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At least 73 records · Page 4

Scintillation and cherenkov photon counting detectors with analog silicon photomultipliers for TOF-PET

Objective. Standard signal processing approaches for scintillation detectors in positron emission tomography (PET) derive accurate estimates for 511 keV photon time of interaction and energy imparted to the detection media from aggregate characteristics of electronic pulse shapes. The ultimate realization of a scintillation detector for PET is one that provides a unique timestamp and position for each detected scintillation photon. Detectors with these capabilities enable advanced concepts for three-dimensional (3D) position and time of interaction estimation with methods that exploit the spatiotemporal arrival time kinetics of individual scintillation photons. Approach. In this work, we show that taking into consideration the temporal photon emission density of a scintillator, the channel density of an analog silicon photomultiplier (SiPM) array, and employing fast electronic readout with digital signal processing, a detector that counts and timestamps scintillation photons can be realized. To demonstrate this approach, a prototype detector was constructed, comprising multichannel electronic readout for a bismuth germanate (BGO) scintillator coupled to an SiPM array. Main Results. In proof-of-concept measurements with this detector, we were able to count and provide unique timestamps for 66% of all optical photons, where the remaining 34% (two-or-more-photon pulses) are also independently counted, but each photon bunch shares a common timestamp. We show this detector concept can implement 3D positioning of 511 keV photon interactions and thereby enable corrections for time of interaction estimators. The detector achieved 17.6% energy resolution at 511 keV and 237 ± 10 ps full-width-at-half-maximum coincidence time resolution (CTR) (fast spectral component) versus a reference detector. We outline the methodology, readout, and approach for achieving this detector capability in first-ever, proof-of-concept measurements for scintillation photon counting detector with analog silicon photomultipliers. Significance. The presented detector concept is a promising design for large area, high sensitivity TOF-PET detector modules that can implement advanced event positioning and time of interaction estimators, which could push state-of-the-art performance.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Event Location using Arrival Times from Seismic and Acoustic Phenomena

Accurately locating seismoacoustic sources with geophysical observations helps to monitor natural and anthropogenic phenomena. Sparsely deployed infrasound arrays can readily locate large sources thousands of kms away, but small events typically produce signals observable at only local to regional distances. At such distances, accurate location efforts rely on observations across smaller regional or temporary deployments which often consist of single-channel infrasound sensors that cannot record direction of arrival. Event locations can also be aided by inclusion of ground coupled airwaves (GCA). This study demonstrates how we can robustly locate a catalog of seismoacoustic events using infrasound, GCA, and seismic arrival times at local to near-regional distances. We employ a probabilistic location framework using simplified forward models. Our results indicate that both single-channel infrasound and GCA arrival times can provide accurate estimates of event location in the absence of array-based observations even when using simple models. However, one must carefully choose model uncertainty bounds to avoid underestimation of confidence intervals.

58 GEOSCIENCES↗

Locating Partial Discharges in Power Transformers with Convolutional Iterative Filtering

The most common source of transformer failure is in the insulation, and the most prevalent warning signal for insulation weakness is partial discharge (PD). Locating the positions of these partial discharges would help repair the transformer to prevent failures. This work investigates algorithms that could be deployed to locate the position of a PD event using data from ultra-high frequency (UHF) sensors inside the transformer. These algorithms typically proceed in two steps: first determining the signal arrival time, and then locating the position based on time differences. This paper reviews available methods for each task and then propose new algorithms: a convolutional iterative filter with thresholding (CIFT) to determine the signal arrival time and a reference table of travel times to resolve the source location. The effectiveness of these algorithms are tested with a set of laboratory-triggered PD events and two sets of simulated PD events inside transformers in production use. Tests show the new approach provides more accurate locations than the best-known data analysis algorithms, and the difference is particularly large, 3.7X, when the signal sources are far from sensors.

