Gaussian modeling uncertainties, the statedependent estimation error is characterized with a quadratic upper-bound. The quadratically-bounded error can be used by a robust controller to maneuver

Rahmani, Amir↗
NASA NTRS1999

An Airborne Scanning Laser Altimetry Survey of Long Valley, California

Between 28 September and 7 October 1995, we conducted an airborne laser altimetry experiment over the Long Valley caldera, California, in which each of two scanning laser altimeters (dubbed SLICER and RASCAL) were flown in a NASA T-39 jet aircraft. Operating concurrently were a Global Positioning System (GPS) guidance system and dual frequency receivers for precise navigation and post-flight calculation or the airplane trajectory relative to a ground station, and an inertial navigation system (INS) for attitude determination. Reduction of raw laser ranges requires merging the differential kinematic GPS aircraft trajectory and the INS data with the laser data, and determination of the atmospheric delay. Data geolocation consists of obtaining the centre location and the mean elevation within each footprint in a geodetic coordinate system. The elevation of Crowley Lake is recovered to an accuracy of approximately 3 cm or better from 3 km above ground level and crossover analysis indicates that the elevation estimates are consistent from pass to pass. We test our geolocation procedures by comparing laser-derived elevations with those determined in situ for recognizable ground features. A comparison of laser and GPS-derived positions shows that the horizontal accuracy is better than the diameter of the footprint and vertical accuracy is within the error inherent in the range measurement. A comparison of SLICER elevation data with digital elevation models (DEMs) of the region shows that the DEM data provides surface topography to within stated accuracy limits. Although research continues to utilize the full potential of laser altimetry data, our results constitute a successful demonstration that the technique may be used to perform geodetic monitoring of surface topographic changes.

Hofton, M. A.↗
NASA NTRS2015

A High-Resolution Merged Wind Dataset for DYNAMO: Progress and Future Plans

In order to support research on optimal data assimilation methods for the Cyclone Global Navigation Satellite System (CYGNSS), launching in 2016, work has been ongoing to produce a high‐resolution merged wind dataset for the Dynamics of the Madden Julian Oscillation (DYNAMO) field campaign, which took place during late 2011/early 2012. The winds are produced by assimilating DYNAMO observations into the Weather Research and Forecasting (WRF) three‐dimensional variational (3DVAR) system. Data sources from the DYNAMO campaign include the upper‐air sounding network, radial velocities from the radar network, vector winds from the Advanced Scatterometer (ASCAT) and Oceansat‐2 Scatterometer (OSCAT) satellite instruments, the NOAA High Resolution Doppler Lidar (HRDL), and several others. In order the prep them for 3DVAR, significant additional quality control work is being done for the currently available TOGA and SMART‐R radar datasets, including automatically dealiasing radial velocities and correcting for intermittent TOGA antenna azimuth angle errors. The assimilated winds are being made available as model output fields from WRF on two separate grids with different horizontal resolutions ‐ a 3‐km grid focusing on the main DYNAMO quadrilateral (i.e., Gan Island, the R/V Revelle, the R/V Mirai, and Diego Garcia), and a 1‐km grid focusing on the Revelle. The wind dataset is focused on three separate approximately 2‐week periods during the Madden Julian Oscillation (MJO) onsets that occurred in October, November, and December 2011. Work is ongoing to convert the 10‐m surface winds from these model fields to simulated CYGNSS observations using the CYGNSS End‐To‐End Simulator (E2ES), and these simulated satellite observations are being compared to radar observations of DYNAMO precipitation systems to document the anticipated ability of CYGNSS to provide information on the relationships between surface winds and oceanic precipitation at the mesoscale level. This research will improve our understanding of the future utility of CYGNSS for documenting key MJO processes.

