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NASA NTRS1990

The correction of infrasound signals for upper atmospheric winds

Infrasound waves propagate in the atmosphere by a well known mechanism produced by refraction of the waves, return to earth, and reflection at the surface into the atmosphere for subsequent bounces. A figure illustrates this phenomenon with results from a ray trace model. In this instance three rays are returned to earth from a region centered at about 50 kilometers in altitude and two from a region near 110 kilometers in altitude. The control of the wave refraction is largely dominated by the temperature-height profile and inversions; however, a major influence is also produced by the atmospheric wind profile. Another figure illustrates the considerable ray differences for rays moving in the wind direction (to the right) and in the counter direction (to the left). It obviously can be expected that infrasonic signal amplitudes will be greatly influenced by the winds in the atmosphere. The seasonal variation of the high altitude atmospheric winds is well documented. A third figure illustrates this with average statistics on the observed zonal wind in the region of 50 plus or minus 5 kilometers in altitude. The results are based upon a survey by Webb; Webb terms this parameterization the Stratospheric Circulation Index (SCI). The very strong seasonal variation has the ability to exert a major seasonal influence on infrasonic signals. The purpose here is to obtain a method for the correction of this effect.

Mutschlecner, J. Paul↗

NASA NTRS1984

Design of infrasound-detection system via adaptive LMSTDE algorithm

A proposed solution to an aviation safety problem is based on passive detection of turbulent weather phenomena through their infrasonic emission. This thesis describes a system design that is adequate for detection and bearing evaluation of infrasounds. An array of four sensors, with the appropriate hardware, is used for the detection part. Bearing evaluation is based on estimates of time delays between sensor outputs. The generalized cross correlation (GCC), as the conventional time-delay estimation (TDE) method, is first reviewed. An adaptive TDE approach, using the least mean square (LMS) algorithm, is then discussed. A comparison between the two techniques is made and the advantages of the adaptive approach are listed. The behavior of the GCC, as a Roth processor, is examined for the anticipated signals. It is shown that the Roth processor has the desired effect of sharpening the peak of the correlation function. It is also shown that the LMSTDE technique is an equivalent implementation of the Roth processor in the time domain. A LMSTDE lead-lag model, with a variable stability coefficient and a convergence criterion, is designed.

Khalaf, C. S.↗

NASA NTRS2011

Collaborative Clustering for Sensor Networks

Traditionally, nodes in a sensor network simply collect data and then pass it on to a centralized node that archives, distributes, and possibly analyzes the data. However, analysis at the individual nodes could enable faster detection of anomalies or other interesting events, as well as faster responses such as sending out alerts or increasing the data collection rate. There is an additional opportunity for increased performance if individual nodes can communicate directly with their neighbors. Previously, a method was developed by which machine learning classification algorithms could collaborate to achieve high performance autonomously (without requiring human intervention). This method worked for supervised learning algorithms, in which labeled data is used to train models. The learners collaborated by exchanging labels describing the data. The new advance enables clustering algorithms, which do not use labeled data, to also collaborate. This is achieved by defining a new language for collaboration that uses pair-wise constraints to encode useful information for other learners. These constraints specify that two items must, or cannot, be placed into the same cluster. Previous work has shown that clustering with these constraints (in isolation) already improves performance. In the problem formulation, each learner resides at a different node in the sensor network and makes observations (collects data) independently of the other learners. Each learner clusters its data and then selects a pair of items about which it is uncertain and uses them to query its neighbors. The resulting feedback (a must and cannot constraint from each neighbor) is combined by the learner into a consensus constraint, and it then reclusters its data while incorporating the new constraint. A strategy was also proposed for cleaning the resulting constraint sets, which may contain conflicting constraints; this improves performance significantly. This approach has been applied to collaborative clustering of seismic and infrasonic data collected by the Mount Erebus Volcano Observatory in Antarctica. Previous approaches to distributed clustering cannot readily be applied in a sensor network setting, because they assume that each node has the same view of the data set. A view is the set of features used to represent each object. When a single data set is partitioned across several computational nodes, distributed clustering works; all objects have the same view. But when the data is collected from different locations, using different sensors, a more flexible approach is needed. This approach instead operates in situations where the data collected at each node has a different view (e.g., seismic vs. infrasonic sensors), but they observe the same events. This enables them to exchange information about the likely cluster membership relations between objects, even if they do not use the same features to represent the objects.

Wagstaff. Loro :/↗

NASA NTRS2005

NASA Tech Briefs, September 2005

Topivs include: Diamond-Coated Carbon Nanotubes for Efficient Field Emission; Improved Anode Coatings for Direct Methanol Fuel Cells; Advanced Ablative Insulators and Methods of Making Them; PETIs as High-Temperature Resin-Transfer-Molding Materials; Stable Polyimides for Terrestrial and Space Uses; Low-Density, Aerogel-Filled Thermal-Insulation Tiles; High-Performance Polymers Having Low Melt Viscosities; Nonflammable, Hydrophobic Aerogel Composites for Insulation; Front-Side Microstrip Line Feeding a Raised Antenna Patch; Medium-Frequency Pseudonoise Georadar; Facilitating Navigation Through Large Archives; Program for Weibull Analysis of Fatigue Data; Comprehensive Micromechanics-Analysis Code - Version 4.0; Component-Based Visualization System; Software for Engineering Simulations of a Spacecraft; LabVIEW Interface for PCI-SpaceWire Interface Card; Path Following with Slip Compensation for a Mars Rover; International Space Station Electric Power System Performance Code-SPACE; Software for Automation of Real-Time Agents, Version 2; Software for Optimizing Plans Involving Interdependent Goals; Computing Gravitational Fields of Finite-Sized Bodies; Custom Sky-Image Mosaics from NASA's Information Power Grid; ANTLR Tree Grammar Generator and Extensions; Generic Kalman Filter Software; Alignment Stage for a Cryogenic Dilatometer; Rugged Iris Mechanism; Treatments To Produce Stabilized Aluminum Mirrors for Cryogenic Uses; Making AlNx Tunnel Barriers Using a Low-Energy Nitrogen-Ion Beam; Making Wide-IF SIS Mixers with Suspended Metal-Beam Leads; Sol-Gel Glass Holographic Light-Shaping Diffusers; Automated Counting of Particles To Quantify Cleanliness; Phase Correction for GPS Antenna with Nonunique Phase Center; Compact Infrasonic Windscreen; Broadband External-Cavity Diode Laser; High-Efficiency Solar Cells Using Photonic-Bandgap Materials; Generating Solid Models from Topographical Data; Computationally Lightweight Air-Traffic-Control Simulation; Spool Valve for Switching Air Flows Between Two Beds; Partial Model of Insulator/ Insulator Contact Charging; Asymmetric Electrostatic Radiation Shielding for Spacecraft; and Reusable Hybrid Propellant Modules for Outer-Space Transport.

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