47 OTHER INSTRUMENTATION↗

Characterization of New Hard X-ray Cataclysmic Variables

Aims. We aim at characterizing a sample of nine new hard X-ray selected Cataclysmic Variable (CVs), to unambiguously identify them as magnetic systems of the Intermediate Polar (IP) type. Methods. We performed detailed timing and spectral analysis by using X-ray, and simultaneous UV and optical data collected by XMM−Newton, complemented with hard X-ray data provided by INTEGRAL and Swift. The pulse arrival time were used to estimate the orbital periods. The broad band X-ray spectra were fitted using composite models consisting of different absorbing columns and emission components. Results. Strong X-ray pulses at the White Dwarf (WD) spin period are detected and found to decrease with energy. Most sources are spin-dominated systems in the X-rays, though four are beat dominated at optical wavelengths. We estimated the orbital period in all system (except for IGR J16500-3307), providing the first estimate for IGRJ08390-4833, IGRJ18308-1232, and IGR J18173-2509. All X-ray spectra are multi-temperature. V2069 Cyg and RX J0636+3535 poses a soft X-ray optically thick component at kT approx. 80 eV. An intense K (sub alpha) Fe line at 6.4 keV is detected in all sources. An absorption edge at 0.76 keV from OVII is detected in IGR J08390-4833. The WD masses and lower limits to the accretion rates are also estimated. Conclusions. We found all sources to be IPs. IGR J08390-4833, V2069 Cyg, and IGR J16500-3307 are pure disc accretors, while IGR J18308-1232, IGR J1509-6649, IGR J17195-4100, and RX J0636+3535 display a disc-overflow accretion mode. All sources show a temperature gradient in the post-shock regions and a highly absorbed emission from material located in the pre-shock flow which is also responsible for the X-ray pulsations. Reflection at the WD surface is likely the origin of the fluorescent iron line. There is an increasing evidence for the presence of a warm absorber in IPs, a feature that needs future exploration. The addition of two systems to the subgroup of soft X-ray IPs confirms a relatively large (∼ 30%) incidence.

hard X-ray↗

Inferring the Focal Depths of Small Earthquakes in Southern California Using Physics-Based Waveform Features

Determining the depths of small crustal earthquakes is challenging in many regions of the world, because most seismic networks are too sparse to resolve trade-offs between depth and origin time with conventional arrival-time methods. Precise and accurate depth estimation is important, because it can help seismologists discriminate between earthquakes and explosions, which is relevant to monitoring nuclear test ban treaties and producing earthquake catalogs that are uncontaminated by mining blasts. Here, we examine the depth sensitivity of several physics-based waveform features for ~8000 earthquakes in southern California that have well-resolved depths from arrival-time inversion. We focus on small earthquakes (2 < M L < 4) recorded at local distances (<150 km), for which depth estimation is especially challenging. We find that differential magnitudes (M w /M L –M c ) are positively correlated with focal depth, implying that coda wave excitation decreases with focal depth. We analyze a simple proxy for relative frequency content, Φ≡log 10 (M 0 )+3log 10 (f c ), and find that source spectra are preferentially enriched in high frequencies, or “blue-shifted,” as focal depth increases. Here, we also find that two spectral amplitude ratios Rg 0.5–2 Hz/Sg 0.5–8 Hz and Pg/Sg at 3–8 Hz decrease as focal depth increases. Using multilinear regression with these features as predictor variables, we develop models that can explain 11%–59% of the variance in depths within 10 subregions and 25% of the depth variance across southern California as a whole. We suggest that incorporating these features into a machine learning workflow could help resolve focal depths in regions that are poorly instrumented and lack large databases of well-located events. Some of the waveform features we evaluate in this study have previously been used as source discriminants, and our results imply that their effectiveness in discrimination is partially because explosions generally occur at shallower depths than earthquakes.

58 GEOSCIENCES↗

Frequency Emitter Geolocation Using Signal Strength Fingerprinting Informed By 3D Propagation Modeling

This work focuses on the problem of RF geolocation in complex multipath environments. Using 3D electromagnetic propagation modeling to characterize environments of interest will enable more accurate RF geolocation. Specifically, a path-loss radio map can be generated in simulation for use in received signal strength indicators (RSSI) fingerprinting, or pattern matching. RSSI fingerprinting is an example of data-based method that takes site specific information into account which should allow for better performance than other model-based methods that use a generalized model of electromagnetic propagation. This modeling capability will also be used to evaluate the relative performance of RSSI fingerprinting, pathloss model based RSSI methods such as differential received signal strength circles (DRSS), RSSI joint gaussian estimation, and time-difference of arrival (TDOA). New methods using this simulation derived electromagnetic characterization could improve the efficacy of currently deployed and future RF spectral monitoring solutions. Wireless InSite developed by Remcom is used as the simulation tool of choice in this work. An indoor location is simulated with a grid of fixed receivers and a grid of transmit locations. Using the output of the Wireless InSite simulation the response from a given transmit location to a given receive location can be generated. During the first year of the project various geolocation methods evaluated on purely synthetic, but realistic, data. The second year focused on testing and validating the efficacy of simulation informed RF geolocation using two physical testbeds. This work has shown that data-based approaches are more accurate than model-based ones at the expensive of requiring measured or simulated site-specific training data.

