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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Systems and methods for augmenting a satellite based navigation system with alternative position and timing data

Various technologies pertaining to integrating a positioning or timing solution from an alternative position, navigation, or timing (PNT) system into a satellite-based-navigation system are described herein. The PNT system generates a position/timing (P/T) solution that indicates a current position or current time of the PNT system. The P/T solution is provided as input to a simulation of a satellite constellation of the satellite-based-navigation system, and a constellation signal is generated based on the simulation and the P/T solution. The constellation signal is formatted according to a navigation signal format of the satellite-based-navigation system such that when the constellation signal is provided to a receiver of the satellite-based-navigation system, the receiver computes a P/T solution that indicates the current position or the current time identified by the PNT system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

SU-G-JeP3-10: Update On a Real-Time Treatment Guidance System Using An IR Navigation System for Pleural PDT

Purpose: Photodynamic therapy (PDT) is used in conjunction with surgical debulking of tumorous tissue during treatment for pleural mesothelioma. One of the key components of effective PDT is uniform light distribution. Currently, light is monitored with 8 isotropic light detectors that are placed at specific locations inside the pleural cavity. A tracking system with real-time feedback software can be utilized to improve the uniformity of light in addition to the existing detectors. Methods: An infrared (IR) tracking camera is used to monitor the movement of the light source. The same system determines the pleural geometry of the treatment area. Software upgrades allow visualization of the pleural cavity as a two-dimensional volume. The treatment delivery wand was upgraded for ease of light delivery while incorporating the IR system. Isotropic detector locations are also displayed. Data from the tracking system is used to calculate the light fluence rate delivered. This data is also compared with in vivo data collected via the isotropic detectors. Furthermore, treatment volume information will be used to form light dose volume histograms of the pleural cavity. Results: In a phantom study, the light distribution was improved by using real-time guidance compared to the distribution when using detectors without guidance. With the tracking system, 2D data can be collected regarding light fluence rather than just the 8 discrete locations inside the pleural cavity. Light fluence distribution on the entire cavity can be calculated at every time in the treatment. Conclusion: The IR camera has been used successfully during pleural PDT patient treatment to track the motion of the light source and provide real-time display of 2D light fluence. It is possible to use the feedback system to deliver a more uniform dose of light throughout the pleural cavity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

A bronchoscopic navigation system using bronchoscope center calibration for accurate registration of electromagnetic tracker and CT volume without markers

Purpose: Various bronchoscopic navigation systems are developed for diagnosis, staging, and treatment of lung and bronchus cancers. To construct electromagnetically navigated bronchoscopy systems, registration of preoperative images and an electromagnetic tracker must be performed. This paper proposes a new marker-free registration method, which uses the centerlines of the bronchial tree and the center of a bronchoscope tip where an electromagnetic sensor is attached, to align preoperative images and electromagnetic tracker systems. Methods: The chest computed tomography (CT) volume (preoperative images) was segmented to extract the bronchial centerlines. An electromagnetic sensor was fixed at the bronchoscope tip surface. A model was designed and printed using a 3D printer to calibrate the relationship between the fixed sensor and the bronchoscope tip center. For each sensor measurement that includes sensor position and orientation information, its corresponding bronchoscope tip center position was calculated. By minimizing the distance between each bronchoscope tip center position and the bronchial centerlines, the spatial alignment of the electromagnetic tracker system and the CT volume was determined. After obtaining the spatial alignment, an electromagnetic navigation bronchoscopy system was established to real-timely track or locate a bronchoscope inside the bronchial tree during bronchoscopic examinations. Results: The electromagnetic navigation bronchoscopy system was validated on a dynamic bronchial phantom that can simulate respiratory motion with a breath rate range of 0–10 min{sup −1}. The fiducial and target registration errors of this navigation system were evaluated. The average fiducial registration error was reduced from 8.7 to 6.6 mm. The average target registration error, which indicates all tracked or navigated bronchoscope position accuracy, was much reduced from 6.8 to 4.5 mm compared to previous registration methods. Conclusions: An electromagnetically navigated bronchoscopy system was constructed with accurate registration of an electromagnetic tracker and the CT volume on the basis of an improved marker-free registration approach that uses the bronchial centerlines and bronchoscope tip center information. The fiducial and target registration errors of our electromagnetic navigation system were about 6.6 and 4.5 mm in dynamic bronchial phantom validation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Earth-Centered, Earth-Fixed Inertial Navigation System & Error-State Kalman Filter Reference Manual

