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Lightweight composite-material (e.g., graphite fiber/epoxy matrix) cocured sandwich panels with eggcratelike cores developed for use as principal components of optical benches and other structures that support precise optical instruments. Structures offer greater thermal and mechanical stability. Advantages include easier fabrication and better mechanical properties.
The Principal Component Spectral Analysis and the Quasi-steady Three-dimensional Histogram techniques provide the means to describe the microgravity acceleration environment of an entire mission on a single plot. This allows a straight forward comparison of the microgravity environment between missions, carriers, and conditions. As shown in this report, the PCSA and QTH techniques bring both the range and median of the microgravity environment onto a single page for an entire mission or another time period or condition of interest. These single pages may then be used to compare similar analyses of other missions, time periods or conditions. The PCSA plot is based on the frequency distribution of the vibrational energy and is normally used for an acceleration data set containing frequencies above the lowest natural frequencies of the vehicle. The QTH plot is based on the direction and magnitude of the acceleration and is normally used for acceleration data sets with frequency content less than 0.1 Hz. Various operating conditions are made evident by using PCSA and QTH plots. Equipment operating either full or part time with sufficient magnitude to be considered a disturbance is very evident as well as equipment contributing to the background acceleration environment. A source's magnitude and/or frequency variability is also evident by the source's appearance on a PCSA plot. The PCSA and QTH techniques are valuable tools for extracting useful information from acceleration data taken over large spans of time. This report shows that these techniques provide a tool for comparison between different sets of microgravity acceleration data, for example different missions, different activities within a mission, and/or different attitudes within a mission. These techniques, as well as others, may be employed in order to derive useful information from acceleration data.
The tectonic response of the Taos Plateau volcanic field in the southern San Luis basin to the late stage extensional environment of the Rio Grande rift was investigated using paleomagnetic techniques. Sixty-two sites (533 samples) of Pliocene volcanic units were collected covering four major rock types with ages of 4.7 to 1.8 Ma. Twenty-two of these sites were from stratigraphic sections of the lower, middle and upper Servilleta Basalt collected in the Rio Grande gorge at two locations 19 km apart. Flows from the lower and middle members in the southern gorge record reversed polarities, while those in Garapata Canyon are normal with an excursion event in the middle of the sequence. The uppermost flows of the upper member at both sites display normal directions. Although these sections correlate chemically, they seem to represent different magnetic time periods during the Gilbert Reversed-Polarity Chiron. Alternating field demagnetization, aided by principal component analysis, yields 55 sites with stable directions representing both normal and reversed polarities, and five sites indicating transitional fields. Mean direction of the normal and inverted reversed sites is I=49.3 deg. and D=356.7 deg. (alpha(sub 95)=3.6 deg). Angular dispersion of the virtual geomagnetic poles is 16.3 deg, which is consistent with paleosecular variation model G, fit to data from the past 5 m.y. Comparison with the expected direction indicates no azimuthal rotation of the Taos Plateau volcanic field; inclination flattening for the southern part of the plateau is 8.3 deg +/- 5.3 deg. Previous paleomagnelic data indicate 10 deg- 15 deg counterclockwise rotation of die Espanola block to the south over the past 5 m.y. The data suggest the Taos Plateau volcanic field, showing no rotation and some flattening in the south and east, has acted as a stable buttress and has been downwarped by overriding of the southeastern end of the plateau by the Picuris Mountains, which make up the northern corner of the counterclockwise rotating Espanola block.
This paper reviews the activities at OKSI related to imaging spectroscopy presenting current and future applications of the technology. The authors discuss the development of several systems including hardware, signal processing, data classification algorithms and benchmarking techniques to determine algorithm performance. Signal processing for each application is tailored by incorporating the phenomenology appropriate to the process, into the algorithms. Pixel signatures are classified using techniques such as principal component analyses, generalized eigenvalue analysis and novel very fast neural network methods. The major hyperspectral imaging systems developed at OKSI include the Intelligent Missile Seeker (IMS) demonstration project for real-time target/decoy discrimination, and the Thermal InfraRed Imaging Spectrometer (TIRIS) for detection and tracking of toxic plumes and gases. In addition, systems for applications in medical photodiagnosis, manufacturing technology, and for crop monitoring are also under development.