Lang, Timothy J.↗
NASA NTRS1998

Tutorial on the Psychophysics and Technology of Virtual Acoustic Displays

Virtual acoustics, also known as 3-D sound and auralization, is the simulation of the complex acoustic field experienced by a listener within an environment. Going beyond the simple intensity panning of normal stereo techniques, the goal is to process sounds so that they appear to come from particular locations in three-dimensional space. Although loudspeaker systems are being developed, most of the recent work focuses on using headphones for playback and is the outgrowth of earlier analog techniques. For example, in binaural recording, the sound of an orchestra playing classical music is recorded through small mics in the two "ear canals" of an anthropomorphic artificial or "dummy" head placed in the audience of a concert hall. When the recorded piece is played back over headphones, the listener passively experiences the illusion of hearing the violins on the left and the cellos on the right, along with all the associated echoes, resonances, and ambience of the original environment. Current techniques use digital signal processing to synthesize the acoustical properties that people use to localize a sound source in space. Thus, they provide the flexibility of a kind of digital dummy head, allowing a more active experience in which a listener can both design and move around or interact with a simulated acoustic environment in real time. Such simulations are being developed for a variety of application areas including architectural acoustics, advanced human-computer interfaces, telepresence and virtual reality, navigation aids for the visually-impaired, and as a test bed for psychoacoustical investigations of complex spatial cues. The tutorial will review the basic psychoacoustical cues that determine human sound localization and the techniques used to measure these cues as Head-Related Transfer Functions (HRTFs) for the purpose of synthesizing virtual acoustic environments. The only conclusive test of the adequacy of such simulations is an operational one in which the localization of real and synthesized stimuli are directly compared in psychophysical studies. To this end, the results of psychophysical experiments examining the perceptual validity of the synthesis technique will be reviewed and factors that can enhance perceptual accuracy and realism will be discussed. Of particular interest is the relationship between individual differences in HRTFs and in behavior, the role of reverberant cues in reducing the perceptual errors observed with virtual sound sources, and the importance of developing perceptually valid methods of simplifying the synthesis technique. Recent attempts to implement the synthesis technique in real time systems will also be discussed and an attempt made to interpret their quoted system specifications in terms of perceptual performance. Finally, some critical research and technology development issues for the future will be outlined.

Wenzel, Elizabeth M.↗
NASA NTRSDate not supplied

Improvements to GNSS Positioning in Challenging Environments by 3DMA Lidar Informed Selective Satellites Usage

The use of global navigation satellite systems (GNSS) for position estimation tends to yield poor results when operating inside of an urban canyon due to large obstructions (e.g., buildings) that disrupt signals as they travel from a satellite to a receiver resulting in a position estimate that may significantly fluctuate in magnitude and direction. Identifying and removing signals that are non-line-of-sight (NLOS) to the receiver and only using signals that are line-of-sight (LOS) can improve the estimated position. However, quickly and accurately determining the LOS status of each measurement can be challenging without additional information about the operating environment. Use of publicly available lidar data can be used to incorporate techniques, such as 3D-mapping-aided (3DMA), to estimate the LOS status of satellites and augment the position solution accordingly. To complicate the issue, the error on the GNSS position estimate in an urban canyon is often so large that is it not sufficient to use as an approximate location for LOS prediction. That is, at times the calculated GNSS solution is not representative of the true location and cannot be used to accurately predict which satellites are within LOS due to the difference in the physical geometry associated with the two locations. This paper explores the use of a GNSS/inertial fused position solution as the initial position estimate for predicting which satellites are within LOS in an urban environment and the impact that removal of predicted NLOS satellites has on the GNSS position solution.

GPS↗
NASA NTRSDate not supplied

Characterizing the Impact of Equatorial Plasma Bubbles on GNSS Accuracy for Crop Yield Estimation in Brazil with NASA GOLD Data

In Brazil, equatorial plasma bubbles are the primary space weather phenomenon impacting the performance of Global Navigation Satellite Systems (GNSS), causing signal disruptions and positional inaccuracies in agricultural machinery used for mapping fields, guiding machinery, and ensuring accurate planting, spraying, and harvesting. As a result, farmers and stakeholders face challenges in maintaining accurate operational capabilities, often needing to shut down machinery to mitigate these effects. This project evaluated the feasibility of using NASA’s Heliophysics observations for a case study in March 2024. Data from NASA's Global-scale Observations of the Limb and Disk (GOLD) instrument were used to characterize equatorial plasma bubbles, while amplitude and phase indices from ground-based GNSS receivers confirmed their presence and impact on signal disruptions. Additionally, data from a local farm's rover receiver assessed the practical implications of these disruptions on Real-Time Kinematic (RTK) GNSS-based operations by calculating the 2-dimensional error. The project involved collaboration across multiple different organizations and sectors, including NASA’s Crustal Dynamics Data Information System (CDDIS) researchers, John Deere, a Brazilian farm for data acquisition, and Brazilian universities for data interpretation. The results aim to inform Brazilian farmers about position errors affecting their precision agriculture operations and provide insights into the needs of space weather data users and modeling. Lessons from this case study will guide future integration of space weather data and modeling with end users.