This is a self-contained reference document that derives the equations necessary to build a combined inertial navigation system and error-state Kalman filter. Coordinate transform, linear time invariant system, inertial sensing, and error-state Kalman filtering theory is built up from first principles. This theory is then leveraged to derive the system equations for two combined inertial navigation system and error-state Kalman filters: (1) a 15-state system modeling white-noise-integrating accelerometer and gyroscope biases, and (2) a 39-state system modeling static and first-order Gauss-Markov accelerometer and gyroscope biases, scale factor errors, and cross-axis sensitivity errors.

42 ENGINEERING↗
DOE OSTI2026

On Transforming the Specific Force Vector for an ECEF Inertial Navigation System

An inertial measurement unit accumulates the instantaneous specific force applied to the sensor over a small window of time. Importantly, this accumulation occurs in the sensor’s frame, yet the specific force must be mathematically integrated in a different navigation frame, and these two frames may be rotating with respect to each other. Consequently, a correction is needed to not only account for the frame difference but also for the time variation in the frame difference. Many references provide derivations of this correction [1], but the derivation is often abbreviated, and important assumptions are sometimes left unstated. This memo addresses this gap and provides a clear derivation of the specific force transform with all assumptions specifically stated. This derivation is specific to the Earth-centered, Earth-fixed navigation frame, but, hopefully, the derivation is sufficiently clear that readers can apply it to other navigation frames. Generally, notation follows the same format as described in both [1, 2].

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Multiple Hypothesis Tracking for Opportunistic Transmitter Identification

The exploitation of radio frequency (RF) signals from Low Earth Orbit (LEO) communication satellites for the purposes of navigation is an active field of research. In this alternative navigation system, navigation observables are passively extracted from existing RF signals. Because these signals are not designed for navigation purposes and often have proprietary signal structures that are unknown to the receiver, they lack much of the information required for navigation systems or such information is unavailable to the receiver.

42 ENGINEERING↗
DOE OSTI2015

Real-Time US-CT/MRI Image Fusion for Guidance of Thermal Ablation of Liver Tumors Undetectable with US: Results in 295 Cases

PurposeThis study was designed to assess feasibility of US-CT/MRI fusion-guided ablation in liver tumors undetectable with US.MethodsFrom 2002 to 2012, 295 tumors (162 HCCs and 133 metastases; mean diameter 1.3 ± 0.6 cm, range 0.5–2.5 cm) detectable on contrast-enhanced CT/MRI, but completely undetectable with unenhanced US and either totally undetectable or incompletely conspicuous with contrast-enhanced US (CEUS), were treated in 215 sessions using either internally cooled radiofrequency or microwave with standard ablation protocols, guided by an image fusion system (Virtual Navigation System, Esaote S.p.A., Genova, Italy) that combines US with CT/ MRI images. Correct targeting and successful ablation of tumor were verified after 24 hours with CT or MRI.ResultsA total of 282 of 295 (95.6 %) tumors were correctly targeted with successful ablation achieved in 266 of 295 (90.2 %). Sixteen of 295 (5.4 %) tumors were correctly targeted, but unsuccessfully ablated, and 13 of 295 (4.4 %) tumors were unsuccessfully ablated due to inaccurate targeting. There were no perioperative deaths. Major complications were observed in 2 of the 215 treatments sessions (0.9 %).ConclusionsReal-time virtual navigation system with US-CT/MRI fusion imaging is precise for targeting and achieving successful ablation of target tumors undetectable with US alone. Therefore, a larger population could benefit from ultrasound guided ablation procedures.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Tsunami Early Warning From Global Navigation Satellite System Data Using Convolutional Neural Networks

