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At least 343 records · Page 19

Detect-and-Avoid Surveillance Range Requirements for Electro-Optical/Infra-Red Sensors

A detect-and-avoid (DAA) system provides surveillance, alerting, and maneuver guidance (referred to as guidance in this report) that are critical to an unmanned aircraft system’s (UAS) ability to maintain separation from manned aircraft and other unmanned aircraft. The last decade has seen significant progress in the development of DAA requirements, spearheaded by RTCA Special Committee 228 (SC228) and subsequently by other standards organizations such as EUROCAE and ASTM. SC-228’s development of DAA requirements assumes the UAS follows instrument flight rules (IFR) and has a remote pilot or operator in the loop. As of the publication of this document, the SC-228’s latest Minimum Operational Performance Standards (MOPS) for DAA, versioned as DO-365B [1], DAA systems use onboard and/or ground surveillance systems to detect traffic. The surveillance systems must detect both cooperative and non-cooperative air traffic. Cooperative traffic are vehicles that have a broadcasting transponder, while non-cooperative traffic do not, and so must be detected via radar or other sensors. A DAA system’s alerting and guidance functions alert the pilot/operator in the loop of potential hazards, such as intruder aircraft, and provide maneuver solutions which help the pilot/operator avoid or mitigate observed hazards. A UAS pilot is expected to coordinate with air traffic control (ATC) before executing a conflict avoidance maneuver if the type of alert is not urgent enough to require an immediate maneuver.

uncrewed aviation systems↗

ATAT: Astronomical Transformer for time series and Tabular data

Context. The advent of next-generation survey instruments, such as theVera C. RubinObservatory and its Legacy Survey of Space and Time (LSST), is opening a window for new research in time-domain astronomy. The Extended LSST Astronomical Time-Series Classification Challenge (ELAsTiCC) was created to test the capacity of brokers to deal with a simulated LSST stream. Aims. Our aim is to develop a next-generation model for the classification of variable astronomical objects. We describe ATAT, the Astronomical Transformer for time series And Tabular data, a classification model conceived by the ALeRCE alert broker to classify light curves from next-generation alert streams. ATAT was tested in production during the first round of the ELAsTiCC campaigns. Methods. ATAT consists of two transformer models that encode light curves and features using novel time modulation and quantile feature tokenizer mechanisms, respectively. ATAT was trained on different combinations of light curves, metadata, and features calculated over the light curves. We compare ATAT against the current ALeRCE classifier, a balanced hierarchical random forest (BHRF) trained on human-engineered features derived from light curves and metadata. Results. When trained on light curves and metadata, ATAT achieves a macro F1 score of 82.9 ± 0.4 in 20 classes, outperforming the BHRF model trained on 429 features, which achieves a macro F1 score of 79.4 ± 0.1. Conclusions. The use of transformer multimodal architectures, combining light curves and tabular data, opens new possibilities for classifying alerts from a new generation of large etendue telescopes, such as theVera C. RubinObservatory, in real-world brokering scenarios.

Astronomy & Astrophysics↗

Optical follow-up observation for GW event S190510g using Subaru/Hyper Suprime-Cam

Abstract A gravitational wave event, S190510g, which was classified as a binary-neutron-star coalescence at the time of preliminary alert, was detected by LIGO/Virgo collaboration on 2019 May 10. At 1.7 hours after the issue of its preliminary alert, we started a target-of-opportunity imaging observation in the Y band to search for its optical counterpart using the Hyper Suprime-Cam (HSC) on the Subaru Telescope. The observation covers a 118.8 deg2 sky area corresponding to $11.6\%$ confidence in the localization skymap released in the preliminary alert and $1.2\%$ in the updated skymap. We divided the observed area into two fields based on the availability of HSC reference images. For the fields with the HSC reference images, we applied an image subtraction technique; for the fields without the HSC reference images, we sought individual HSC images by matching a catalog of observed objects with the PS1 catalog. The search depth is 22.28 mag in the former method and the limit of search depth is 21.3 mag in the latter method. Subsequently, we performed visual inspection and obtained 83 candidates using the former method and 50 candidates using the latter method. Since we only have the one-day photometric data, we evaluated the probability of candidates being located inside the 3D skymap by estimating their distances with photometry of associated extended objects. We found three candidates are likely located inside the 3D skymap and concluded they could be a counterpart of S190510g, while most of the 133 candidates were likely to be supernovae because the number density of candidates was consistent with the expected number of supernova detections. By comparing our observational depth with a light-curve model of such a kilonova reproducing AT2017gfo, we show that early deep observations with the Subaru/HSC can capture the rising phase of the blue component of a kilonova at the estimated distance of S190510g (∼230 Mpc).

