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Machine Learning Algorithms for Aerosol and Cloud Detection Using CATS on the ISS

Clouds and aerosols are one of the largest uncertainties in understanding and forecasting the Earth’s changing climate system. The type and height of aerosols are important factors in determining the top-of-atmosphere (TOA) radiation budget, either direct reflection of solar radiation back to space and/or absorption of solar radiation. In addition to their impact on the Earth’s climate system, aerosols near the surface from wildfires, man-made pollution events, and dust storms are hazardous to human health. The phase and height of clouds also play a critical role in determining the role of clouds in the Earth’s climate system. Cirrus clouds in the upper troposphere can induce a significant daytime TOA warming effect, while liquid water clouds near the surface cause a large corresponding cooling effect. Lidar measurements provide accurate vertically resolved information about clouds and aerosols, including complex multi-layer scenes where passive sensors are challenged and at night, when passive sensors are unable to measure cloud and aerosol properties. The Cloud-Aerosol Transport System (CATS) is a lidar instrument that operated for 33 months on the International Space Station (ISS) at the 1064 nm wavelength to measure attenuated total backscatter and depolarization ratio. These fundamental measurements are used to derive “vertical feature mask” cloud and aerosol products, including layer top/base heights, layer geometrical thickness, aerosol type, and cloud phase. While space-based lidar systems like CATS provide cloud and aerosol vertical distributions that improve our understanding of the climate system, averaging of the daytime data from these sensors is required, at the expense of spatial resolution, to improve the daytime signal-to noise (SNR) and thus atmospheric layer detection. This presentation shows results from machine learning (ML) techniques that, when applied to CATS data: 1. improve the 1064 nm SNR 2. enable detection of atmospheric features during daytime with a horizontal resolution of 350 m or 5 km (compared to the 60 km required for standard CATS data products) 3. increase the number of atmospheric layers detected in the CATS data. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination, cloud phase, and aerosol typing compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime. The ML tools described in this paper can facilitate the development of smaller, low-cost lidar systems in the future and enable real-time accessibility of lidar data products from future lidar systems for monitoring and forecasting of hazardous events.

John Yorks↗

The Asteroid Impact and Deflection Assessment Mission and its Potential Contributions to Human Exploration of Asteroids

The joint ESA and NASA Asteroid Impact and Deflection Assessment (AIDA) mission will directly address aspects of NASA's Asteroid Initiative and will contribute to future human exploration. The NASA Asteroid Initiative is comprised of two major components: the Grand Challenge and the Asteroid Mission. The first component, the Grand Challenge, focuses on protecting Earth's population from asteroid impacts by detecting potentially hazardous objects with enough warning time to either prevent them from impacting the planet, or to implement civil defense procedures. The Asteroid Mission, involves sending astronauts to study and sample a near-Earth asteroid (NEA) prior to conducting exploration missions of the Martian system, which includes Phobos and Deimos. AIDA's primary objective is to demonstrate a kinetic impact deflection and characterize the binary NEA Didymos. The science and technical data obtained from AIDA will aid in the planning of future human exploration missions to NEAs and other small bodies. The dual robotic missions of AIDA, ESA's Asteroid Impact Monitor (AIM) and NASA's Double Asteroid Redirection Test (DART), will provide a great deal of technical and engineering data on spacecraft operations for future human space exploration while conducting in-depth scientific examinations of the binary target Didymos both prior to and after the kinetic impact demonstration. The knowledge gained from this mission will help identify asteroidal physical properties in order to maximize operational efficiency and reduce mission risk for future small body missions. The AIDA data will help fill crucial strategic knowledge gaps concerning asteroid physical characteristics that are relevant for human exploration considerations at similar small body destinations.

Abell, Paul A.↗

Robotic Missions to Small Bodies and Their Potential Contributions to Human Exploration and Planetary Defense