This paper presents the results of applying two different types of neural networks in two different approaches to the sensor validation problem. The first approach uses a functional approximation neural network as part of a nonlinear observer in a model-based approach to analytical redundancy. The second approach uses an auto-associative neural network to perform nonlinear principal component analysis on a set of redundant sensors to provide an estimate for a single failed sensor. The approaches are demonstrated using a nonlinear simulation of a turbofan engine. The fault detection and sensor estimation results are presented and the training of the auto-associative neural network to provide sensor estimates is discussed.
This project deals with developing advanced methods for investigating and controlling interior noise in aircraft. The work concentrates on developing and applying the techniques of Near Field Acoustic Holography (NAH) and Principal Component Analysis (PCA) to the aircraft interior noise dynamic problem. This involves investigating the current state of the art, developing new techniques and then applying them to the particular problem being studied. The knowledge gained under the first part of the project was then used to develop and apply new, advanced noise control techniques for reducing interior noise. A new fully active control approach based on the PCA was developed and implemented on a test cylinder. Finally an active-passive approach based on tunable vibration absorbers was to be developed and analytically applied to a range of test structures from simple plates to aircraft fuselages.
The microgravity environment of the NASA Shuttles and Russia's Mir space station have been measured by specially designed accelerometer systems. The need for comparisons between different missions, vehicles, conditions, etc. has been addressed by the two new processes described in this paper. The Principal Component Spectral Analysis (PCSA) and Quasi-steady Three-dimensional Histogram QTH techniques provide the means to describe the microgravity acceleration environment of a long time span of data on a single plot. As described in this paper, the PCSA and QTH techniques allow both the range and the median of the microgravity environment to be represented graphically on a single page. A variety of operating conditions may be made evident by using PCSA or QTH plots. The PCSA plot can help to distinguish between equipment operating full time or part time, as well as show the variability of the magnitude and/or frequency of an acceleration source. A QTH plot summarizes the magnitude and orientation of the low-frequency acceleration vector. This type of plot can show the microgravity effects of attitude, altitude, venting, etc.
The Principal Component Spectral Analysis and the Quasi-steady Three-dimensional Histogram techniques provide the means to describe, on a single plot, the microgravity acceleration environment of a long period of time, such as a day, week, or month. This allows a straight forward comparison of the microgravity environment between microgravity increments on the International Space Station, locations within the International Space Station, and/or different operating conditions. Traditional data display methods (e.g. acceleration versus time), while adequate for shorter time periods, would utilize more plots for an extensive period of time, often making interpretation more difficult. These new techniques provide a single page representation of a large set of microgravity acceleration data. These techniques, in conjunction with other techniques, may be employed to derive useful information from acceleration data to characterize or compare the microgravity environment.
The primary objective of this project was to apply the tropospheric atmospheric radon (Rn222) measurements to the development and verification of the global 3-D atmospheric chemical transport model under development by NASA's Atmospheric Effects of Aviation Project (AEAP). The AEAP project had two principal components: (1) a modeling effort, whose goal was to create, test and apply an elaborate three-dimensional atmospheric chemical transport model (the NASA/AEAP Core model to an evaluation of the possible short and long-term effects of aircraft emissions on atmospheric chemistry and climate--and (2) a measurement effort, whose goal was to obtain a focused set of atmospheric measurements that would provide some of the observational data used in the modeling effort. My activity in this project was confined to the first of these components. Both atmospheric transport and atmospheric chemical reactions (as well the input and removal of chemical species) are accounted for in the NASA/AEAP Core model. Thus, for example, in assessing the effect of aircraft effluents on the chemistry of a given region of the upper troposphere, the model must keep track not only of the chemical reactions of the effluent species emitted by aircraft flying in this region, but also of the transport into the region of these (and other) species from other, remote sources--for example, via the vertical convection of boundary layer air to the upper troposphere. Radon, because of its known surface source and known radioactive half-life, and freedom from chemical production or loss, and from removal from the atmosphere by physical scavenging, is a recognized and valuable tool for testing the transport components of global transport and circulation models.