79 ASTRONOMY AND ASTROPHYSICS↗

Photovoltaic Inverter Failure Mechanism Estimation Using Unsupervised Machine Learning and Reliability Assessment

This article introduces a data-driven approach to assessing failure mechanisms and reliability degradation in outdoor photovoltaic (PV) string inverters. The manufacturer's stated PV inverter lifetime can vary due to the impact of operating site conditions. To address limitations in degradation estimation through accelerated testing, condition monitoring, or degradation modeling, we propose a machine learning (ML) oriented approach. Utilizing data from a 1.4 MW PV power plant operational since 2016, with 46 string PV inverters tied to the grid, we employ the unsupervised one-class support vector machine ML technique to analyze inverter and sensor data, capable of classifying humidity cycling and temperature fluctuations as dominant failure mechanisms. Utilizing the anomaly alert relationship and alert details specific to the inverter, the level of PV inverter output is considered as its availability or available reliability. Subsequently, a continuous Markov model is applied to six-month alert data, revealing an average stated reliability of 20% after 20 years of continuous operation. These results support recommendations for time-bound preventive measures to enhance PV inverter reliability under diverse outdoor conditions. Furthermore, the approach provides a nondestructive, top–down, and generalized method for analyzing any commercial PV inverter exposed to outdoor conditions, contingent on the availability of relevant data.

14 SOLAR ENERGY↗

Inter-Domain Fusion for Enhanced Intrusion Detection in Power Systems: An Evidence Theoretic and Meta-Heuristic Approach

False alerts due to misconfigured or compromised intrusion detection systems (IDS) in industrial control system (ICS) networks can lead to severe economic and operational damage. However, research using deep learning to reduce false alerts often requires the physical and cyber sensor data to be trustworthy. Implicit trust is a major problem for artificial intelligence or machine learning (AI/ML) in cyber-physical system (CPS) security, because when these solutions are most urgently needed is also when they are most at risk (e.g., during an attack). To address this, the Inter-Domain Evidence theoretic Approach for Inference (IDEA-I) is proposed that reframes the detection problem as how to make good decisions given uncertainty. Specifically, an evidence theoretic approach leveraging Dempster–Shafer (DS) combination rules and their variants is proposed for reducing false alerts. A multi-hypothesis mass function model is designed that leverages probability scores obtained from supervised-learning classifiers. Using this model, a location-cum-domain-based fusion framework is proposed to evaluate the detector’s performance using disjunctive, conjunctive, and cautious conjunctive rules. The approach is demonstrated in a cyber-physical power system testbed, and the classifiers are trained with datasets from Man-In-The-Middle attack emulation in a large-scale synthetic electric grid. For evaluating the performance, we consider plausibility, belief, pignistic, and general Bayesian theorem-based metrics as decision functions. To improve the performance, a multi-objective-based genetic algorithm is proposed for feature selection considering the decision metrics as the fitness function. Finally, we present a software application to evaluate the DS fusion approaches with different parameters and architectures.

42 ENGINEERING↗

Clear air turbulence - Detection by infrared observations of water vapor

'Forward-looking' infrared measurements of water vapor from the C-141A Kuiper Airborne Observatory of the National Aeronautics and Space Administration Ames Research Center show large, distinctly identifiable, signal anomalies from 4 to 10 minutes in advance of subsequent encounters with clear air turbulence (CAT). These anomalies are characteristically different from the signals not followed by CAT encounters. Results of airborne field trials in which the infrared radiometer was used indicate that, out of 51 situations, 80 percent were CAT alerts followed by CAT encounters, 12 percent were 'false alarms' (CAT alerts not followed by CAT encounters), and 8 percent were CAT encounters not preceded by an infrared signal anomaly or CAT alert.

Kuhn, P.↗

Design and preliminary tests of an IR-airborne LLWS remote sensing system

Recent history underscores the need for in-cockpit alerts of LLWS for takeoffs and landings. The 13-15 micron portion of the CO2 molecular spectrum can be used to remote sense LLWS in and around thunderstorms. A radiometer with a designed look-distance of about 10 km remote senses an average air temperature along a forward, horizontal path. Wind shear alerts are based on the difference between this forward air temperature and the air temperature near the aircraft. Although spectral ranging, a major design improvement of an IR LLWS alert system, is not at present feasible with noncooled detectors, it is an important technique to keep in mind, given the rapid advance in IR technology.

