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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Studies of Florida Thunderstorms Using LDAR, LLP, and Single Doppler Radar Data

The paper summarizes results from research conducted on thunderstorms in the vicinity of the Kennedy Space Center (KSC) Florida, between 1993 and 1998. The focus of the research was to identify procedures that would assist weather forecasters at the Cape Canaveral Air Station (CCAS) in real-time detection and forecasting of the lightning threat to launches and daily ground operations at KSC/CCAS sites. The research was divided into three topics: (1) studies aimed at improving the forecasting of the initial cloud-ground (CG) lightning threat, (2) studies aimed at improving the forecasting of the end-of-storm termination of the CG lightning threat, and (3) studies of the location of CG strikes relative to the thunderstorm radar echo and to lightning discharges aloft. Only the first two topics are covered in this preprint.

Forbes, Gregory S.↗
NASA NTRS1996

Processing Ultra Wide Band Synthetic Aperture Radar Data with Motion Detectors

Several issues makes the processing of ultra wide band (UWB) SAR data acquired from an airborne platform difficult. The character of UWB data invalidates many of the usual SAR batch processing techniques, leading to the application of wavenumber domain type processors...This paper will suggest and evaluate an algorithm which combines a wavenumber domain processing algorithm with a motion compensation procedure which enables motion compensation to be applied as a function of target range and the azimuth angle.

synthetic aperture radar sar ultra wide band sar m↗
NASA NTRS1978

Real-time synthetic aperture radar data processing for space applications

Range and azimuth correlation in the time domain using current state-of-the-art CCD LSI technology provides a potentially practical means of achieving real-time pipeline processing of SAR images for future space missions. The proposed range correlator approach, using already demonstrated CCD transversal filtering techniques, will require very little power: less than 10 watts per Seasat-type 20-km processing module. The azimuth correlator architecture is considerably more demanding since it requires a large number of parallel chips (1020 for a Seasat-type 20-km module) to achieve a real-time processing capability.

Arens, W. E.↗
NASA NTRS1979

Aircraft motion analysis using limited flight and radar data

The development and application of methods for reconstructing, from a limited set of recorded data, a comprehensive scenario of aircraft motions before and during an accident are described. The accuracy of these analytical methods is investigated using data recorded onboard the Ames CV-990 research aircraft. In these experiments, the expanded set of data, derived from either foil or ATC records, is compared with corresponding values measured by the research instrumentation system onboard the aircraft. The results indicate that many of the derived quantities are in good agreement with the corresponding onboard measurements. A recent application of this procedure using actual accident records is presented and potential applications are briefly reviewed.

Wingrove, R. C.↗
NASA NTRS1980

Analysis of urban area land cover using SEASAT Synthetic Aperture Radar data

Digitally processed SEASAT synthetic aperture raar (SAR) imagery of the Denver, Colorado urban area was examined to explore the potential of SAR data for mapping urban land cover and the compatability of SAR derived land cover classes with the United States Geological Survey classification system. The imagery is examined at three different scales to determine the effect of image enlargement on accuracy and level of detail extractable. At each scale the value of employing a simplistic preprocessing smoothing algorithm to improve image interpretation is addressed. A visual interpretation approach and an automated machine/visual approach are employed to evaluate the feasibility of producing a semiautomated land cover classification from SAR data. Confusion matrices of omission and commission errors are employed to define classification accuracies for each interpretation approach and image scale.

Henderson, F. M.↗
NASA NTRS1984

Processing of Synthetic-Aperture-Radar Data

Ambiguous data combined to permit fast-transform convolution. New data processor designed: two-dimensional ensemble of range-correlated SAR data stored in memory and extracted in format for which azimuth data are colinear.

Di Cenzo, A. E.↗
NASA NTRS1983

Computer analysis of X-band radar data

The effectiveness of using currently available computer techniques for interpretation of MSS data to interpret SAR imagery for forest monitoring was assessed. Data were gathered with NASA's airborne APQ-102 dual-polarized, X-band SAR in a flight at 60,000 ft. Microdensitometry was employed to digitize the HH- and HV-polarized imagery. A ground spatial resolution of 15 m was obtained, control points were identified, a second order biquadratic transformation was applied to compensate for orientation, and rms errors were calculated. A second data set was taken with 30 m resolution in order to simulate thematic mapper operation. Classification was performed with pixel-by-pixel and textural classification algorithms. A statistical analysis was also carried out to find any significant differences between classifiers in a data set for a given classifier. Each polarization featured an independent distortion which required appropriate preprocessing to correct. Further studies are recommended with multiple frequencies viewing and multiple polarizations and look angles to define the actual forest classifications that can be made with the SAR imagery.