Abstract We investigate the potential of using Global Navigation Satellite System (GNSS) observations to directly forecast full tsunami waveforms in real time. We train convolutional neural networks to use less than 9 min of GNSS data to forecast the full tsunami waveforms over 6 hr at select locations, and obtain accurate forecasts on a test data set. Our training and test data consists of synthetic earthquakes and associated GNSS data generated for the Cascadia Subduction Zone using the MudPy software, and corresponding tsunami waveforms in Puget Sound computed using GeoClaw. We use the same suite of synthetic earthquakes and waveforms as in earlier work where tsunami waveforms were used for forecasting, and provide a comparison. We also explore varying the number of GNSS stations, their locations, and their observation durations.

Rim, Donsub↗
DOE OSTI2026

A Proof for the Unbiased Nature of Range-Doppler Measurements in Coarse-Resolution Dechirp-on-Receive Feedback Synthetic Aperture Radar Navigation

In feedback synthetic aperture radar (SAR) navigation, observables extracted from SAR range-Doppler images correct position and velocity errors accumulated within an associated navigation system. Unlike most other sensors, which produce measurements without input from a navigation system, SARs require a prior estimate of the radar’s position and velocity to adjust the radar’s matched filter during range-Doppler image formation. Consequently, it is possible for position and velocity errors within a navigation system to manifest as additional errors (biases) in the range-Doppler measurement observables. Prior work has not tackled this possibility in the context of feedback SAR navigation with a dechirp-on-receive radar. This paper offers a proof demonstrating that range-Doppler observables extracted from coarse-resolution vertical SAR images formed with a dechirp-on-receive radar may be safely modeled as unbiased measurements of the radar’s true position and velocity despite the presence of moderate navigation errors.

dechirp-on-receive↗
DOE OSTI2020

A Chip-Scale Oscillation-Mode Optomechanical Inertial Sensor Near the Thermodynamical Limits

Modern navigation systems integrate the global positioning system (GPS) with an inertial navigation system (INS), which complement each other for correct attitude and velocity determination. Here, the core of the INS integrates accelerometers and gyroscopes used to measure forces and angular rate in the vehicular inertial reference frame. With the help of gyroscopes and by integrating the acceleration to compute velocity and distance, precision and compact accelerometers with sufficient accuracy can provide small–error location determination. Solid–state implementations, through coherent readout, can provide a platform for high performance acceleration detection. In contrast to prior accelerometers using piezoelectric or capacitive readout techniques, optical readout provides narrow–linewidth high–sensitivity laser detection along with low–noise resonant optomechanical transduction near the thermodynamical limits. Here an optomechanical inertial sensor with an 8.2 µg Hz –1/2 velocity random walk (VRW) at an acquisition rate of 100 Hz and 50.9 µg bias instability is demonstrated, suitable for applications, such as, inertial navigation, inclination sensing, platform stabilization, and/or wearable device motion detection. Driven into optomechanical sustained–oscillation, the slot photonic crystal cavity provides radio–frequency readout of the optically–driven transduction with an enhanced 625 µg Hz –1 sensitivity. Measuring the optomechanically–stiffened oscillation shift, instead of the optical transmission shift, provides a 220× VRW enhancement over pre–oscillation mode detection.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Characterizing and communicating uncertainty: lessons from NASA’s Carbon Monitoring System

Navigating uncertainty is a critical challenge in all fields of science, especially when translating knowledge into real-world policies or management decisions. However, the wide variance in concepts and definitions of uncertainty across scientific fields hinders effective communication. As a microcosm of diverse fields within Earth Science, NASA’s Carbon Monitoring System (CMS) provides a useful crucible in which to identify cross-cutting concepts of uncertainty. The CMS convened the Uncertainty Working Group (UWG), a group of specialists across disciplines, to evaluate and synthesize efforts to characterize uncertainty in CMS projects. This paper represents efforts by the UWG to build a heuristic framework designed to evaluate data products and communicate uncertainty to both scientific and non-scientific end users. We consider four pillars of uncertainty: origins, severity, stochasticity versus incomplete knowledge, and spatial and temporal autocorrelation. Using a common vocabulary and a generalized workflow, the framework introduces a graphical heuristic accompanied by a narrative, exemplified through contrasting case studies. Envisioned as a versatile tool, this framework provides clarity in reporting uncertainty, guiding users and tempering expectations. Beyond CMS, it stands as a simple yet powerful means to communicate uncertainty across diverse scientific communities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System

Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗
DOE OSTI2024

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System: Preprint

Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

SU-F-P-42: “To Navigate, Or Not to Navigate: HDR BT in Recurrent Spine Lesions”

Purpose: We compare the accuracy of HDR catheter placement for paraspinal lesions using O-arm CBCT imaging combined with StealthStation navigation and traditional fluoroscopically guided catheter placement. Methods: CT and MRI scans were acquired pre-treatment to outline the lesions and design treatment plans (pre-plans) to meet dosimetric constrains. The pre-planned catheter trajectories were transferred into the StealthStation Navigation system prior to the surgery. The StealthStation is an infra red (IR) optical navigation system used for guidance of surgical instruments. An intraoperative CBCT scan (O-arm) was acquired with reference IR optical fiducials anchored onto the patient and registered with the preplan image study to guide surgical instruments in relation to the patients’ anatomy and to place the brachytherapy catheters along the pre-planned trajectories. The final treatment plan was generated based on a 2nd intraoperative CBCT scan reflecting achieved implant geometry. The 2nd CBCT was later registered with the initial CT scan to compare the preplanned dwell positions with actual dwell positions (catheter placements). Similar workflow was used in placement of 8 catheters (1 patient) without navigation, but under fluoroscopy guidance in an interventional radiology suite. Results: A total of 18 catheters (3 patients) were placed using navigation assisted surgery. Average displacement of 0.66 cm (STD=0.37cm) was observed between the pre-plan source positions and actual source positions in the 3 dimensional space. This translates into an average 0.38 cm positioning error in one direction including registration errors, digitization errors, and the surgeons ability to follow the planned trajectory. In comparison, average displacement of non-navigated catheters was 0.50 cm (STD=0.22cm). Conclusion: Spinal lesion HDR brachytherapy planning is a difficult task. Catheter placement has a direct impact on target coverage and dose to critical structures. While limited to a handful of patients, our experience shows navigation and fluoroscopy guided placement yield similar results.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

A Real-Time Vehicle-Specific Eco-Routing Model for On-Board Navigation Applications Capturing Transient Vehicle Behavior

The paper develops a real-time vehicle-specific eco-routing model for use in on-board navigation systems for both conventional fuel- and battery-powered electric vehicles. The model uses a novel link cost function that retains all microscopic transient behavior along a link by capturing within-link speed, acceleration, and road grade variations. Specifically, eight vehicle-agnostic link-specific variables are transmitted to the cloud and fused with information received from other connected vehicles. The fused data are then sent back to the connected vehicles and used to compute vehicle-specific eco-routes (edge computing). The solution produces an energy-efficient dynamic user-equilibrium traffic assignment that is solved incrementally. A numerical experiment is first designed to test the model, demonstrating the benefits associated with vehicle-specific eco-routes compared to those produced by traditional models. The model is then implemented in a micro-simulation framework to evaluate the network-wide impacts of the proposed energy-efficient user-optimum incremental traffic assignment for different traffic demand levels. Results demonstrate that the proposed model produces lower network-wide energy consumption levels compared to traditional energy-efficient and travel time user-optimum traffic assignment methods for both conventional fuel and electric vehicles. Conventional fuel savings relative to travel time routing decrease with increasing traffic demand levels, while electric power savings do not vary monotonically with congestion levels. Energy savings relative to traditional eco-routing are also demonstrated to not vary monotonically with demand levels. Results of the study also demonstrate that the transportation network layout significantly affects the eco-routing system performance. Finally, the feasibility of the proposed model in real-world applications is discussed and presented.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