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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↗

NASA NTRS2004

Using software security analysis to verify the secure socket layer (SSL) protocol

nal Aeronautics and Space Administration (NASA) have tens of thousands of networked computer systems and applications. Software Security vulnerabilities present risks such as lost or corrupted data, information the3, and unavailability of critical systems. These risks represent potentially enormous costs to NASA. The NASA Code Q research initiative 'Reducing Software Security Risk (RSSR) Trough an Integrated Approach '' offers, among its capabilities, formal verification of software security properties, through the use of model based verification (MBV) to address software security risks. [1,2,3,4,5,6] MBV is a formal approach to software assurance that combines analysis of software, via abstract models, with technology, such as model checkers, that provide automation of the mechanical portions of the analysis process. This paper will discuss: The need for formal analysis to assure software systems with respect to software and why testing alone cannot provide it. The means by which MBV with a Flexible Modeling Framework (FMF) accomplishes the necessary analysis task. An example of FMF style MBV in the verification of properties over the Secure Socket Layer (SSL) communication protocol as a demonstration.

software↗

NASA NTRS1988

A fiber optic tactical voice/data network based on FDDI

An asynchronous high-speed fiber optic local area network is described that supports ordinary data packet traffic simultaneously with synchronous Tl voice traffic over a common FDDI token ring channel. A voice interface module was developed that parses, buffers, and resynchronizes the voice data to the packet network. The technique is general, however, and can be applied to any deterministic class of networks, including multi-tier backbones. A conventional single token access protocol was employed at the lowest layer, with fixed packet sizes for voice and variable for data. In addition, the higher layer packet data protocols are allowed to operate independently of those for the voice thereby permitting great flexibility in reconfiguring the network. Voice call setup and switching functions were performed external to the network with PABX equipment.

Bergman, L. A.↗

NASA NTRS2018

The Way to the Future Has Already Started: ICAO Aeronautical Telecommunication Network (ATN) Using Internet Protocol Suite (IPS) Standards and Protocol Evolution Update

Millions of people are able to exchange information over phones, computers, tablets and an array of new interconnected devices such as sensors, cameras, home appliances and others are increasingly becoming networked. At the core of this sizeable interconnection is a set of underlying protocols that enable millions of devices to seamlessly talk to each other. Aviation, as many other industries have, utilizes the internet protocol for ground-to-ground network communications and efforts are underway to bring it to the cockpit.In 2015, the International Civil Aviation Organization (ICAO) published the second edition of Document 9896 (Doc 9896) titled: Manual on the Aeronautical Telecommunication Network (ATN) using Internet Protocol Suite (IPS) Standards and Protocol. This manual adopted the Internet protocol version 6 (IPv6) for Internet layer interoperability. Document 9896 defined data communications protocols and services to be used for implementing aeronautical telecommunication network (ATN) using the Internet protocol suite (IPS). The document provided technical specifications that addressed security, network and transport protocols, described applications, supported by ATN/IPS and provided communications guidance. The international aviation community working under the guidance of ICAO initiated work on updates to Doc 9896. Under the ICAO Communication Panel, Working Group Internetworking (WG-I) got this challenging task. Key areas of work for WG-I are related to ATN/IPS Security and ANT/IPS Mobility. Two sub-groups have been assembled to work on these elements. The ICAO anticipates the release of updated Doc 9896 in 2020. Additional ATN/IPS standardization efforts include Radio Technical Commission for Aeronautics Special Committee 223 (RTCA SC-223) IPS profile development, Airlines Electronic Engineering Committee (AEEC) A658 Roadmap of IPS future activities and European Organization for Civil Aviation Equipment (EUROCAE) WG-108 development of guidance documentation.This paper describes ICAO WG-I approach to update key areas of the document in closed coordination with AEEC, RTCA and EUROCAE committees supporting the development of ATN/IPS. Additionally, the paper will explore WG-I mobility solutions under investigation, security developments, IPv6 addressing challenges and other proposed updates. Finally, as new operational expectations such as Free Route and Remote Piloted Aircraft System integration are currently pushing the boundaries set by old operational concepts, the paper identifies the emerging new challenges that will drive the ATN/IPS development beyond 2020. They are related to future voice utilization, System Wide Information Management and Remotely Piloted Aircraft System deployment. IPS systems are seen as the only way forward.