Introduction: Robotic missions to small bodies will directly address aspects of NASA's Asteroid Initiative and will contribute to future human exploration and planetary defense. The NASA Asteroid Initiative is comprised of two major components: the Grand Challenge and the Asteroid Mission. The first component, the Grand Challenge, focuses on protecting Earth's population from asteroid impacts by detecting potentially hazardous objects with enough warning time to either prevent them from impacting the planet, or to implement civil defense procedures. The Asteroid Mission involves sending astronauts to study and sample a near-Earth asteroid (NEA) prior to conducting exploration missions of the Martian system, which includes Phobos and Deimos. The science and technical data obtained from robotic precursor missions that investigate the surface and interior physical characteristics of an object will help identify the pertinent physical properties that will maximize operational efficiency and reduce mission risk for both robotic assets and crew operating in close proximity to, or at the surface of, a small body. These data will help fill crucial strategic knowledge gaps (SKGs) concerning asteroid physical characteristics that are relevant for human exploration considerations at similar small body destinations. These data can also be applied for gaining an understanding of pertinent small body physical characteristics that would also be beneficial for formulating future impact mitigation procedures. Small Body Strategic Knowledge Gaps: For the past several years NASA has been interested in identifying the key SKGs related to future human destinations. These SKGs highlight the various unknowns and/or data gaps of targets that the science and engineering communities would like to have filled in prior to committing crews to explore the Solar System. An action team from the Small Bodies Assessment Group (SBAG) was formed specifically to identify the small body SKGs under the direction of the Human Exploration and Operations Missions Directorate (HEOMD), given NASA's recent interest in NEAs and the Martian moons as potential human destinations. The action team organized the SKGs into four broad themes: 1) Identify human mission targets; 2) Understand how to work on and interact with the small body surface; 3) Understand the small body environment and its potential risk/benefit to crew, systems, and operational assets; and 4) Understand the small body resource potential. Of these four SKG themes, the first three have significant overlap with planetary defense considerations. The data obtained from investigations of small body physical characteristics under these three themes can be directly applicable to planetary defense initiatives. Conclusions: Missions to investigate small bodies can address small body strategic knowledge gaps and contribute to the overall success for human exploration missions to asteroids and the Martian moons. In addition, such reconnaissance of small bodies can also provide a wealth of information relevant to the science and planetary defense of NEAs.

Abell, Paul A.↗

NGSLR Safety Handbook

NASA's Next Generation Satellite Laser Ranging (NGSLR) station is the prototype for NASA's Satellite Laser Ranging (SLR) systems which will be deployed around the world in the coming decade. The NGSLR system will be an autonomous, photon-counting SLR station with an expected absolute range accuracy of better than one centimeter and a normal point (time-averaged) range precision better than one millimeter. The system provides continuous (weather permitting), 24 hour tracking coverage to an existing constellation of approximately two dozen artificial satellites equipped with passive retroreflector arrays, using pulsed, 532 nm, class IV laser systems. Current details on the approved laser systems can be found in the Appendix 1 of this document. This safety plan addresses the potential hazards to emitted laser radiation, which can occur both inside and outside the shelter. Hazards within the shelter are mitigated through posted warning signs, activated warning lights, procedural controls, personal protective equipment (PPE), laser curtains, beam blocking systems, interlock controls, pre-configured laser control settings, and other controls discussed in this document. Since the NGSLR is a satellite tracking system, laser hazards exist outside the shelter to personnel on the shelter roof and to passing aircraft. Potential exposure to personnel outside the system is mitigated through the use of posted warning signs, access control, procedural controls, a stairwell interlock, beam attenuation/blocking devices, and a radar based aircraft detection system.

satellite laser ranging↗

Demonstration of Lidar Sensors for Precision Safe Landing on Planetary Bodies

Missions to solar system bodies must meet increasingly ambitious objectives requiring highly reliable “precision landing”, and “hazard avoidance” capabilities. To meet these needs, we have developed two lidar sensor systems that can be used individually or in concert depending on the mission requirements. One is Navigation Doppler Lidar (NDL) capable of providing vehicle precision vector velocity and ground-relative altitude and the other is an Imaging Flash Lidar for Terrain Relative Navigation and Hazard Detection and Avoidance. Using both lidar sensors together will enable landing anywhere and under any lighting condition. The NDL performance has been extensively characterized through numerous ground and aircraft flight tests and will be soon demonstrated on two lunar landing missions (mid-2023). The Flash Lidar performance is currently being assessed onboard a drone and will soon be tested on helicopter and fixed-wing aircraft platforms. This paper describes both lidar sensors and their expected operation on landing vehicles.