Knowlton, D. J.↗
NASA NTRS1983

Analysis of Synthetic Aperture Radar data acquired over a variety of land cover

An analysis has been conducted of two-look-angle, multipolarization X-band SAR results. On the basis of the variety of land covers studied, the vertical-vertical polarization (VV) data is judged to contain the highest degree of contrast, while the horizontal-vertical (HV) polarization contained the least. VV polarization data is accordingly recommended for forest vegetation classification in those cases where only one data channel is available. The inclusion of horizontal-horizontal polarization data, however, is noted to be capable of delineating special surface features.

Wu, S. T.↗
NASA NTRS1986

The Tukey algorithm for enhancing MST radar data

One of the most troublesome features in MSR (mesosphere stratosphere troposphere) velocity measurements is the determination of unwanted scatterer whose velocity is different from that of the surrounding atmosphere. Aircraft seen in the sidelobes of the antenna are the principal problem. Because coherent integration essentially eliminates echoes with line of sight velocities greater than 10 or 20 m/s, aircraft are seen only when their flight path is almost perpendicular to the line of sight. Then, they give large returns whose velocities may be positive or negative, and certainly different from that of the surrounding air. The glitches in the minute by minute velocity records are quite troublesome in that they may distort the statistics of the velocity. An objective way is therefore needed to remove sporadic points of this kind. For this purpose, the Tukey algorithm is appropriate and has some advantages over averaging. The Tukey algorithm, applied to a data array, uses for each data point the median of it and the two points surrounding it. If the three points form a monotonically increasing or decreasing sequence, the original point is copied with change. However, if the central point is remote from the other two, it is replaced by whichever of the two surrounding points is closest in value. The greatest effect of the Tukey algorithm is on data where the successive points are uncorrelated. Examples are given.

Bowhill, S. A.↗
NASA NTRS1987

Parametric analysis of synthetic aperture radar data for characterization of deciduous forest stands

The SAR sensor parameters that affect the estimation of deciduous forest stand characteristics were examined using data sets for the Gulf Coastal Plain region, acquired by the NASA/JPL multipolarization airborne SAR. In the regression analysis, the mean digital-number values of the three polarization data are used as the independent variables to estimate the average tree height (HT), basal area (BA), and total-tree biomass (TBM). The following results were obtained: (1) in the case of simple regression and using 28 plots, vertical-vertical (VV) polarization yielded the largest correlation coefficients (r) in estimating HT, BA, and TBM; (2) in the case of multiple regression, the horizontal-horizontal (HH) and VV polarization combination yielded the largest r value in estimating HT, while the VH and HH polarization combination yielded the largest r values in estimating BA and TBM. With the addition of a third polarization, the increase in r values is insignificant.

Wu, Shih-Tseng↗
NASA NTRS1989

Low-pass spatial filtering of satellite radar data

Thirty-four low-pass spatial filter treatments were applied to a multi-angle SIR-B data set to reduce speckle effects and improve classification performance. These treatments were based on four algorithms: square mean, separable mean, square median, and separable recursive median. The filtered images were evaluated using both quantitative and qualitative techniques. It was determined that the square median algorithm implemented at two iterations with a window size of 3 by 3 produced the best overall results with the 28.5-m SIR-B data.

Mueller, Paul W.↗
NASA NTRS1988

Parametric analysis of synthetic aperture radar data for the study of forest stand characteristics

A parametric analysis of a Gulf Coast forest stand was performed using multipolarization, multipath airborne SAR data, and forest plot properties. Allometric equations were used to compute the biomass and basal area for the test plots. A multiple regression analysis with stepwise selection of independent variables was performed. It is found that forest stand characteristics such as biomass, basal area, and average tree height are correlated with SAR data.

Wu, Shih-Tseng↗