Caracena, F.↗

A concept for reducing oceanic separation minima through the use of a TCAS-derived CDTI

A concept for using a cockpit display of traffic information (CDTI), as derived from a modified version of the Traffic Alert and Collision Avoidance System 2 (TCAS 2), to support reductions in air traffic separation minima for an oceanic track system is presented. The concept, and the TCAS modifications required to support it, are described. The feasibility of the concept is examined from a number of standpoints, including expected benefits, maximum alert rates, and possible transition strategies. Various implementation issues are analyzed. Pilot procedures are suggested for dealing with alert situations. Possible variations of the concept are also examined. Finally, recommendations are presented for other studies and simulation experiments which can be used to further verify the feasibility of the concept.

Love, W. D.↗

CANOZE measurements of the Arctic ozone hole

In CANOZE 1 (Canadian Ozone Experiment), a series of 20 ozone profile measurements were made in April, 1986 from Alert at 82.5 N. CANOZE is the Canadian program for study of the Arctic winter ozone layer. In CANOZE 2, ozone profile measurements were made at Saskatoon, Edmonton, Churchill and Resolute during February and March, 1987 with ECC ozonesondes. Ground based measurements of column ozone, nitrogen dioxide and hydrochloric acid were conducted at Saskatoon. Two STRATOPROBE balloon flights were conducted on February 26 and March 19, 1987. Two aerosol flights were conducted by the University of Wyoming. The overall results of this study will be reported and compared with the NOZE findings. The results from CANOZE 3 in 1988, are also discussed. In 1988, as part of CANOZE 3, STRATOPROBE balloon flights were conducted from Saskatchewan on January 27 and February 13. A new lightweight infrared instrument was developed and test flown. A science flight was successfully conducted from Alert (82.5 N) on March 9, 1988 when the vortex was close to Alert; a good measurement of the profile of nitric acid was obtained. Overall, the Arctic spring ozone layer exhibits many of the features of the Antarctic ozone phenomenon, although there is obviously not a hole present every year. The Arctic ozone field in March, 1986 demonstrated many similarities to the Antarctic ozone hole. The TOMS imagery showed a crater structure in the ozone field similar to the Antarctic crater in October. Depleted layers of ozone were found in the profiles around 15 km, very similar to those reported from McMurdo. Enhanced levels of nitric acid were measured in air which had earlier been in the vortex. The TOMS imagery for March 1987 did not show an ozone crater, but will be examined for an ozone crater in February and March, 1988, the target date for the CANOZE 3 project.

Evans, W. F. J.↗

Advanced power sources for space missions

Approaches to satisfying the power requirements of space-based Strategic Defense Initiative (SDI) missions are studied. The power requirements for non-SDI military space missions and for civil space missions of the National Aeronautics and Space Administration (NASA) are also considered. The more demanding SDI power requirements appear to encompass many, if not all, of the power requirements for those missions. Study results indicate that practical fulfillment of SDI requirements will necessitate substantial advances in the state of the art of power technology. SDI goals include the capability to operate space-based beam weapons, sometimes referred to as directed-energy weapons. Such weapons pose unprecedented power requirements, both during preparation for battle and during battle conditions. The power regimes for these two sets of applications are referred to as alert mode and burst mode, respectively. Alert-mode power requirements are presently stated to range from about 100 kW to a few megawatts for cumulative durations of about a year or more. Burst-mode power requirements are roughly estimated to range from tens to hundreds of megawatts for durations of a few hundred to a few thousand seconds. There are two likely energy sources, chemical and nuclear, for powering SDI directed-energy weapons during the alert and burst modes. The choice between chemical and nuclear space power systems depends in large part on the total duration during which power must be provided. Complete study findings, conclusions, and eight recommendations are reported.

Gavin, Joseph G., Jr.↗

Cockpit display of hazardous weather information

Information transfer and display issues associated with the dissemination of hazardous-weather warnings are studied in the context of wind-shear alerts. Operational and developmental wind-shear detection systems are briefly reviewed. The July 11, 1988 microburst events observed as part of the Denver TDWR operational evaluation are analyzed in terms of information transfer and the effectiveness of the microburst alerts. Information transfer, message content, and display issues associated with microburst alerts generated from ground-based sources (Doppler radars, LLWAS, and PIREPS) are evaluated by means of pilot opinion surveys and part-task simulator studies.