Melissa Marquez↗
NASA NTRS2021

A Semi-Empirical Scheme for Bathymetric Mapping in Shallow Water by ICESat-2 and Sentinel-2: A Case Study in the South China Sea

To derive shallow water bathymetry for coastal areas, a common approach is to deploy a scanning airborne bathymetric light detection and ranging (LiDAR) system or a shipborne echosounder for ground surveys. However, recent advancements in satellite remote sensing, including the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) offer new tools for generating satellite derived bathymetry (SDB). The key payload onboard ICESat-2 is the Advanced Topographic Laser Altimeter System (ATLAS), a micro-pulse, photon-counting LiDAR system, simultaneously emitting six separate 532 nm beams at 10 kHz pulse rate. However, despite its high resolution, the major limitation for bathymetry is that ICESat-2 only provides along-track height profiles, leaving observation gaps between the parallel ground tracks. Merging ICESat-2 observations with optical multispectral imagery, as demonstrated herein, provides an effective solution for deriving a full scene of water depth in light of the spectral attenuation behavior. This study aims to combine ICESat-2 and Sentinel-2 optical data to derive shallow water bathymetry (depth <20 m) at six islands and reefs in the South China Sea. ICESat-2 ATL03 point clouds of georeferenced photons are first filtered to determine the seafloor elevation along the ground track. Results indicate a root-mean-square error (RMSE) of 0.26–0.61 m as compared with independent observations from an airborne LiDAR campaign. Next, three semi-empirical functions, namely the Modified Linear/Polynomial/Exponential Ratio Models with its kernel formed by the log ratio between Sentinel-2′s green and blue bands, are used to fit the spectral data with ICESat-2 height profiles. After water depth mapping using the trained model, independent ICESat-2 point clouds are used to validate the Sentinel-2 derived bathymetry. The RMSE values of the three models using the weighted average of multiple images for these six islands are within 0.50–0.90 m in 0–15 m deep. We also demonstrate that a synthesis of satellite laser altimetry and optical remote sensing can produce SDB results that potentially meet the requirement of category C in Zones of Confidence (ZOC) of the Electronic Navigational Chart (ENC) in 0–8 m deep. It is foreseen that ICESat-2 will be a helpful tool for mapping coastal and shallow waters around the world especially where bathymetric data are unavailable.

Coastal Bathymetry↗
DOE OSTI2025

An efficient hybrid downscaling framework to estimate high-resolution river hydrodynamics

Flow depth and velocity are the most important hydrodynamic variables that govern various river functions, including water resources, navigation, sediment transport, and biogeochemical cycling. Existing high-resolution flow depth simulations rely on either computationally expensive river hydrodynamic models (RHMs) or data-driven models with formidable training costs, whereas data-driven modeling of flow velocity has rarely been explored. Here, using the hybrid Low-fidelity, Spatial analysis, and Gaussian process learning (LSG) model, we developed a downscaling approach to construct high-resolution flow depth and velocity from a two-dimensional (2-D) RHM simulation at coarse resolution. The LSG models were trained and tested in an urban watershed in Houston using two different hurricane-driven flood events. The high-resolution (as fine as 30 m resolution) and low-resolution (mostly 1000 m resolution) meshes include 664 724 and 14 536 grid cells, respectively. The results showed that through downscaling, the simulation errors were reduced to less than one-fourth and one-third of the errors of the low-resolution 2-D RHM for flow depth and velocity, respectively. Our analysis further revealed that the dominant uncertainty sources of the downscaled hydrodynamics are different, with flow velocity dominated by the dimensionality reduction error, which we reduced by using a regionalized training procedure. The downscaling approach achieves an 84-fold acceleration in computational time compared to the high-resolution 2-D RHM, making high-fidelity ensemble flood modeling feasible. More importantly, the developed method provides an opportunity to couple large-scale hydrodynamical processes with local physical, chemical, and biological processes in river models.