Precision Landing↗

Distributed Vision Sensing of Small Uncrewed Aircraft Systems in Urban Traffic Corridors

The NASA Advanced Air Mobility mission will enable widespread low altitude passenger travel, cargo delivery, and a variety of public services through the development of Uncrewed Aerial Systems (UAS) operations. Ensuring safe, autonomous operations in densely populated environments requires careful consideration towards hazards including other aircraft, infrastructure, and evolving weather. Small Uncrewed Aerial Systems (SUAS) present a unique hazard to UAS operations as they share airspace and may be readily operated in a non-cooperative fashion. This work investigates distributed sensing of SUAS traversing an air traffic corridor in an urban setting. This work develops a distributed vision detect and track strategy at NASA Langley Research Center. Three nodes, each with at least one global shutter camera, are distributed around a traffic corridor to surveil flight operations for two SUAS performing low altitude flight operations. Each node is equipped with a GPS and cellular modem to enable timestamping and remote control of acquisition. Node one faces a traffic roundabout with buildings in the background and achieves 99% surveillance coverage for two SUAS against building and tree backgrounds at ranges 50 to 130m. The second node points down Langley Boulevard with trees and buildings in the background and achieves 99% coverage at separation distances between 70 and 180m. The analysis for the second node is limited to ranges below 180m due to low contrast against dark, tree backgrounds. Finally, the third node points down Langley Boulevard from another perspective and achieves 99% coverage at ranges 60m to 200m against mostly building with a few sections of trees in the background.

Chester V Dolph↗

Formation and Detection of Planetary Systems

Modern theories of star and planet formation and of the orbital stability of planetary systems are described and used to discuss possible characteristics of undiscovered planetary systems. The most detailed models of planetary growth are based upon observations of planets and smaller bodies within our own Solar System and of young stars and their environments. Terrestrial planets are believed to grow via pairwise accretion until the spacing of planetary orbits becomes large enough that the configuration is stable for the age of the system. Giant planets begin their growth as do terrestrial planets, but they become massive enough that they are able to accumulate substantial amounts of gas before the protoplanetary disk dissipates. These models predict that rocky planets should form in orbit about most single stars. It is uncertain whether or not gas giant planet formation is common, because most protoplanetary disks may dissipate before solid planetary cores can grow large enough to gravitationally trap substantial quantities of gas. A potential hazard to planetary systems is radial decay of planetary orbits resulting from interactions with material within the disk. Planets more massive than Earth have the potential to decay the fastest, and may be able to sweep up smaller planets in their path. The implications of the giant planets found in recent radial velocity searches for the abundances of habitable planets are discussed, and the methods that are being used and planned for detecting and characterizing extrasolar planets are reviewed.

Lissauer, Jack J.↗

Science Writers' Guide to TERRA

The launch of NASA's Terra spacecraft marks a new era of comprehensive monitoring of the Earth's atmosphere, oceans, and continents from a single space-based platform. Data from the five Terra instruments will create continuous, long-term records of the state of the land, oceans, and atmosphere. Together with data from other satellite systems launched by NASA and other countries, Terra will inaugurate a new self-consistent data record that will be gathered over the next 15 years. The science objectives of NASAs Earth Observing System (EOS) program are to provide global observations and scientific understanding of land cover change and global productivity, climate variability and change, natural hazards, and atmospheric ozone. Observations by the Terra instruments will: provide the first global and seasonal measurements of the Earth system, including such critical functions as biological productivity of the land and oceans, snow and ice, surface temperature, clouds, water vapor, and land cover; improve our ability to detect human impacts on the Earth system and climate, identify the "fingerprint" of human activity on climate, and predict climate change by using the new global observations in climate models; help develop technologies for disaster prediction, characterization, and risk reduction from wildfires, volcanoes, floods, and droughts, and start long-term monitoring of global climate change and environmental change.

Source record↗

Optimizing Ventilation Using Low-Cost Sensors to Improve Health, Safety, and Energy Efficiency

Air is the primary carrier of hazards within a space, whether it be hazardous byproducts of laboratory research activities or airborne pathogens. As a result, building ventilation is a primary defense against unseen airborne hazards. Critical laboratory facilities require effective mitigation of exposure to research-related, airborne hazards, providing a proving ground for effective ventilation strategies that optimize safety of occupants and reduce energy use. The heart of smart laboratory building operation is dynamic, analytics-based ventilation, which requires an in-depth intimate knowledge of building environmental conditions achieved through contaminant-detection systems. Unfortunately, currently many contaminant-detection solutions are expensive, elaborate systems that raise barriers for building managers. Through the successful deployment of a novel low-cost, modular sensor technology, we have developed a demand-control ventilation protocol effective in improving safety and reducing energy in critical laboratory environments. In this article, we will highlight best practices and lessons learned through this deployment that can be applied beyond laboratories. This article describes a low-cost sensor to support providing a safe, healthy building environment and reduce energy use through effective and efficient ventilation.