Apaza, Rafael↗

NASA NTRS1984

Investigation of mesoscale pre-convective forcing mechanisms

The installation and testing of a numerical mesoscale boundary layer model is discussed. A data analysis is first made using the rawinsonde network which shows a strong baroclinic zone developing in the region where convection was initiated. The observed wind field shows an easterly component developing in opposition to the synoptic flow producing convergence. The numerical boundary layer model is used to diagnose the physical development of the thermal and flow fields. Two physical mechanisms are examined; topography and cloud shading. The results shows that while heated sloping topography alone does create a baroclinic zone and convergence values, cloud shading is a stronger mechanism for producing a thermal field representative of observed conditions

Mcnider, R. T.↗

NASA NTRS2002

MPL-Net Measurements of Aerosol and Cloud Vertical Distributions at Co-Located AERONET Sites

In the early 1990s, the first small, eye-safe, and autonomous lidar system was developed, the Micropulse Lidar (MPL). The MPL acquires signal profiles of backscattered laser light from aerosols and clouds. The signals are analyzed to yield multiple layer heights, optical depths of each layer, average extinction-to-backscatter ratios for each layer, and profiles of extinction in each layer. In 2000, several MPL sites were organized into a coordinated network, called MPL-Net, by the Cloud and Aerosol Lidar Group at NASA Goddard Space Flight Center (GSFC) using funding provided by the NASA Earth Observing System. tn addition to the funding provided by NASA EOS, the NASA CERES Ground Validation Group supplied four MPL systems to the project, and the NASA TOMS group contributed their MPL for work at GSFC. The Atmospheric Radiation Measurement Program (ARM) also agreed to make their data available to the MPL-Net project for processing. In addition to the initial NASA and ARM operated sites, several other independent research groups have also expressed interest in joining the network using their own instruments. Finally, a limited amount of EOS funding was set aside to participate in various field experiments each year. The NASA Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) project also provides funds to deploy their MPL during ocean research cruises. All together, the MPL-Net project has participated in four major field experiments since 2000. Most MPL-Net sites and field experiment locations are also co-located with sunphotometers in the NASA Aerosol Robotic Network. (AERONET). Therefore, at these locations data is collected on both aerosol and cloud vertical structure as well as column optical depth and sky radiance. Real-time data products are now available from most MPL-Net sites. Our real-time products are generated at times of AERONET aerosol optical depth (AOD) measurements. The AERONET AOD is used as input to our processing routines, which calculate the aerosol layer top height and extinction profile, and our MPL calibration value. A variety of other data products are available or under development. We present an overview of the MPL-Net project and discuss data products useful to the AERONET community. Results from several sites and field experiments will be presented.

Welton, Ellsworth J.↗

NASA NTRS2006

Profiler Support for Operations at Space Launch Ranges

Accurate vertical wind profiles are essential to successful launch or landing. Wind changes can make it impossible to fly a desired trajectory or avoid dangerous vehicle loads, possibly resulting in loss of mission. Balloons take an hour to generate a profile up to 20 km, but major wind changes can occur in 20 minutes. Wind profilers have the temporal response to detect such last minute hazards. They also measure the winds directly overhead while balloons blow downwind. At the Eastern Range (ER), altitudes from 2 to 20 km are sampled by a 50-MHz profiler every 4 minutes. The surface to 3 km is sampled by five 915-MHz profilers every 15 minutes. The Range Safety office assesses the risk of potential toxic chemical dispersion. They use observational data and model output to estimate the spatial extent and concentration of substances dispersed within the boundary layer. The ER uses 915-MHz profilers as both a real time observation system and as input to dispersion models. The WR has similar plans. Wind profilers support engineering analyses for the Space Shuttle. The 50-IVl11z profiler was used recently to analyze changes in the low frequency wind and low vertical wavenumber content of wind profiles in the 3 to 15 km region of the atmosphere. The 915-MHz profiler network was used to study temporal wind change within the boundary layer.