Tan, Zeli [Pacific Northwest National Laboratory (↗
DOE OSTI2025

Dual‐Transformer Deep Learning Framework for Seasonal Forecasting of Great Lakes Water Levels

Abstract The Great Lakes of North America form one of the largest freshwater systems on Earth, and their lake‐wide average water levels (lake levels) can fluctuate by more than 0.5 m on a seasonal scale. These fluctuations pose substantial challenges for coastal resilience, flood risk management, and navigation planning. Accurate seasonal forecasting of lake levels using traditional mechanistic models is challenging due to the complex physical mechanisms and coupled hydroclimatic processes involved. Recently, deep learning has gained prominence in geoscience applications for its ability to recognize intricate patterns within multiphysical data sets. Here, we introduce a novel Dual‐Transformer deep learning framework, tested on the Great Lakes. This architecture integrates two modified Transformer models: the Prophet, which predicts underlying trends, and the Critic, which refines the Prophet's predictions. The final lake level prediction is derived by weighting the outputs of both models through a multi‐layer perceptron, jointly trained with the Prophet and Critic to enhance overall accuracy. Our results demonstrate that the innovative learning framework achieves the highest prediction accuracy compared to established deep learning models when using identical input features. It attains a root mean square error of 4–7 cm in predicting lake levels up to 6 months in advance across the lakes. Additionally, the Dual‐Transformer model runs six orders of magnitude faster than conventional mechanistic models, producing results in less than one second on a typical personal computer. These findings suggest that our deep learning framework has strong potential to advance lake level prediction and carries important implications for water management and disaster mitigation, thereby enhancing the quality of life in coastal regions.

Chen, Yi [Great Lakes Research Center Michigan Tec↗
DOE OSTI2025

Real-Time High-Accuracy Digital Wireless Time, Frequency, and Phase Calibration for Coherent Distributed Antenna Arrays

his work presents a fully-digital high-accuracy real-time calibration procedure for frequency and time alignment of open-loop wirelessly coordinated coherent distributed antenna array (CDA) modems, enabling radio frequency (RF) phase coherence of spatially separated commercial off-the-shelf (COTS) software-defined radios (SDRs) without cables or external references such as the global navigation satellite system (GNSS). Building on previous work using high-accuracy spectrally-sparse time of arrival (ToA) waveforms and a multistep ToA refinement process, a high-accuracy two-way time transfer (TWTT)-based time–frequency coordination approach is demonstrated. Due to the two-way nature of the high-accuracy TWTT approach, the time and frequency estimates are Doppler and multipath tolerant, so long as the channel is reciprocal over the synchronization epoch. This technique is experimentally verified using COTS SDRs in a lab environment in static and dynamic scenarios and with significant multipath scatterers. Time, frequency, and phase stability were evaluated by beamforming over coaxial cables to an oscilloscope which achieved time and phase precisions of ~60– 70 ps , with median coherent gains above 99% using optimized coordination parameters, and a beamforming frequency root-mean-square error (RMSE) of 3.73 ppb in a dynamic scenario. Finally, experiments were conducted to compare the performance of this technique with previous works using an analog continuous-wave two-tone (CWTT) frequency reference technique in both static and dynamic settings.

Clock synchronization↗
NASA NTRS2007

Measuring Image Navigation and Registration Performance at the 3-Sigma Level Using Platinum Quality Landmarks

Geostationary Operational Environmental Satellite (GOES) Image Navigation and Registration (INR) performance is specified at the 3- level, meaning that 99.7% of a collection of individual measurements must comply with specification thresholds. Landmarks are measured by the Replacement Product Monitor (RPM), part of the operational GOES ground system, to assess INR performance and to close the INR loop. The RPM automatically discriminates between valid and invalid measurements enabling it to run without human supervision. In general, this screening is reliable, but a small population of invalid measurements will be falsely identified as valid. Even a small population of invalid measurements can create problems when assessing performance at the 3-sigma level. This paper describes an additional layer of quality control whereby landmarks of the highest quality ("platinum") are identified by their self-consistency. The platinum screening criteria are not simple statistical outlier tests against sigma values in populations of INR errors. In-orbit INR performance metrics for GOES-12 and GOES-13 are presented using the platinum landmark methodology.

Carr, James L.↗
NASA NTRS1973

Feasibility test for a V-slit star mapper for pioneer spacecraft terminal navigation

A laboratory demonstration of the feasibility of using a V-slit star mapper to meet the sensitivity and accuracy of on-board navigational requirements for future Pioneer Missions to the outer planets was conducted by the Control and Sensors Laboratory of TRW. The breadboard was extremely simple in configuration, consisting of an end-on photomultiplier tube and a V-slit reticle located at the focal plane of the objective lens. In addition, a plano-convex lens was used between the reticle and the PMT in a Fabry-Perot configuration. The analytical effort indicated that the sensor should easily meet the requirements. The Pioneer SRA test set was examined to determine its basic accuracy and modify it where necessary to bring its accuracy into the 1-3 arc second range. The test results show that it is feasible to use this type of star mapper in the 10 arc second accuracy range. The test equipment accuracy (approximately 5 arc Sec) was sufficient to bound the sensor errors at less than 10 arc seconds.