Hansman, R. John, Jr.↗

Cockpit display of hazardous weather information

Information transfer and display issues associated with the dissemination of hazardous weather warnings are studied in the context of windshear alerts. Operational and developmental windshear detection systems are briefly reviewed. The July 11, 1988 microburst events observed as part of the Denver Terminal Doppler Weather Radar (TDWR) operational evaluation are analyzed in terms of information transfer and the effectiveness of the microburst alerts. Information transfer, message content and display issues associated with microburst alerts generated from ground based sources are evaluated by means of pilot opinion surveys and part task simulator studies.

Hansman, R. John, Jr.↗

A spatial disorientation predictor device to enhance pilot situational awareness regarding aircraft attitude

An effort was initiated at the Armstrong Aerospace Medical Research Laboratory (AAMRL) to investigate the improvement of the situational awareness of a pilot with respect to his aircraft's spatial orientation. The end product of this study is a device to alert a pilot to potentially disorienting situations. Much like a ground collision avoidance system (GCAS) is used in fighter aircraft to alert the pilot to 'pull up' when dangerous flight paths are predicted, this device warns the pilot to put a higher priority on attention to the orientation instrument. A Kalman filter was developed which estimates the pilot's perceived position and orientation. The input to the Kalman filter consists of two classes of data. The first class of data consists of noise parameters (indicating parameter uncertainty), conflict signals (e.g. vestibular and kinesthetic signal disagreement), and some nonlinear effects. The Kalman filter's perceived estimates are now the sum of both Class 1 data (good information) and Class 2 data (distorted information). When the estimated perceived position or orientation is significantly different from the actual position or orientation, the pilot is alerted.

Chelette, T. L.↗

Status of Sundstrand research

Wind shear detection status is presented in the form of view-graphs. The following subject areas are covered: second generation detection (Q-bias, gamma bias, temperature biases, maneuvering flight modulation, and altitude modulation); third generation wind shear detection (use wind shear computation to augment flight path and terrain alerts, modulation of alert thresholds based on wind/terrain data base, incorporate wind shear/terrain alert enhancements from predictive sensor data); and future research and development.

Bateman, Don↗

An investigation of air transportation technology at the Massachusetts Institute of Technology, 1990-1991

Brief summaries are given of research activities at the Massachusetts Institute of Technology (MIT) under the sponsorship of the FAA/NASA Joint University Program. Topics covered include hazard assessment and cockpit presentation issues for microburst alerting systems; the situational awareness effect of automated air traffic control (ATC) datalink clearance amendments; a graphical simulation system for adaptive, automated approach spacing; an expert system for temporal planning with application to runway configuration management; deterministic multi-zone ice accretion modeling; alert generation and cockpit presentation for an integrated microburst alerting system; and passive infrared ice detection for helicopter applications.

Simpson, Robert W.↗

Acquisition and use of Orlando, Florida and Continental Airbus radar flight test data

Westinghouse is developing a lookdown pulse Doppler radar for production as the sensor and processor of a forward looking hazardous windshear detection and avoidance system. A data collection prototype of that product was ready for flight testing in Orlando to encounter low level windshear in corroboration with the FAA-Terminal Doppler Weather Radar (TDWR). Airborne real-time processing and display of the hazard factor were demonstrated with TDWR facilitated intercepts and penetrations of over 80 microbursts in a three day period, including microbursts with hazard factors in excess of .16 (with 500 ft. PIREP altitude loss) and the hazard factor display at 6 n.mi. of a visually transparent ('dry') microburst with TDWR corroborated outflow reflectivities of +5 dBz. Range gated Doppler spectrum data was recorded for subsequent development and refinement of hazard factor detection and urban clutter rejection algorithms. Following Orlando, the data collection radar was supplemental type certified for in revenue service on a Continental Airlines Airbus in an automatic and non-interferring basis with its ARINC 708 radar to allow Westinghouse to confirm its understanding of commercial aircraft installation, interface realities, and urban airport clutter. A number of software upgrades, all of which were verified at the Receiver-Transmitter-Processor (RTP) hardware bench with Orlando microburst data to produce desired advanced warning hazard factor detection, included some preliminary loads with automatic (sliding window average hazard factor) detection and annunciation recording. The current (14-APR-92) configured software is free from false and/or nuisance alerts (CAUTIONS, WARNINGS, etc.) for all take-off and landing approaches, under 2500 ft. altitude to weight-on-wheels, into all encountered airports, including Newark (NJ), LAX, Denver, Houston, Cleveland, etc. Using the Orlando data collected on hazardous microbursts, Westinghouse has developed a lookdown pulse Doppler radar product with signal and data processing algorithms which detect realistic microburst hazards and has demonstrated those algorithms produce no false alerts (or nuisance alerts) in urban airport ground moving vehicle (GMTI) and/or clutter environments.