Merceret, Francis↗

NASA NTRS2016

In-Space Networking on NASA's SCAN Testbed

The NASA Space Communications and Navigation (SCaN) Testbed, an external payload onboard the International Space Station, is equipped with three software defined radios and a flight computer for supporting in-space communication research. New technologies being studied using the SCaN Testbed include advanced networking, coding, and modulation protocols designed to support the transition of NASAs mission systems from primarily point to point data links and preplanned routes towards adaptive, autonomous internetworked operations needed to meet future mission objectives. Networking protocols implemented on the SCaN Testbed include the Advanced Orbiting Systems (AOS) link-layer protocol, Consultative Committee for Space Data Systems (CCSDS) Encapsulation Packets, Internet Protocol (IP), Space Link Extension (SLE), CCSDS File Delivery Protocol (CFDP), and Delay-Tolerant Networking (DTN) protocols including the Bundle Protocol (BP) and Licklider Transmission Protocol (LTP). The SCaN Testbed end-to-end system provides three S-band data links and one Ka-band data link to exchange space and ground data through NASAs Tracking Data Relay Satellite System or a direct-to-ground link to ground stations. The multiple data links and nodes provide several upgradable elements on both the space and ground systems. This paper will provide a general description of the testbeds system design and capabilities, discuss in detail the design and lessons learned in the implementation of the network protocols, and describe future plans for continuing research to meet the communication needs for evolving global space systems.

space networks↗

NASA NTRS1991

A simple method to derive bounds on the size and to train multilayer neural networks

A new derivation is presented for the bounds on the size of a multilayer neural network to exactly implement an arbitrary training set; namely, the training set can be implemented with zero error with two layers and with the number of the hidden-layer neurons equal to no.1 is greater than p - 1. The derivation does not require the separation of the input space by particular hyperplanes, as in previous derivations. The weights for the hidden layer can be chosen almost arbitrarily, and the weights for the output layer can be found by solving no.1 + 1 linear equations. The method presented exactly solves (M), the multilayer neural network training problem, for any arbitrary training set.

Sartori, Michael A.↗

NASA NTRS1993

Conjugate-Gradient Neural Networks in Classification of Multisource and Very-High-Dimensional Remote Sensing Data

Application of neural networks to classification of remote sensing data is discussed. Conventional two-layer backpropagation is found to give good results in classification of remote sensing data but is not efficient in training. A more efficient variant, based on conjugate-gradient optimization, is used for classification of multisource remote sensing and geographic data and very-high-dimensional data. The conjugate-gradient neural networks give excellent performance in classification of multisource data, but do not compare as well with statistical methods in classification of very-high-dimentional data.

Benediktsson, J. A.↗

NASA NTRS1989

Automatic voice recognition using traditional and artificial neural network approaches

The main objective of this research is to develop an algorithm for isolated-word recognition. This research is focused on digital signal analysis rather than linguistic analysis of speech. Features extraction is carried out by applying a Linear Predictive Coding (LPC) algorithm with order of 10. Continuous-word and speaker independent recognition will be considered in future study after accomplishing this isolated word research. To examine the similarity between the reference and the training sets, two approaches are explored. The first is implementing traditional pattern recognition techniques where a dynamic time warping algorithm is applied to align the two sets and calculate the probability of matching by measuring the Euclidean distance between the two sets. The second is implementing a backpropagation artificial neural net model with three layers as the pattern classifier. The adaptation rule implemented in this network is the generalized least mean square (LMS) rule. The first approach has been accomplished. A vocabulary of 50 words was selected and tested. The accuracy of the algorithm was found to be around 85 percent. The second approach is in progress at the present time.