Gates, R. F.↗
NASA NTRS1989

GOES I/M image navigation and registration

Image Navigation and Registration (INR) is the system that will be used on future Geostationary Operational Environmental Satellite (GOES) missions to locate and register radiometric imagery data. It consists of a semiclosed loop system with a ground-based segment that generates coefficients to perform image motion compensation (IMC). The IMC coefficients are uplinked to the satellite-based segment, where they are used to adjust the displacement of the imagery data due to movement of the imaging instrument line-of-sight. The flight dynamics aspects of the INR system is discussed in terms of the attitude and orbit determination, attitude pointing, and attitude and orbit control needed to perform INR. The modeling used in the determination of orbit and attitude is discussed, along with the method of on-orbit control used in the INR system, and various factors that affect stability. Also discussed are potential error sources inherent in the INR system and the operational methods of compensating for these errors.

Fiorello, J. L., Jr.↗
NASA NTRS2001

Space Shuttle Main Engine Joint Data List Applying Today's Desktop Technologies to Facilitate Engine Processing

Boeing-Rocketdyne's Space Shuttle Main Engine (SSME) is the world's first large reusable liquid rocket engine. The space shuttle propulsion system has three SSMEs, each weighing 7,400 lbs and providing 470,000 lbs of thrust at 100% rated power level. To ensure required safety and reliability levels are achieved with the reusable engines, each SSME is partially disassembled, inspected, reassembled, and retested at Kennedy Space Center between each flight. Maintenance processing must be performed very carefully to replace any suspect components, maintain proper engine configuration, and avoid introduction of contaminants that could affect performance and safety. The long service life, and number, complexity, and pedigree of SSME components makes logistics functions extremely critical. One SSME logistics challenge is documenting the assembly and disassembly of the complex joint configurations. This data (joint nomenclature, seal and fastener identification and orientation, assembly sequence, fastener torques, etc.) must be available to technicians and engineers during processing. Various assembly drawings and procedures contain this information, but in this format the required (practical) joint data can be hard to find, due to the continued use of archaic engineering drawings and microfilm for field site use. Additionally, the release system must traverse 2,500 miles between design center and field site, across three time zones, which adds communication challenges and time lags for critical engine configuration data. To aid in information accessibility, a Joint Data List (JDL) was developed that allows efficient access to practical joint data. The published JDL has been a very useful logistics product, providing illustrations and information on the latest SSME configuration. The JDL identifies over 3,350 unique parts across seven fluid systems, over 300 joints, times two distinct engine configurations. The JDL system was recently converted to a web-based, navigable electronic manual that contains all the required data and illustrations in expanded view format using standard PC products (Word, Excel, PDF, Photoshop). The logistics of accurately releasing this information to field personnel was greatly enhanced via the utilization of common office products to produce a more user-friendly format than was originally developed under contract to NASA. This was done without reinventing the system, which would be cost prohibitive on a program of this maturity. The brunt of the joint part tracking is done within the logistics organization and disseminated to all field sites, without duplicating effort at each site. The JDL is easily accessible across the country via the NASA intranet directly at the SSME workstand. The advent of this logistics data product has greatly enhanced the reliability of tracking dynamic changes to the SSME and greatly reduces engineering change turnaround time and potential for errors. Since the inception of the JDL system in 1997, no discrepant parts have propagated to engine assembly operations. This presentation focuses on the challenges overcome and the techniques used to apply today's desktop technologies to an existing logistics data source.

Jacobs, Kenneth↗
NASA NTRS2006

Human Factors Considerations for Area Navigation Departure and Arrival Procedures

Area navigation (RNAV) procedures are being implemented in the United States and around the world as part of a transition to a performance-based navigation system. These procedures are providing significant benefits and have also caused some human factors issues to emerge. Under sponsorship from the Federal Aviation Administration (FAA), the National Aeronautics and Space Administration (NASA) has undertaken a project to document RNAV-related human factors issues and propose areas for further consideration. The component focusing on RNAV Departure and Arrival Procedures involved discussions with expert users, a literature review, and a focused review of the NASA Aviation Safety Reporting System (ASRS) database. Issues were found to include aspects of air traffic control and airline procedures, aircraft systems, and procedure design. Major findings suggest the need for specific instrument procedure design guidelines that consider the effects of human performance. Ongoing industry and government activities to address air-ground communication terminology, design improvements, and chart-database commonality are strongly encouraged. A review of factors contributing to RNAV in-service errors would likely lead to improved system design and operational performance.

