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NASA NTRS2018

Aeroacoustic Validation of Installed Low Noise Propulsion for NASA's N+2 Supersonic Airliner

An aeroacoustic test was conducted at NASA Glenn Research Center on an integrated propulsion system designed to meet noise regulations of ICAO Chapter 4 with 10EPNdB cumulative margin. The test had two objectives: to demonstrate that the aircraft design did meet the noise goal, and to validate the acoustic design tools used in the design. Variations in the propulsion system design and its installation were tested and the results compared against predictions. Far-field arrays of microphones measured the acoustic spectral directivity, which was transformed to full scale as noise certification levels. Phased array measurements confirmed that the shielding of the installation model adequately simulated the full aircraft and provided data for validating RANS-based noise prediction tools. Particle image velocimetry confirmed that the flow field around the nozzle on the jet rig mimicked that of the full aircraft and produced flow data to validate the RANS solutions used in the noise predictions. The far-field acoustic measurements confirmed the empirical predictions for the noise. Results provided here detail the steps taken to ensure accuracy of the measurements and give insights into the physics of exhaust noise from installed propulsion systems in future supersonic vehicles.

supersonic↗
NASA NTRS1980

Near-infrared spectral imaging Michelson interferometer for astronomical applications

The design and operation of an imaging Michelson interferometer-spectrometer used for near-infrared (0.8 micron to 2.5 microns) spectral imaging are reported. The system employs a rapid scan interferometer modified for stable low resolution (250/cm) performance and a 42 element PbS linear detector array. A microcomputer system is described which provides data acquisition, coadding, and Fourier transformation for near real-time presentation of the spectra of all 42 scene elements. The electronic and mechanical designs are discussed and telescope performance data presented.

Wells, C. W.↗
NASA NTRS1983

The potential of SAR directional spectra in operational wave forecasting

Digitally processed Seasat SAR ocean wave imagery, when digitally transformed, smoothed, and corrected for known instrument biases, can accurately track multiple (at least three) wave systems in the open ocean, across major currents, and into shallow water. Furthermore, the relative backscatterer of the digitally processed SAR image, when sampled within a single pass and along a constant range, responds to the local wind through a simple power law relationship. The results indicate that SAR spectra, if obtained from a low altitude satellite, could be an important supplement to global winds and non-directional wave heights obtained through other methods.

Beal, R. C.↗
NASA NTRS1988

Relationships between near-surface plankton concentrations, hydrography, and satellite-measured sea surface temperature

Sea surface temperatures (SSTs) mapped by IR satellite images and in situ hydrographic measurements off the west coast of British Columbia for early-winter and midsummer periods were correlated with in situ measurements of surface chlorophyll and zooplankton concentration. Correlations between winter log(e) transformed zooplankton concentrations and SSTs demonstrated that IR satellite imagery could explain 49 percent of the sampled zooplankton concentration variance. A least-squares-fit nonlinear equation showed that satellite-measured SST patterns explained 72 percent of the log(e) transformed chlorophyll variance. However, summer zooplankton concentrations were not consistently related to satellite temperature patterns.

Thomas, A. C.↗
NASA NTRSDate not supplied

How the Open Data Policy of the Landsat Program Has Advanced Our Understanding of Environmental Change

A time series is a sequence of observations of a phenomenon taken sequentially in time. A crucial characteristic of a time series is the dependence among adjacent observations – techniques for analyzing this dependence are referred to as time series analysis. This analytical approach enables us to predict or forecast future values of a time series, study the impact of various inputs on the observed phenomenon, and examine interrelationships among related time series variables. Within the geographical sciences, time series analysis has historically been limited to coarse-resolution satellite data, as constructing time series of data suitable for studying land cover and land use dynamics, such as Landsat data, were prohibitively costly. A transformative shift occurred in 2008 when the U.S. Government decided to make free and open all past and future data collected by the Landsat satellite program. The decision brought about a paradigm shift away from analyzing individual images or observations to continuous monitoring in time. Of particular relevance to environmental remote sensing is the ability to forecast observations – if we can predict how future observations should behave, we can infer information about how the land surface is changing. In this presentation, we will examine literature examples that showcase scientific gains enabled by time series analysis of satellite data. We will delve into how the analysis of dense time series of satellite data revealed that overall rate of forest disturbance in the Amazon has increased despite a reduction in deforestation; how different types of forest degradation, previously unquantified, are now being accurately assessed in the Caucasus region; and how we now can study the highly dynamic and intricate patterns of shifting cultivation in Southeast Asia.