dynamic management of indoor air quality↗

Advancing the Limits of InSAR to Detect Crustal Displacement from Low-Magnitude Earthquakes through Deep Learning

Detecting surface deformation associated with low-magnitude (M w ≤ 5) seismicity using interferometric synthetic aperture radar (InSAR) is challenging due to the subtlety of the signal and the often challenging imaging environments. However, low-magnitude earthquakes are potential precursors to larger seismic events, and thus characterizing the crustal displacement associated with them is crucial for regional seismic hazard assessment. We combine InSAR time-series techniques with a Deep Learning (DL) autoencoder denoiser to detect the magnitude and extent of crustal deformation from the M w = 3.4 Gallina, New Mexico earthquake that occurred on 30 July 2020. Although InSAR alone cannot detect event-related deformation from such a low-magnitude seismic event, application of the DL method reveals maximum displacements as small as (±2.5 mm) in the vicinity of both the fault and earthquake epicenter without prior knowledge of the fault system. This finding improves small-scale displacement discernment with InSAR by an order of magnitude relative to previous studies. We additionally estimate best-fitting fault parameters associated with the observed deformation. The application of the DL technique unlocks the potential for low-magnitude earthquake studies, providing new insights into local fault geometries and potential risks from higher-magnitude earthquakes. This technique also permits low-magnitude event monitoring in areas where seismic networks are sparse, allowing for the possibility of global fault deformation monitoring.

58 GEOSCIENCES↗

HOME - An application of fault-tolerant techniques and system self-testing

Hard Over Monitoring Equipment (HOME) has been designed to complement and enhance the flight safety of a flight research helicopter. HOME is an independent, highly reliable, and fail-safe special purpose computer that monitors the flight control commands issued by the flight control computer of the helicopter. In particular, HOME detects the issuance of a hazardous hard-over command for any of the four flight control axes and transfers the control of the helicopter to the flight safety pilot. The design of HOME incorporates certain reliability and fail-safe enhancement design features, such as triple modular redundancy, majority logic voting, fail-safe dual circuits, independent status monitors, in-flight self-test, and a built-in preflight exerciser. The HOME design and operation is described with special emphasis on the reliability and fail-safe aspects of the design.

Holden, D. G.↗

Precision Landing and Hazard Avoidance Doman

The Precision Landing and Hazard Avoidance (PL&HA) domain addresses the development, integration, testing, and spaceflight infusion of sensing, processing, and GN&C functions critical to the success and safety of future human and robotic exploration missions. PL&HA sensors also have applications to other mission events, such as rendezvous and docking. Autonomous PL&HA builds upon the core GN&C capabilities developed to enable soft, controlled landings on the Moon, Mars, and other solar system bodies. Through the addition of a Terrain Relative Navigation (TRN) function, precision landing within tens of meters of a map-based target is possible. The addition of a 3-D terrain mapping lidar sensor improves the probability of a safe landing via autonomous, real-time Hazard Detection and Avoidance (HDA). PL&HA significantly improves the probability of mission success and enhances access to sites of scientific interest located in challenging terrain. PL&HA can also utilize external navigation aids, such as navigation satellites and surface beacons. Advanced Lidar Sensors High precision ranging, velocimetry, and 3-D terrain mapping Terrain Relative Navigation (TRN) TRN compares onboard reconnaissance data with real-time terrain imaging data to update the S/C position estimate Hazard Detection and Avoidance (HDA) Generates a high-resolution, 3-D terrain map in real-time during the approach trajectory to identify safe landing targets Inertial Navigation During Terminal Descent High precision surface relative sensors enable accurate inertial navigation during terminal descent and a tightly controlled touchdown within meters of the selected safe landing target.