Botros, Nazeih M.↗

NASA NTRS2004

Space Network Devices Developed

The NASA Glenn Research Center through a contract with Spectrum Astro, Inc., has been developing space network hardware as an enabling technology using open systems interconnect (OSI) standards for space-based communications applications. The OSI standard is a well-recognized layered reference model that specifies how data should be sent node to node in a communications network. Because of this research and technology development, a space-qualifiable Ethernet-based network interface card (similar to the type found in a networked personal computer) and the associated four-port hub were designed and developed to flight specifications. During this research and development, there also have been many lessons learned for determining approaches for migrating existing spacecraft architectures to an OSI-network-based platform. Industry has recognized the benefits of targeting hardware developed around OSI standards such as Transmission Control Protocol/Internet Protocol (TCP/IP) or similar protocols for use in future generations of space communication systems. Some of these tangible benefits include overall reductions in mission schedule and cost and in system complexity. This development also brings us a step closer to the realization of a principal investigator on a terrestrial Internet site being able to interact with space platform assets in near real time. To develop this hardware, Spectrum Astro first conducted a technology analysis of alternatives study. For this analysis, they looked at the features of three protocol specifications: Ethernet (IEEE 802.3), Firewire (IEEE 1394), and Spacewire (IEEE 1355). A thorough analysis was performed on the basis of criteria such as current protocol performance and suitability for future space applications. Spectrum Astro also projected future influences such as cost, hardware and software availability, throughput performance, and integration procedures for current and transitive space architectures. After a thorough analysis, Ethernet was chosen because it was seen as the best longer term fit because of the prevalent commercial market; the current and projected availability of hardware, software, and development tools; and the ease of architecture integration.

Jones, Robert E.↗

NASA NTRS1986

The crack layer approach to toughness characterization in steel

In a study of the laws of crack propagation and toughness characterization, it is feasible to employ two alternative approaches, including the fracture mechanics approach and the material science approach. The crack layer (CL) theory discussed by Khandogin and Chudnovsky (1978) and Chudnovsky (1980) considers the crack together with the surrounding defects as one system which has several degrees of freedom. It is pointed out that the CL theory defines the relationship between the parameters of fracture mechanics and the characteristics of microstructural changes which are the subject of material science. Experiments are described, taking into account a toughness characterization test and microscopic studies. Attention is given to a phenomenological study of toughness characterization, the morphology of crack layer, and the evaluation of energy stored in the dislocation network.

Bessendorff, M.↗

NASA NTRS2004

The Effect of Impacts on the Early Martian Climate

The first images returned by the Mariner 7 spacecraft of the Martian surface showed a landscape heavily scared by impacts. Mariner 9 imaging revealed geomorphic features including valley networks and outflow channels that suggest liquid water once flowed at the surface of Mars. Further evidence for water erosion and surface modification has come from the Viking Spacecraft, Mars Pathfinder, Mars Global Surveyor's (MGS) Mars Orbiter Camera (MOC), and Mars Odyssey's THEMIS instrument. In addition to network channels, this evidence includes apparent paleolake beds, fluvial fans and sedimentary layers. The estimated erosion rates necessary to explain the observed surface morphologies present a conundrum. The rates of erosion appear to be highest when the early sun was fainter and only 75% as luminous as it is today. All of this evidence points to a very different climate than what exists on Mars today. The most popular paradigm for the formation of the valley networks is that Mars had at one time a warm (T average > 273), wetter and stable climate. Possible warming mechanisms have included increased surface pressures, carbon dioxide clouds and trace greenhouse gasses. Yet to date climate models have not been able to produce a continuously warm and wet early Mars. The rates of erosion appear to correlate with the rate at which Mars was impacted thus an alternate possibility is transient warm and wet conditions initiated by large impacts. It is widely accepted that even relatively small impacts (approx. 10 km) have altered the past climate of Earth to such an extent as to cause mass extinctions. Mars has been impacted with a similar distribution of objects. The impact record at Mars is preserved in the abundance of observable craters on it surface. Impact induced climate change must have occurred on Mars.

Colaprete, A.↗

NASA NTRS2000

Experimental Verification of Electric Drive Technologies Based on Artificial Intelligence Tools

In this report, a fully integrated prototype of a flight servo control system is successfully developed and implemented using brushless dc motors. The control system is developed by the fuzzy logic theory, and implemented with a multilayer neural network. First, a neural network-based architecture is introduced for fuzzy logic control. The characteristic rules and their membership functions of fuzzy systems are represented as the processing nodes in the neural network structure. The network structure and the parameter learning are performed simultaneously and online in the fuzzy-neural network system. The structure learning is based on the partition of input space. The parameter learning is based on the supervised gradient decent method, using a delta adaptation law. Using experimental setup, the performance of the proposed control system is evaluated under various operating conditions. Test results are presented and discussed in the report. The proposed learning control system has several advantages, namely, simple structure and learning capability, robustness and high tracking performance and few nodes at hidden layers. In comparison with the PI controller, the proposed fuzzy-neural network system can yield a better dynamic performance with shorter settling time, and without overshoot. Experimental results have shown that the proposed control system is adaptive and robust in responding to a wide range of operating conditions. In summary, the goal of this study is to design and implement-advanced servosystems to actuate control surfaces for flight vehicles, namely, aircraft and helicopters, missiles and interceptors, and mini- and micro-air vehicles.