Pontus Olofsson↗
NASA NTRSDate not supplied

Total Variation Majorization Minimization (TV-MM) Approach to Radiometer Brightness Temperature Gridding and Reconstruction

This paper presents the implementation of an algorithm to enhance the image resolution of the Earth's surface brightness temperature (T B ) data measured by radiometers such as the one onboard of the Soil Moisture Active Passive (SMAP) mission. A key step in radiometer T B processing is the conversion of the swath-based calibrated antenna temperature (T A ) measurements to the Level 3 Earth-centered grid. The simplest algorithm to transform this data from swath to gridded format is called drop-in-the-bucket which simply averages surrounding noisy T A samples to form a T B value at the gridded location. This method reduces noise, however produces low resolution products. To obtain a higher resolution product, SMAP uses other techniques such the Backus-Gilbert (BG) algorithm, which is the conventional method used in microwave radiometry. Although this method performs the required interpolation, it is not effective in denoising and removing blurring effects due to antenna filtering of the radiometer image data. Our motivation for this development is to further improve the resolution through post-processing of the radiometer T B image, a highly cost-effective method of image enhancement. The approach adapted in this work is based on the minimization of the Total Variation (TV) regularized objective function that is used extensively in solving general ill-posed linear inverse problems in image processing. Since the TV-based objective function is convex but not everywhere differentiable, there exists many numerical algorithms that can estimate the solution and the one selected for this work is called Majorization- Minimization (MM). By applying this algorithm, simulation experiments were performed based on synthetic data from the Geophysical model as well as real SMAP data to demonstrate the effectiveness of the technique. Results were then compared against the BG method.

Wing Lee↗
NASA NTRS2010

Multi-Stage System for Automatic Target Recognition

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an artificial neural network classifier. The multi-stage system allows tuning the detection sensitivity and the identification specificity individually in each stage. It is easier to achieve optimized ATR operation based on its specific goal. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar and video image datasets.

Chao, Tien-Hsin↗
NASA NTRS1974

Solar radiometry at millimeter wavelengths

In the area of resolution enhancement, the use of Fast Fourier Transform programs was investigated for possible application to millimeter wavelength maps of the sun. A difficulty arises with the La Posta maps in that they are limited to 35 arc-minutes square while the smeared out solar image is larger than that. A list of possible cometary emission lines near 13 millimeters is presented. Although preparation of the list was inspired by the appearance of Comet Kohoutek, the results are applicable to any future comet. The brightness temperature of the sun at 8.6 millimeters was measured using the moon as a calibration source. The result does not confirm a deep absorption feature as apparently observed by earlier workers.

Henze, W.↗
NASA NTRS1995

Wavelet transform analysis of the small-scale X-ray structure of the cluster Abell 1367

We have developed a new technique based on a wavelet transform analysis to quantify the small-scale (less than a few arcminutes) X-ray structure of clusters of galaxies. We apply this technique to the ROSAT position sensitive proportional counter (PSPC) and Einstein high-resolution imager (HRI) images of the central region of the cluster Abell 1367 to detect sources embedded within the diffuse intracluster medium. In addition to detecting sources and determining their fluxes and positions, we show that the wavelet analysis allows a characterization of the sources extents. In particular, the wavelet scale at which a given source achieves a maximum signal-to-noise ratio in the wavelet images provides an estimate of the angular extent of the source. To account for the widely varying point response of the ROSAT PSPC as a function of off-axis angle requires a quantitative measurement of the source size and a comparison to a calibration derived from the analysis of a Deep Survey image. Therefore, we assume that each source could be described as an isotropic two-dimensional Gaussian and used the wavelet amplitudes, at different scales, to determine the equivalent Gaussian Full Width Half-Maximum (FWHM) (and its uncertainty) appropriate for each source. In our analysis of the ROSAT PSPC image, we detect 31 X-ray sources above the diffuse cluster emission (within a radius of 24 min), 16 of which are apparently associated with cluster galaxies and two with serendipitous, background quasars. We find that the angular extents of 11 sources exceed the nominal width of the PSPC point-spread function. Four of these extended sources were previously detected by Bechtold et al. (1983) as 1 sec scale features using the Einstein HRI. The same wavelet analysis technique was applied to the Einstein HRI image. We detect 28 sources in the HRI image, of which nine are extended. Eight of the extended sources correspond to sources previously detected by Bechtold et al. Overall, using both the PSPC and the HRI observations, we detect 16 extended features, of which nine have galaxies coincided with the X-ray-measured positions (within the positional error circles). These extended sources have luminosities lying in the range (3 - 30) x 10(exp 40) ergs/s and gas masses of approximately (1 - 30) x 10(exp 9) solar mass, if the X-rays are of thermal origin. We confirm the presence of extended features in A1367 first reported by Bechtold et al. (1983). The nature of these systems remains uncertain. The luminosities are large if the emission is attributed to single galaxies, and several of the extended features have no associated galaxy counterparts. The extended features may be associated with galaxy groups, as suggested by Canizares, Fabbiano, & Trinchieri (1987), although the number required is large.