Robertson, Edward A.↗

Sensor Fault Detection in Smart Extraterrestrial Habitats Using Unsupervised Learning

Various types of sensors are needed to monitor the health state of smart deep-space habitats. However, measured data can be affected by sensor faults, which influence the health management system and consequently the decision-making. In this paper, an unsupervised learning approach based on convolutional autoencoders (CAEs) is developed to detect anomalies in temperature and pressure sensors. The proposed method is systematically investigated using a habitat simulator (HabSim). Several illustrative examples are demonstrated in the nominal and hazardous states of the habitat, including micrometeorite impact and fire scenarios. The performance of the proposed method using CAEs is compared with that of existing methods using auto-associative neural networks (AANNs) and variational autoencoders. This comparison is based on typical evaluation metrics, including precision, recall, F1 score, training time, and testing time. The effect of temperature–pressure coupling on the detection performance of CAEs and AANNs is explored by training different data-driven models, including one with temperature sensors, one with pressure sensors, and one with both temperature and pressure sensors. The effect of the number of faulty sensors on the performance of CAEs is studied, as with an increase in the number of faulty sensors, redundant information among the sensors is reduced. The capability of CAEs to change the number of sensors without redesigning the network architecture and retraining the neural network is investigated and demonstrated. The capabilities and limitations of the proposed solution are discussed.

Zixin Wang↗

NASA’s Identified Risks of Adverse Outcomes Due to Inadequate Human Systems Integration Architecture in Human Spaceflight

The NASA Human System Risk Board (HSRB) has the overall responsibility for tracking the evolution of the top ~30 human system risks that it has identified to be associated with human spaceflight. As part of this process, the Board is charged with maintaining a consistent, integrated process to mitigate those risks, and developing evidence-based risk posture recommendations. One of the identified risks is due to inadequate human systems integration architecture (HSIA) and a driving factor of this risk is that given decreasing real-time ground support for execution of complex operations during future exploration missions, there is a possibility of adverse performance outcomes including that crew are unable to adequately respond to unanticipated critical malfunctions or detect safety critical procedural errors. The HSRB uses Directed Acyclic Graphs (DAGs) as a communication tool for describing how astronaut exposure to spaceflight hazards leads to meaningful mission-level health and performance outcomes and as the basis for understanding intermediate causal relationships between risk contributing factors and countermeasures that link hazards to outcomes. The HSIA risk DAG will be presented and described. Historically, critical malfunctions requiring Crew/MCC management occurred at a rate of 1.7 times per year for ISS averaged over the lifetime and 3-4 times per year in the burn in phase for the vehicle. These averages do not include EVA data, which greatly increases the incident rate. Prior experience from the Apollo program showed 10/11 crewed missions experienced significant anomalies where crew relied heavily on MCC expertise in real-time. These failure patterns are in line with those observed in other complex engineered systems (e.g., oil rigs, launch systems, commercial aviation, etc.) It is likely that general malfunction and error rates are > 10% for short duration missions (<30 days), based on past and current spaceflight operations data. Likelihood of adverse outcomes has the potential to increase as crew conduct work with new, complex systems and with less ground support. For Low Earth Orbit missions and Lunar missions less than 30 days, assuming minimal comm delays, disruptions and bandwidth limitations, malfunctions and errors can affect mission objectives and crew health but may be mitigated by ground support. For Lunar missions greater than 30 days and any potential Mars mission malfunctions and errors can have Loss of Crew and Loss of Mission consequences due to reduced ground support (communication delays, constraints and blackouts) for more complex operations, as well as reduced resupply and evacuation options.

Daniel M Buckland↗

Improved Detection Technique for Solvent Rinse Cleanliness Verification

The NASA White Sands Test Facility (WSTF) has an ongoing effort to reduce or eliminate usage of cleaning solvents such as CFC-113 and its replacements. These solvents are used in the final clean and cleanliness verification processes for flight and ground support hardware, especially for oxygen systems where organic contaminants can pose an ignition hazard. For the final cleanliness verification in the standard process, the equivalent of one square foot of surface area of parts is rinsed with the solvent, and the final 100 mL of the rinse is captured. The amount of nonvolatile residue (NVR) in the solvent is determined by weight after the evaporation of the solvent. An improved process of sampling this rinse, developed at WSTF, requires evaporation of less than 2 mL of the solvent to make the cleanliness verification. Small amounts of the solvent are evaporated in a clean stainless steel cup, and the cleanliness of the stainless steel cup is measured using a commercially available surface quality monitor. The effectiveness of this new cleanliness verification technique was compared to the accepted NVR sampling procedures. Testing with known contaminants in solution, such as hydraulic fluid, fluorinated lubricants, and cutting and lubricating oils, was performed to establish a correlation between amount in solution and the process response. This report presents the approach and results and discusses the issues in establishing the surface quality monitor-based cleanliness verification.