The Scanning Multichannel Microwave Radiometer (SMMR) on board the NASA Nimbus 7 satellite was designed to obtain data for sea surface temperatures (SSTs), near-surface wind speeds, sea ice coverage and type, rainfall rates over the oceans, cloud water content, snow water equivalent, and soil moisture. In this paper, I shall emphasize the sea ice observations and mention briefly some important SST observations. A prime factor contributing to the importance of SMMR sea ice observations lies in their successful integration into a long-term time series, presently being extended by observations from the series of Special Sensor Microwave/Imager (SSMI) on board the DOD/DMSP F8, Fl1, and F12 satellites. This currently constitutes a 19-year data set. Almost half of this was provided by the SMMR. Unfortunately, the 4-year data set produced earlier by the single-channel Electrically Scanned Microwave Radiometer (ESMR) was not successfully integrated into the SMMR/SSMI data set. This resulted primarily from the lack of an overlap period to provide intersensor adjustment, but also because of the large difference between the algorithms to produce ice concentrations and large temporal gaps in the ESMR data. The lack of overlap between the SeaSat and Nimbus 7 SMMR data sets was an important consideration for also excluding the SeatSat one, but the spatial gaps especially in the Southern Hemisphere daily SeaSat observations was another. The sea ice observations will continue into the future by means of the Advanced Microwave Scanning Radiometer (AMSR) on board the ADEOS II and EOS satellites due to be launched in mid- and late-2000, respectively. Analysis of the sea ice data has been carried out by a number of different techniques. Long-term trends have been examined by means of ordinary least squares and band-limited regression. Oscillations in the data have been examined by band-limited Fourier analysis. Here, I shall present results from a novel combination of Principal Component analysis and the recently-developed Empirical Mode Decomposition (EMD). In this method, the data are first separated into spatial and temporal parts, and then the temporal parts of the first few PCs are broken into intrinsic modes by the EMD method.
Mass redistribution in terms of angular momentum will change the Earth's rotation under the conservation of angular momentum. It also changes the external gravitational field according to Newton's gravitational law. These small geodynamic variations can be measured very accurately by modem space geodetic techniques. We report on new estimates of the oceanic tidal angular momentum and hence the tidal variations in the Earth's rotation rate and polar motion. These are deduced from the new tidal solutions GOT99 and TPXO.3, plus M2 and Mf estimates (with error bars) from TPXO.4a. Comparisons with observed diurnal/semidiurnal tidal variations are generally similar to previous model estimates. Comparisons of models and observations of Mf polar motion are confused, with neither models nor observations agreeing among themselves or with each other. Part of this is caused by differences in Mf currents; model TPXO.4 shows current-intensive Rossby modes along western boundaries of major basins, which are indeed expected on theoretical grounds. Unfortunately, there are no reliable in situ observations of Mf currents useful for comparing models. On non-tidal oceanic mass redistribution we compute the principal components of the multi-year T/P sea surface height (SSH) field using EOF (empirical orthogonal functions) taking into consideration of the latitude-dependent area weighting. Emphasis is placed upon non-seasonal and interannual oscillations on regional scales, including ENSO and the North Atlantic Oscillation. Steric corrections to the observed SSH due to sea surface temperature changes (which has no geodynamic effects) is now under study using POCM ocean model output.
A generalized (pseudo) inverse technique was developed to facilitate a better understanding of the numerical effects of tropical singularities inherent in the spectral linear balance equation (LBE). Depending upon the truncation, various levels of determinancy are manifest. The traditional fully-determined (FD) systems give rise to a strong response, while the under-determined (UD) systems yield a weak response to the tropical singularities. The over-determined (OD) systems result in a modest response and a large residual in the tropics. The FD and OD systems can be alternatively solved by the iterative method. Differences in the solutions of an UD system exist between the inverse technique and the iterative method owing to the non- uniqueness of the problem. A realistic balanced wind was obtained by solving the principal components of the spectral LBE in terms of vorticity in an intermediate resolution. Improved solutions were achieved by including the singular-component solutions which best fit the observed wind data.