Grebeney, S. A.↗
NASA NTRS1975

Investigation to develop a multistage forest sampling inventory system using ERTS-1 imagery

The author has identified the following significant results. The annotation system produced a RMSE of about 200 m ground distance in the MSS data system with the control data used. All the analytical MSS interpretation models tried were highly significant. However, the gains in forest sampling efficiency that can be achieved by using the models vary from zero to over 50 percent depending on the area to which they are applied and the sampling method used. Among the sampling methods tried, regression sampling yielded substantial and the most consistent gains. The single most significant variable in the interpretation model was the difference between bands 5 and 7. The contrast variable, computed by the Hadamard transform was significant but did not contribute much to the interpretation model. Forest areas containing very large timber volumes because of large tree sizes were not separable from areas of similar crown cover but containing smaller trees using ERTS image interpretation only. All correlations between space derived timber volume predictions and estimates obtained from aerial and ground sampling were relatively low but significant and stable. There was a much stronger relationship between variables derived from MSS and U2 data than between U2 and ground data.

Langley, P. G.↗
NASA NTRS1991

A new system model for radar polarimeters

The validity of the 2 x 2 receive R and transmit T model for radar polarimeter systems, first proposed by Zebker et al. (1987), is questioned. The model is found to be invalid for many practical realizations of radar polarimeters, which can lead to significant errors in the calibration of polarimetric radar images. A more general model is put forward, which addresses the system defects which cause the 2 x 2 model to break down. By measuring one simple parameter from a polarimetric active radar calibration (PARC), it is possible to transform the scattering matrix measurements made by a radar polarimeter to a format compatible with a 2 x 2 R and T matrix model. Alternatively, the PARC can be used to verify the validity of the 2 x 2 model for any polarimetric radar system. Recommendations for the use of PARCs in polarimetric calibration and to measure the orientation angle of the horizontal (H) and vertical (V) coordinate system are also presented.

Freeman, Anthony↗
NASA NTRS1991

The fractional Fourier transform and applications

This paper describes the 'fractional Fourier transform', which admits computation by an algorithm that has complexity proportional to the fast Fourier transform algorithm. Whereas the discrete Fourier transform (DFT) is based on integral roots of unity e exp -2(pi)i/n, the fractional Fourier transform is based on fractional roots of unity e exp -2(pi)i(alpha), where alpha is arbitrary. The fractional Fourier transform and the corresponding fast algorithm are useful for such applications as computing DFTs of sequences with prime lengths, computing DFTs of sparse sequences, analyzing sequences with noninteger periodicities, performing high-resolution trigonometric interpolation, detecting lines in noisy images, and detecting signals with linearly drifting frequencies. In many cases, the resulting algorithms are faster by arbitrarily large factors than conventional techniques.

Bailey, David H.↗
NASA NTRS2013

Mixture-Tuned, Clutter Matched Filter for Remote Detection of Subpixel Spectral Signals

Mapping localized spectral features in large images demands sensitive and robust detection algorithms. Two aspects of large images that can harm matched-filter detection performance are addressed simultaneously. First, multimodal backgrounds may thwart the typical Gaussian model. Second, outlier features can trigger false detections from large projections onto the target vector. Two state-of-the-art approaches are combined that independently address outlier false positives and multimodal backgrounds. The background clustering models multimodal backgrounds, and the mixture tuned matched filter (MT-MF) addresses outliers. Combining the two methods captures significant additional performance benefits. The resulting mixture tuned clutter matched filter (MT-CMF) shows effective performance on simulated and airborne datasets. The classical MNF transform was applied, followed by k-means clustering. Then, each cluster s mean, covariance, and the corresponding eigenvalues were estimated. This yields a cluster-specific matched filter estimate as well as a cluster- specific feasibility score to flag outlier false positives. The technology described is a proof of concept that may be employed in future target detection and mapping applications for remote imaging spectrometers. It is of most direct relevance to JPL proposals for airborne and orbital hyperspectral instruments. Applications include subpixel target detection in hyperspectral scenes for military surveillance. Earth science applications include mineralogical mapping, species discrimination for ecosystem health monitoring, and land use classification.