47 OTHER INSTRUMENTATION↗

A new multifunction acousto-optic signal processor

An acousto-optic architecture for simultaneously obtaining time integration correlation and high-speed power spectrum analysis was constructed using commercially available TeO2 modulators and photodiode detector-arrays. The correlator section of the processor uses coherent interferometry to attain maximum bandwidth and dynamic range while achieving a time-bandwidth product of 1 million. Two correllator outputs are achieved in this system configuration. One is optically filtered and magnified 2 : 1 to decrease the spatial frequency to a level where a 25-MHz bandwidth may be sampled by a 62-mm array with elements on 25-micro centers. The other output is magnified by a factor of 10 such that the center 4 microseconds of information is available for estimation of time-difference-of-arrival to within 10 ns. The Bragg cell spectrum-analyzer section, which also has two outputs, resolves a 25-MHz instantaneous bandwidth to 25 kHz and can determine discrete-frequency reception time to within 15 microseconds. A microprocessor combines spectrum analysis information with that obtained from the correlator.

Berg, N. J.↗

Time-controlled descent guidance in uncertain winds

A procedure has been developed for constructing a statistical model of the altitude-dependent mean wind profile from the historical record of wind measurements at particular locations. The model is constructed by fitting a Markov process, with altitude as the stage variable, to the historical wind data. The wind model, together with the aircraft dynamics and the error characteristics of the navigation system, are incorporated in the design of a state estimator, which gives the minimum variance estimate of the aircraft state and the wind vector. The state and wind estimates are used as inputs to a linear feedback law for guiding the aircraft along the nominal trajectory. An example design of a time-constrained (4D RNAV) descent guidance system is presented, showing tracking accuracy, control activity, and probability of arrival time with and without the wind estimator.

Menga, G.↗

Perturbation analysis of queueing systems with a time-varying arrival rate

The authors consider an M/G/1 queuing with a time-varying arrival rate. The objective is to obtain infinitesimal perturbation analysis (IPA) gradient estimates for various performance measures of interest with respect to certain system parameters. In particular, the authors consider the mean system time over n arrivals and an arrival rate alternating between two values. By choosing a convenient sample path representation of this system, they derive an unbiased IPA gradient estimator which, however, is not consistent, and investigate the nature of this problem.

Cassandras, Christos G.↗

Optimizing infrasound observations for sample return capsule re-entry: Insights from OSIRIS-REx and Hayabusa2

The atmospheric entry of meteoroids presents a rare and unpredictable phenomenon, posing challenges for systematic observation and detailed characterization. Such events are nonetheless critical for advancing understanding of acoustic wave propagation, atmospheric structure, and entry dynamics. In contrast, sample return capsules (SRCs) from space missions follow well constrained re-entry trajectories, enabling planned observations of shock wave generation and propagation under controlled conditions. This study compares two SRC atmospheric entries, Hayabusa2 in 2020 and OSIRIS-REx in 2023, to assess how different infrasound array configurations influence shock wave detection and trajectory validation. Hayabusa2’s re-entry was monitored using a distributed network of 28 portable infrasound sensors across seven arrays in Woomera, Australia, permitting three-dimensional reconstruction of the trajectory and analysis of wave characteristics. For OSIRIS-REx, a compact four-sensor array deployed near Eureka Airport provided trajectory confirmation through arrival-time differences and back-azimuth estimates. Spectral and waveform analyses revealed differences in signal properties associated with variations in entry angle and velocity. The results illustrate both the strengths and the limitations of the deployed array configurations. The dense and distributed arrays during Hayabusa2’s re-entry enabled detailed trajectory reconstruction, whereas the compact array at Eureka primarily provided confirmation of signal coherence and back-azimuth consistency. These case studies highlight that even relatively small arrays, if located close to the predicted ground track, can still capture useful information on arrival direction and timing. Such insights provide practical guidance for planning future observational campaigns of SRC returns and other controlled atmospheric entries, and may also inform approaches to opportunistic observations of meteoroid events and other atmospheric acoustic phenomena.