Atmospheric aerosol has uncertain impacts on the global climate system, as well as on atmospheric and bio-geo-chemical processes of regional and local scales. EOS-MODIS is one example of a satellite sensor designed to improve understanding of the aerosols' type, size and distribution at all temporal and spatial scales. Ocean scientists also plan to use data from EOS-MODIS to assess the temporal and spatial coverage of in-water chlorophyll. MODIS is the first sensor planned to observe the combined ocean-atmosphere system with a wide spectral range (from 410 to 2200 nm). Dust aerosol and salt aerosol have similar spectral signals for wavelengths longer than 550 nm, but because dust selectively absorbs blue light, they have divergent signals in the blue wavelength regions (412 to 490 nm). Chlorophyll also selectively absorbs blue radiation, so that varying chlorophyll concentrations produces a highly varying signal in the blue regions, but less variability in the green, and almost no signal in the red to mid-infrared regions. Thus, theoretically, it may be difficult to differentiate dust and salt in the presence of unknown chlorophyll in the ocean. This study attempts to address the cases in which aerosol and chlorophyll signals can and cannot be separated. For the aerosol spectra, we use the aerosol lookup table from the operational MODIS aerosol-over-ocean algorithm, and for chlorophyll spectra, we use the SeaBAM data set (created for SeaWiFS). We compare the signals using Principal Component Analysis and attempt to retrieve both chlorophyll and aerosol properties using a variant of the operational MODIS aerosol-over-ocean algorithm. Results show that for small optical depths, less than 0.5, it is not possible to differentiate between dust and salt and to determine the chlorophyll concentration at the same time. For larger aerosol optical depths, the chlorophyll signals are comparatively insignificant, and we can hope to distinguish between dust and salt.
This paper investigated the possibility of using spaceborne radar data to map forest types and logging in the mountainous Western Sayani area in Siberia. L and C band HH, HV, and VV polarized images from the Shuttle Imaging Radar-C instrument were used in the study. Techniques to reduce topographic effects in the radar images were investigated. These included radiometric correction using illumination angle inferred from a digital elevation model, and reducing apparent effects of topography through band ratios. Forest classification was performed after terrain correction utilizing typical supervised techniques and principal component analyses. An ancillary data set of local elevations was also used to improve the forest classification. Map accuracy for each technique was estimated for training sites based on Russian forestry maps, satellite imagery and field measurements. The results indicate that it is necessary to correct for topography when attempting to classify forests in mountainous terrain. Radiometric correction based on a DEM (Digital Elevation Model) improved classification results but required reducing the SAR (Synthetic Aperture Radar) resolution to match the DEM. Using ratios of SAR channels that include cross-polarization improved classification and
An active structural acoustic control system has been demonstrated on a Raytheon Aircraft Company 1900D turboprop airliner. Both single frequency and multi-frequency control of the blade passage frequency and its harmonics was accomplished. The control algorithm was a variant of the popular filtered-x LMS implemented in the principal component domain. The control system consisted of 21 inertial actuators and 32 microphones. The actuators were mounted to the aircraft's ring frames. The microphones were distributed uniformly throughout the interior at head height, both seated and standing. Actuator locations were selected using a combinatorial search optimization algorithm. The control system achieved a 14 dB noise reduction of the blade passage frequency during single frequency tests. Multi-frequency control of the first 1st, 2nd and 3rd harmonics resulted in 10.2 dB, 3.3 dB and 1.6 dB noise reductions respectively. These results fall short of the predictions which were produced by the optimization algorithm (13.5 dB, 8.6 dB and 6.3 dB). The optimization was based on actuator transfer functions taken on the ground and it is postulated that cabin pressurization at flight altitude was a factor in this discrepancy.