Rubaai, Ahmed↗

NASA NTRS1981

Dynamic study of the upper Sao Francisco River and the Tres Marias reservoir using MSS/LANDSAT images

The use of LANDSAT multispectral ban scanner imagery to verify the relationship between the behavior of the Tres Marias reservoir and the dynamics of the Sao Francisco River supply basin is described. The dispersion of suspended sediments and their concentration in the surface layers of the water are considered. A five year survey of the region during both dry and rainy seasons was performed. The drainage network was analyzed based on the patterns of dessication, water rises and soil use in the supply basin. Surface layers of the reservoir were tabulated as a function of the levels of gray in the imagery. In situ observations of water depth and reflectance were performed. Ground truth and LANDSAT data were correlated to determine the factors affecting the dynamics of the supply basin.

Dejesusparada, N.↗

NASA NTRS1983

Networking DEC and IBM computers

Local Area Networking of DEC and IBM computers within the structure of the ISO-OSI Seven Layer Reference Model at a raw signaling speed of 1 Mops or greater are discussed. After an introduction to the ISO-OSI Reference Model nd the IEEE-802 Draft Standard for Local Area Networks (LANs), there follows a detailed discussion and comparison of the products available from a variety of manufactures to perform this networking task. A summary of these products is presented in a table.

Mish, W. H.↗

NASA NTRS1993

Application of neural network to remote sensing of soil moisture using theoretical polarimetric backscattering coefficients

This paper investigates the potential application of neural network to inversion of soil moisture using polarimetric remote sensing data. The neural network used for the inversion of soil parameters is multi-layer perceptron trained with the back-propagation algorithm. The training data include the polarimetric backscattering coefficients obtained from theoretical surface scattering models together with an assumed nominal range of soil parameters which are comprised of the soil permittivity and surface roughness parameters. Soil permittivity is calculated from the soil moisture and the assumed soil texture based on an empirical formula at C-, L-, and P-bands. The rough surface parameters for the soil surface, which is described by the Gaussian random process, are the root-mean-square (rms) height and correlation length. For the rough surface scattering, small perturbation method is used for the L-band frequency, and Kirchhoff approximation is used for the C-band frequency to obtain the corresponding backscattering coefficients. During the training, the backscattering coefficients are the inputs to the neural net and the output from the net are compared with the desired soil parameters to adjust the interconnecting weights. The process is repeated for each input-output data entry and then for the entire training data until convergence is reached. After training, the backscattering coefficients are applied to the trained neural net to retrieve the soil parameters which are compared with the desired soil parameters to verify the effectiveness of this technique. Several cases are examined. First, for simplicity, the correlation length and rms height of the soil surface are fixed while soil moisture is varied. Soil moisture obtained using the neural networks with either L-band or C-band backscattering coefficients for the HH and VV polarizations as inputs is in good agreement with the desired soil moisture. The neural net output matches the desired output for the soil moisture range of 16 to 60 percent for the C-band case. The next case investigated is to vary both soil moisture and rms height while keeping the correlation length fixed. For this case, C-band backscattering coefficients are not sufficient for retrieving two parameters because the Kirchhoff approximation gives the same HH and VV backscattering coefficients. Therefore, the backscattering coefficients at two different frequency bands are necessary to find both the soil moisture and rms height. Finally, the neural nets are also applied to simultaneously invert soil moisture, rms height, and correlation length. Overall, the soil moisture retrieved from the neural network agrees very well with the desired soil moisture. This suggests that the neural network shows potential for retrieval of soil parameters from remote sensing data.

Wang, L.↗