celestial mechanics: orbit determination↗

UWB Tracking System Design for Lunar/Mars Exploration

This paper describes a design effort for a prototype ultra-wideband (UWB) tracking system that is currently under development at NASA Johnson Space Center (JSC). The system is being studied for use in tracking of lunar/Mars rovers during early exploration missions when satellite navigation systems are not available. The UWB technology is exploited to implement the tracking system due to its properties such as high data rate, fine time resolution, low power spectral density, and multipath immunity. A two-cluster prototype design using commercially available UWB products is proposed to implement the Angle Of Arrival (AOA) tracking methodology in this research effort. An AOA technique using the Time Difference Of Arrival (TDOA) information is utilized for location estimation in the prototype system, not only to exploit the precise time resolution possible with UWB signals, but also to eliminate the need for synchronization between the transmitter and the receiver. After the UWB radio at each cluster is used to obtain the TDOA estimates from the UWB signal sent from the target, the TDOA data is converted to AOA data to find the angle of arrival, assuming this is a far field application. Since the distance between two clusters is known, the target position is computed by a simple triangulation. Simulations show that the average tracking error at a range of 610 meters is 2.7595 meters, less than 0.5% of the tracking range. Outdoor tests to track the SCOUT vehicle (The Science Crew Operations and Utility Testbed) near the Meteor Crater, Flagstaff, Arizona were performed on September 12-13, 2005. The tracking performance was obtained with less than 1% tracking error at ranges up to 2000 feet. No RF interference with on-board GPS, video, voice and telemetry systems was detected. Outdoor tests demonstrated the UWB tracking capability.

Ni, Jianjun↗

Predicting Operator Execution Times Using CogTool

Researchers and developers of NextGen systems can use predictive human performance modeling tools as an initial approach to obtain skilled user performance times analytically, before system testing with users. This paper describes the CogTool models for a two pilot crew executing two different types of a datalink clearance acceptance tasks, and on two different simulation platforms. The CogTool time estimates for accepting and executing Required Time of Arrival and Interval Management clearances were compared to empirical data observed in video tapes and registered in simulation files. Results indicate no statistically significant difference between empirical data and the CogTool predictions. A population comparison test found no significant differences between the CogTool estimates and the empirical execution times for any of the four test conditions. We discuss modeling caveats and considerations for applying CogTool to crew performance modeling in advanced cockpit environments.

Santiago-Espada, Yamira↗

A Robust Initialization Scheme for a Lateral Trajectory Optimization Problem with Time of Arrival Windows

We present a robust initialization scheme that estimates parameter values for the numerical solution of a two-point boundary value problem. The two-point boundary value problem formulation stems from the optimization of a cost functional subject to the dynamics of a simplified lateral aircraft model and other constraints. Leveraging regular perturbation methods, initial parameter estimates are analytically determined and used to initialize a gradient descent optimization routine which is shown to rapidly converge over a range of initial aircraft positions and heading angles. Additionally, the velocity of the aircraft is optimized to ensure the trajectory of the aircraft terminates within a desired region in both time and space.

lateral trajectory optimization↗

Ensemble Simulations of the 2012 July 12 Coronal Mass Ejection with the Constant-turn Flux Rope Model

Flux-rope-based magnetohydrodynamic modeling of coronal mass ejections (CMEs) is a promising tool for prediction of the CME arrival time and magnetic field at Earth. In this work, we introduce a constant-turn flux rope model and use it to simulate the 2012 July 12 16:48 CME in the inner heliosphere. We constrain the initial parameters of this CME using the graduated cylindrical shell (GCS) model and the reconnected flux in posteruption arcades. We correctly reproduce all the magnetic field components of the CME at Earth, with an arrival time error of approximately 1 hr. We further estimate the average subjective uncertainties in the GCS fittings by comparing the GCS parameters of 56 CMEs reported in multiple studies and catalogs. We determined that the GCS estimates of the CME latitude, longitude, tilt, and speed have average uncertainties of 5°.74, 11°.23, 24°.71, and 11.4%, respectively. Using these, we have created 77 ensemble members for the 2012 July 12 CME. We found that 55% of our ensemble members correctly reproduce the sign of the magnetic field components at Earth. We also determined that the uncertainties in GCS fitting can widen the CME arrival time prediction window to about 12 hr for the 2012 July 12 CME. On investigating the forecast accuracy introduced by the uncertainties in individual GCS parameters, we conclude that the half-angle and aspect ratio have little impact on the predicted magnetic field of the 2012 July 12 CME, whereas the uncertainties in longitude and tilt can introduce relatively large spread in the magnetic field predicted at Earth.

Talwinder Singh↗

Uncertainty Quantification of Expected Time-of-Arrival in UAV Flight Trajectory

One of the foremost requirements for accurate in-flight safety monitoring of autonomous unmanned aerial vehicles (UAVs) is tracking of their flight trajectory. Existing UAVs leverage autonomous flight functionalities based on trajectory generation algorithms developed in robotic applications such as polynomial or spline curves in order to facilitate kinematic smoothness, minimum vibrations and fuel efficiency. However in practice, the actual path may be subjected to unexpected local weather conditions, unexpected obstacles along the path or abrupt traffic changes in the low-altitude airspace resulting in large errors of the predicted time-of-arrival at way-points. In this study, an approach to quantify and propagate uncertainty in 4D trajectories is proposed. The paper presents a simple error interval propagation method based on the expected cruise speed of the UAV and its associated uncertainty. The uncertainty is then propagated in time to estimate reasonable confidence intervals on the times-of-arrival of the vehicle at each way-point as well as along the entire flight-path. The uncertainty propagation is demonstrated on a state-of-the-art trajectory generation algorithm based on non-uniform rational B-spline (NURBS) curves. Further, the effect of a stationary wind field is incorporated in the uncertainty propagation approach. The proposed method is implemented on synthetic and real data obtained from flight experiments with a small UAV.