Hornung, S. D.↗

Ultraviolet-Absorption Spectroscopic Biofilm Monitor

An ultraviolet-absorption spectrometer system has been developed as a prototype instrument to be used in continuous, real-time monitoring to detect the growth of biofilms. Such monitoring is desirable because biofilms are often harmful. For example, biofilms in potable-water and hydroponic systems act as both sources of pathogenic bacteria that resist biocides and as a mechanism for deterioration (including corrosion) of pipes. Biofilms formed from several types of hazardous bacteria can thrive in both plant-growth solutions and low-nutrient media like distilled water. Biofilms can also form in condensate tanks in air-conditioning systems and in industrial heat exchangers. At present, bacteria in potable-water and plant-growth systems aboard the space shuttle (and previously on the Mir space station) are monitored by culture-plate counting, which entails an incubation period of 24 to 48 hours for each sample. At present, there are no commercially available instruments for continuous monitoring of biofilms in terrestrial or spaceborne settings.

Micheels, Ronald H.↗

2021 Annual Site Environmental Report

This report provides the U.S. Department of Energy (DOE) and the public with information on the level of radioactive and non-radioactive pollutants (if any) that are added to the environment as a result of Princeton Plasma Physics Laboratory’s (PPPL) operations. The results of PPPL’s 2021 environmental surveillance and monitoring program are presented and discussed. The report also summarizes environmental initiatives, assessments, and community involvement programs that were undertaken in 2021. PPPL’s on-site operations were significantly curtailed in 2021 due to the global coronavirus pandemic. PPPL has engaged in fusion energy research since 1951. The Laboratory’s mission is to develop the scientific knowledge and advanced engineering to enable fusion to power the U.S. and the world, and to developing the understanding of plasmas from the nano- to the astrophysical scale. PPPL’s primary experiment, the National Spherical Torus Experiment-Upgrade (NSTX-U) is a collaboration among national laboratories, universities, and national and international research institutions and is a major element in the US Fusion Energy Sciences Program. Its design tests the physics principles of spherical torus (ST) plasmas, playing an important role in the development of smaller, more economical fusion reactors. Due to previous operational issues, NSTX-U did not operate in 2021. PPPL is engaged in a project to replace key NSTX-U components and systems to enable operation of this international fusion user facility. In 2021, PPPL’s radiological environmental monitoring program measured tritium in the air at the NSTX-U Stack and at onsite sampling stations. Using highly sensitive air monitors, PPPL is capable of detecting small changes in the ambient levels of tritium. The operation of an in-stack monitor located on D-site is used to demonstrate compliance with the National Emission Standard for Hazardous Air Pollutants (NESHAPs) regulations. Also included in PPPL’s radiological environmental monitoring program, are water monitoring – ground, surface, and waste waters. PPPL’s radiological monitoring program characterized the background levels of tritium in the environment and those data are presented in this report. Ground water monitoring continued under New Jersey Department of Environmental Protection’s (NJDEP) Site Remediation Program regulations. PPPL monitored for non-radiological contaminants, mainly volatile organic compounds (components of common degreasing solvents). In 2021, PPPL complied with permit limits for surface and sanitary discharges. PPPL was honored with awards for EPEAT-certified electronics purchasing and use of peracetic acid as an alternative water treatment chemical in its non-potable process water systems an NJDEP recycling award.

54 ENVIRONMENTAL SCIENCES↗

Fiber optic and laser sensors X; Proceedings of the Meeting, Boston, MA, Sept. 8-11, 1992

Topics addressed include acoustic and pressure sensors; fiber optic gyros; electric and magnetic field sensors; bend, strain, and temperature sensors; industrial applications of sensors; and processing techniques. Particular attention is given to fiber optic interferometric acoustic sensors for wind tunnel applications, polished coupler and resonator fabrication, second-harmonic detection for rotation sensing in fiber optic gyros, simplified control theory in closed-loop fiber optic gyroscopes, and a Fabry-Perot sensor with digital signal processing for the measurement of magnetostriction. Also discussed are a Bragg fiber laser sensor, commercialization of fiber optic strain gauge systems, thermal ignition in hazardous environments due to stray light from optical fibers, a system for absolute measurements by interferometric sensors, and high-performance interferometric demodulation techniques.

Udd, Eric↗