Barhydt, Richard↗
NASA NTRS2011

Modeling and Simulation for Multi-Missions Space Exploration Vehicle

Asteroids and Near-Earth Objects [NEOs] are of great interest for future space missions. The Multi-Mission Space Exploration Vehicle [MMSEV] is being considered for future Near Earth Object missions and requires detailed planning and study of its Guidance, Navigation, and Control [GNC]. A possible mission of the MMSEV to a NEO would be to navigate the spacecraft to a stationary orbit with respect to the rotating asteroid and proceed to anchor into the surface of the asteroid with robotic arms. The Dynamics and Real-Time Simulation [DARTS] laboratory develops reusable models and simulations for the design and analysis of missions. In this paper, the development of guidance and anchoring models are presented together with their role in achieving mission objectives and relationships to other parts of the simulation. One important aspect of guidance is in developing methods to represent the evolution of kinematic frames related to the tasks to be achieved by the spacecraft and its robot arms. In this paper, we compare various types of mathematical interpolation methods for position and quaternion frames. Subsequent work will be on analyzing the spacecraft guidance system with different movements of the arms. With the analyzed data, the guidance system can be adjusted to minimize the errors in performing precision maneuvers.

Multi-Mission Space Exploration Vehicle [MMSEV]↗
NASA NTRS2015

The Rise of GNSS Reflectometry for Earth Remote Sensing

The Global Navigation Satellite System (GNSS) reflectometry, i.e. GNSS-R, is a novel remote-sensing technique first published in that uses GNSS signals reflected from the Earth's surface to infer its surface properties such as sea surface height (SSH), ocean winds, sea-ice coverage, vegetation, wetlands and soil moisture, to name a few. This communication discusses the scientific value of GNSS-R to (a) furthering our understanding of ocean mesoscale circulation toward scales finer than those that existing nadir altimeters can resolve, and (b) mapping vegetated wetlands, an emerging application that might open up new avenues to map and monitor the planet's wetlands for methane emission assessments. Such applications are expected to be demonstrated by the availability of data from GEROS-ISS, an ESA experiment currently in phase A, and CyGNSS [3], a NASA mission currently in development. In particular, the paper details the expected error characteristics and the role of filtering played in the assimilation of these data to reduce the altimetric error (when averaging many measurements).

wetland mapping↗
DOE OSTI2024

EHR-BERT: A BERT-based model for effective anomaly detection in electronic health records

Objective: Physicians and clinicians rely on data contained in electronic health records (EHRs), as recorded by health information technology (HIT), to make informed decisions about their patients. The reliability of HIT systems in this regard is critical to patient safety. Consequently, better tools are needed to monitor the performance of HIT systems for potential hazards that could compromise the collected EHRs, which in turn could affect patient safety. In this paper, we propose a new framework for detecting anomalies in EHRs using sequence of clinical events. This new framework, EHR-Bidirectional Encoder Representations from Transformers (BERT), is motivated by the gaps in the existing deep-learning related methods, including high false negatives, sub-optimal accuracy, higher computational cost, and the risk of information loss. EHR-BERT is an innovative framework rooted in the BERT architecture, meticulously tailored to navigate the hurdles in the contemporary BERT method; thus, enhancing anomaly detection in EHRs for healthcare applications.Methods: The EHR-BERT framework was designed using the Sequential Masked Token Prediction (SMTP) method. This approach treats EHRs as natural language sentences and iteratively masks input tokens during both training and prediction stages. This method facilitates the learning of EHR sequence patterns in both directions for each event and identifies anomalies based on deviations from the normal execution models trained on EHR sequences.Results: Extensive experiments on large EHR datasets across various medical domains demonstrate that EHR-BERT markedly improves upon existing models. It significantly reduces the number of false positives and enhances the detection rate, thus bolstering the reliability of anomaly detection in electronic health records. This improvement is attributed to the model’s ability to minimize information loss and maximize data utilization effectively.Conclusion: EHR-BERT showcases immense potential in decreasing medical errors related to anomalous clinical events, positioning itself as an indispensable asset for enhancing patient safety and the overall standard of healthcare services. The framework effectively overcomes the drawbacks of earlier models, making it a promising solution for healthcare professionals to ensure the reliability and quality of health data.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