Uncertainty Quantification↗

Self-Supervised T-GCN for Detection of Disturbance and Propagation in Power Grid

Urban power systems increasingly rely on dense sensing to monitor grid reliability, yet disturbance labels are scarce and events are rare. We present a self-supervised spatio-temporal method that detects, localizes, and characterizes grid frequency disturbances across urban areas using only unlabeled data. Our approach trains a tiny Temporal Graph Convolutional Network (T-GCN) to forecast per-site frequency residuals (deviation from 60 Hz). The sensor graph is constructed directly from signals using pre-event Pearson correlation with a cross-correlation lag penalty without geocoding. At inference, node-level anomalies are the model's forecast errors; region-level alarms arise from connected components of high-score nodes. We estimate disturbance propagation by computing per-node arrival times (first persistent exceedance), then fit a planar or time-of-arrival model to obtain direction, speed, and an epicenter proxy. With only three real events collected at decisecond resolution across U.S. cities, we evaluate the T-GCN and report time-to-detect, footprint size, and propagation consistency. We further show that short-window embeddings from the T-GCN's hidden states enable few-shot event-vs-background recognition via a simple prototypical classifier. Despite minimal data and no labels, our system yields fast, spatially coherent detection and interpretable propagation maps, offering a practical, lightweight pathway to city-scale grid resilience analytics.

Niu, Haoran [ORNL] (ORCID:0000000155228297)↗

Fast-Time Simulation for Evaluating the Impact of Estimated Flight Ready Time Uncertainty on Surface Metering

NASA has been developing and demonstrating new concepts and technologies for Integrated Arrival, Departure, and Surface (IADS) traffic management capabilities under the Airspace Technology Demonstration 2 (ATD-2) project. One of the IADS capabilities in the ATD-2 project is surface metering enabled by a tactical surface scheduler to provide controllers with the pushback advisories for departures at gates. The tactical surface scheduler uses the estimated flight ready times provided by airlines, called Earliest Off-Block Times (EOBTs), as input to calculate the target off-block times for pushback advisories. However, the EOBTs are often inaccurate and deviate from the actual flight ready times, which may reduce the benefits of surface metering. In this paper, a linear regression model is developed to model the EOBT uncertainty distribution over time based on actual EOBT data collected at Charlotte airport. This EOBT model is integrated with a tactical surface scheduler and a fast-time simulation tool. To evaluate the impact of the EOBT accuracy on airport surface operations, fast-time simulations are implemented for selected traffic scenarios under different levels of modelled EOBT accuracy. The simulation results show that the EOBT uncertainty affects several performance metrics related to the surface metering, such as gate hold, taxi time reduction, and target takeoff time predictability, which in turn influences ATD-2's scheduler performance.

tactical surface scheduler↗

Fast-Time Simulation for Evaluating the Impact of Estimated Flight Ready Time Uncertainty on Surface Metering

NASA has been developing and demonstrating new concepts and technologies for Integrated Arrival, Departure, and Surface (IADS) traffic management capabilities under the Airspace Technology Demonstration 2 (ATD-2) project. One of the IADS capabilities in the ATD-2 project is surface metering enabled by a tactical surface scheduler to provide controllers with the pushback advisories for departures at gates. The tactical surface scheduler uses the estimated flight ready times provided by airlines, called Earliest Off-Block Times (EOBTs), as input to calculate the target off-block times for pushback advisories. However, the EOBTs are often inaccurate and deviate from the actual flight ready times, which may reduce the benefits of surface metering. In this paper, a linear regression model is developed to model the EOBT uncertainty distribution over time based on actual EOBT data collected at Charlotte airport. This EOBT model is integrated with a tactical surface scheduler and a fast-time simulation tool. To evaluate the impact of the EOBT accuracy on airport surface operations, fast-time simulations are implemented for selected traffic scenarios under different levels of modelled EOBT accuracy. The simulation results show that the EOBT uncertainty affects several performance metrics related to the surface metering, such as gate hold, taxi time reduction, and target takeoff time predictability, which in turn influences ATD-2's scheduler performance.

tactical surface scheduler↗