Eide, Michael C.↗

Brain wave correlates of attentional states: Event related potentials and quantitative EEG analysis during performance of cognitive and perceptual tasks

The increased use of automation in the cockpits of commercial planes has dramatically decreased the workload requirements of pilots, enabling them to function more efficiently and with a higher degree of safety. Unfortunately, advances in technology have led to an unexpected problem: the decreased demands on pilots have increased the probability of inducing 'hazardous states of awareness.' A hazardous state of awareness is defined as a decreased level of alertness or arousal which makes an individual less capable of reacting to unique or emergency types of situations. These states tend to be induced when an individual is not actively processing information. Under such conditions a person is likely to let his/her mind wander, either to internal states or to irrelevant external conditions. As a result, they are less capable of reacting quickly to emergency situations. Since emergencies are relatively rare, and since the high automated cockpit requires progressively decreasing levels of engagement, the probability of being seduced into a lowered state of awareness is increasing. This further decreases the readiness of the pilot to react to unique circumstances such as system failures. The HEM Lab at NASA-Langley Research Center has been studying how these states of awareness are induced and what the physiological correlates of these different states are. Specifically, they have been interested in studying electroencephalographic (EEG) measures of different states of alertness to determine if such states can be identified and, hopefully, avoided. The project worked on this summer involved analyzing the EEG and the event related potentials (ERP) data collected while subjects performed under two conditions. Each condition required subjects to perform a relatively boring vigilance task. The purpose of using these tasks was to induce a decreased state of awareness while still requiring the subject to process information. Each task involved identifying an infrequently presented target stimulus. In addition to the task requirements, irrelevant tones were presented in the background. Research has shown that even though these stimuli are not attended, ERP's to them can still be elicited. The amplitude of the ERP waves has been shown to change as a function of a person's level of alertness. ERP's were also collected and analyzed for the target stimuli for each task. Brain maps were produced based on the ERP voltages for the different stimuli. In addition to the ERP's, a quantitative EEG (QEEG) was performed on the data using a fast Fourier technique to produce a power spectral analysis of the EEG. This analysis was conducted on the continuous EEG while the subjects were performing the tasks. Finally, a QEEG was performed on periods during the task when subjects indicated that they were in an altered state of awareness. During the tasks, subjects were asked to indicate by pressing a button when they realized their level of task awareness had changed. EEG epochs were collected for times just before and just after subjects made this reponse. The purpose of this final analysis was to determine whether or not subjective indices of level of awareness could be correlated with different patterns of EEG.

Freeman, Frederick G.↗

Certification methodology applied to the NASA experimental radar system

The objective of the research is to apply selected FAA certification techniques to the NASA experimental wind shear radar system. Although there is no intent to certify the NASA system, the procedures developed may prove useful to manufacturers that plan to undergo the certification process. The certification methodology for forward-looking wind shear detection radars will require estimation of system performance in several FAA-specified microburst/clutter scenarios as well as the estimation of probabilities of missed and false hazard alerts under general operational conditions. Because of the near-impossibility of obtaining these results experimentally, analytical and simulation approaches must be used. Hazard detection algorithms were developed that derived predictive estimates of aircraft hazard from basic radar measurements of weather reflectivity and radial wind velocity. These algorithms were designed to prevent false alarms due to ground clutter while providing accurate predictions of hazard to the aircraft due to weather. A method of calculation of the probability of missed and false hazard alerts has been developed that takes into account the effect of the various algorithms used in the system and provides estimates of the probability of missed and false alerts per microburst encounter under weather conditions found at Denver, Kansas City, and Orlando. Simulation techniques have been developed that permit the proper merging of radar ground clutter data (obtained from flight tests) with simulated microburst data (obtained from microburst models) to estimate system performance using the microburst/clutter scenarios defined by the FAA.

Britt, Charles L.↗