We present an algorithm for detecting a specified set of targets for an Automatic Target Recognition (ATR) application. ATR involves processing images for detecting, classifying, and tracking targets embedded in a background scene. We address the problem of discriminating between targets and nontarget objects in a scene by evaluating 40x40 image blocks belonging to an image. Each image block is first projected onto a set of templates specifically designed to separate images of targets embedded in a typical background scene from those background images without targets. These filters are found using directed principal component analysis which maximally separates the two groups. The projected images are then clustered into one of n classes based on a minimum distance to a set of n cluster prototypes. These cluster prototypes have previously been identified using a modified clustering algorithm based on prior sensed data. Each projected image pattern is then fed into the associated cluster's trained neural network for classification. A detailed description of our algorithm will be given in this paper. We outline our methodology for designing the templates, describe our modified clustering algorithm, and provide details on the neural network classifiers. Evaluation of the overall algorithm demonstrates that our detection rates approach 96% with a false positive rate of less than 0.03%.
Wavelet analysis of NASA scatterometer (NSCAT) backscatter and Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) radiance data can be used to obtain daily sea ice drift information for the Arctic region. This technique provides improved spatial coverage over the existing array of Arctic Ocean buoys and better temporal resolution over techniques utilizing data from satellite synthetic aperture radars. Comparisons with ice motion derived from ocean buoys give good quantitative agreement. Both comparison results from NSCAT and SSM/I are compatible, and the results from NSCAT can definitely complement that from SSM/I when there are cloud or surface effects. Then three sea-ice drift daily results from NSCAT, SSM/I, and buoy data can be merged as a composite map by some data fusion techniques. The ice flow streamlines are highly correlated with surface air pressure contours. Examples of derived ice-drift maps in December 1996 illustrate large-scale circulation reversals over a period of four days. A method for deriving divergence and shear at the large-scale has been developed and comparison between buoys and satellite results shows a good agreement. These calibrated/validated results indicate that NSCAT, SSM/I merged daily ice motion are suitably accurate to identify and closely locate sea ice processes, and to improve our current knowledge of sea ice drift and related processes through the data assimilation of ocean-ice numerical model. For demonstration purpose, the ice velocities derived from satellite data are compared with the ice velocities derived from a coupled ice-ocean interaction model. The comparison reveals that the general circulation patterns of the two are quite similar but the ice velocity differences between the two are quite significant. In order to quantify the wind effects on ice motion, empirical orthogonal functions (EOF) are used in the principal component analysis for both ice motion and pressure field. Some preliminary results of sea-ice motion from QuikScat will also be presented.
NASA's long term plan for Mars sample collection and return requires a highly streamlined approach for spectrally characterizing a landing site, documenting the mineralogical make-up of the site and guiding the collections of samples which represent the diversity of the site. Ideally, image data should be acquired at hundreds of VIS and IR wavelengths, in order to separately distinguish numerous anticipated species, using principal component analysis and linear unmixing. Cameras with bore-sighted point spectrometers can acquire spectra of isolated scene elements, but it requires 10(exp 2) to 10(exp 2) successive motions and precise relative pointing knowledge in order to create a single data cube which qualifies as a spectral map. These and other competing science objectives have to be accomplished within very short lander/rover operational lifetime (a few sols). True, 2-D imaging spectroscopy greatly speeds up the data acquisition process, since the spectra of all pixels in the scene are collected at once. This task can be accomplished with cameras that use electronically tunable acousto-optic tunable filters (AOTFs) as the optical tuning element. AOTFs made from TeO2 are now a mature technology, and operate at wavelengths from near-UV to about 5 microns. Because of incremental improvements in the last few years, present generation devices are rugged, radiation-hard and operate at temperatures down to at least 150K so they can be safely integrated into the ambient temperature optics of in-situ instruments such as planetary or small-body landers. They have been used for ground-based astronomy, and were also baselined for the ST-4 Champollion IR comet lander experiment (CIRCLE), prior to cancellation of the ST-4 mission last year. AIMS (for Acousto-optic Imaging spectrometer), is a prototype lander instrument which is being built at GSFC with support by the NASA OSS Advanced Technologies and Mission Studies, Mars Instrument Definition and Development Program (MIDP). AIMS is capable of tunable spectroscopic imaging of surface mineralogy, ices and dust between 0.5 and 2.4 microns, at a resolving power (lambda/delta lambda) which is typically several hundred. The design spatial resolution, similar to IMP and SSI, will allow mapping at scales down to about 1 cm.