Thompson, David R.↗
NASA NTRS2021

NASA's Surface Biology and Geology Concept Study: Status and Next Steps

The National Academies Decadal Survey for Earth Science recommended that NASA pursue global imaging spectroscopy and thermal infrared measurements in the coming decade [1]. Both measurements would offer repeat coverage on approximately five-day to biweekly cadence, with comprehensive coverage of the globe's coastal and terrestrial area. This would be an unprecedented volume of data with the potential to transform remote sensing practice. To address this recommendation, NASA has sponsored a concept study by NASA research centers and associated university partners (https://sbg.jpl.nasa.gov). This study is determining a family of architecture options - including launch vehicle, spacecraft, instrument, and suborbital components - that could address the Decadal Survey objectives. The architecture study is driven by science needs and builds on input of the research community. As of this writing, the study is entering a phase in which a large field of system possibilities is pared down to a representative handful for an ultimate decision by NASA.

Imaging Spectroscopy↗
NASA NTRS1974

Measurement of the earth resources technology satellite /ERTS-1/ multi-spectral scanner OTF from operational imagery

The optical transfer function (OTF) of some typical ERTS-1 multispectral imagery was obtained by comparison of matched sets of aircraft underflight and ERTS photographic and digital images. One-dimensional OTF analysis consisted in obtaining U-2 and ERTS microdensitometer scans followed by density to transmission conversion, microdensitometer aperture correction, exposure calibration, scan correlation scale optimization, OTF calculation, obtaining a form weighted average of the OTFs, transformation of the OTFs back to the spatial domain (giving the line spread function or LSF), and application of a window function to the LSF resulting in a smoothed OTF. Date-to-date comparison of ERTS OTFs showed a drop in quality on April 4, 1973, compared with January 4, 1973.

Schowengerdt, R. A.↗
NASA NTRS1992

Passive microwave precipitation mapping and retrieval simulation

A numerical simulation of the satellite-based multispectral passive microwave mapping and precipitation retrieval process is described. The simulation contains three major components: (1) the forward radiative transfer calculation; (2) the sensor observation simulation; and (3) the precipitation retrieval algorithm. Secondary components include a Karhunen-Loeve transformation module and antenna pattern deconvolution module. The simulation facilitates the investigation of candidate precipitation retrieval algorithms using sub-Nyquist brightness temperature imagery, and the comparison of the relative merits of proposed radiometric systems such as the EOS multispectral imaging microwave radiometer (MIMR), the tropical rainfall measurement mission (TRMM) microwave imager (TRMM TMI), and the geosynchronous satellite sensors. A procedure for retrieving rain rates using a statistical iterative approach is outlined.

Skofronick, G. M.↗
NASA NTRS2006

Aeroelastic Flight Data Analysis with the Hilbert-Huang Algorithm

This report investigates the utility of the Hilbert Huang transform for the analysis of aeroelastic flight data. It is well known that the classical Hilbert transform can be used for time-frequency analysis of functions or signals. Unfortunately, the Hilbert transform can only be effectively applied to an extremely small class of signals, namely those that are characterized by a single frequency component at any instant in time. The recently-developed Hilbert Huang algorithm addresses the limitations of the classical Hilbert transform through a process known as empirical mode decomposition. Using this approach, the data is filtered into a series of intrinsic mode functions, each of which admits a well-behaved Hilbert transform. In this manner, the Hilbert Huang algorithm affords time-frequency analysis of a large class of signals. This powerful tool has been applied in the analysis of scientific data, structural system identification, mechanical system fault detection, and even image processing. The purpose of this report is to demonstrate the potential applications of the Hilbert Huang algorithm for the analysis of aeroelastic systems, with improvements such as localized online processing. Applications for correlations between system input and output, and amongst output sensors, are discussed to characterize the time-varying amplitude and frequency correlations present in the various components of multiple data channels. Online stability analyses and modal identification are also presented. Examples are given using aeroelastic test data from the F-18 Active Aeroelastic Wing airplane, an Aerostructures Test Wing, and pitch plunge simulation.

Brenner, Martin J.↗
NASA NTRS2009

Direct-Solve Image-Based Wavefront Sensing

A method of wavefront sensing (more precisely characterized as a method of determining the deviation of a wavefront from a nominal figure) has been invented as an improved means of assessing the performance of an optical system as affected by such imperfections as misalignments, design errors, and fabrication errors. The method is implemented by software running on a single-processor computer that is connected, via a suitable interface, to the image sensor (typically, a charge-coupled device) in the system under test. The software collects a digitized single image from the image sensor. The image is displayed on a computer monitor. The software directly solves for the wavefront in a time interval of a fraction of a second. A picture of the wavefront is displayed. The solution process involves, among other things, fast Fourier transforms. It has been reported to the effect that some measure of the wavefront is decomposed into modes of the optical system under test, but it has not been reported whether this decomposition is postprocessing of the solution or part of the solution process.

Lyon, Richard G.↗