Abstract-WindSat is a space-based polarimetric microwave radiometer designed to demonstrate the capability to measure the ocean surface wind vector using a radiometer. We describe a nonlinear iterative algorithm for simultaneous retrieval of sea surface temperature, columnar water vapor, columnar cloud liquid water, and the ocean surface wind vector from WindSat measurements. The algorithm uses a physically based forward model function for the WindSat brightness temperatures. Empirical corrections to the physically based model are discussed. We present evaluations of initial retrieval performance using a six-month dataset of WindSat measurements and collocated data from other satellites and a numerical weather model. We focus primarily on the application to wind vector retrievals.
Abstract-Automatic land cover classification maps were developed from Airborne Hyperspectral Scanner (HyMAP) imagery acquired May 8, 2000 over Smith Island, VA, a barrier island in the Virginia Coast Reserve. Both unsupervised and supervised classification approaches were used to create these products to evaluate relative merits and to develop models that would be useful to natural resource managers at higher spatial resolution than has been available previously. Ground surveys made by us in late October and early December 2000 and again in May, August, and October 2001 and May 2002 provided ground truth data for 20 land cover types. Locations of pure land cover types recorded with global positioning system (GPS) data from these surveys were used to extract spectral end-members for training and testing supervised land cover classification models. Unsupervised exploratory models were also developed using spatial-spectral windows and projection pursuit (PP), a class of algorithms suitable for extracting multimodal views of the data. PP projections were clustered by ISODATA to produce an unsupervised classification. Supervised models, which relied on the GPS data, used only spectral inputs because for some categories in particular areas, labeled data consisted of isolated single-pixel waypoints. Both approaches to the classification problem produced consistent results for some categories such as Spartina alterniflora, although there were differences for other categories. Initial models for supervised classification based on 112 HyMAP spectra, labeled in ground surveys, obtained reasonably consistent results for many of the dominant categories, with a few exceptions. For an invasive plant species, Phragmites australis, a particular concern of natural resource managers, this approach initially had an excessively high false-alarm rate. Increasing the number of spectral training samples by an order of magnitude and making concomitant improvements to the georectification led to dramatic improvements in this and other categories. The unsupervised spatial-spectral approach also found a cluster closely associated with Phragmites patches near the thicket boundary, but this approach did not identify the exposed are compared against HyMAP image spectra at model-predicted pixels and at validated GPS waypoints.Index Terms-Barrier islands, hyperspectral, in situ spectrometry, invasive plant species, land cover classification, neural networks, principle component analysis, projection pursuit, supervised classification, unsupervised classification.
Abstract-Radio-frequency interference (RFI) in the spaceborne multichannel radiometer data of WindSat and the Advanced Microwave Scanning Radiometer-EOS is currently being detected using a spectral difference technique. Such a technique does not explicitly utilize multichannel correlations of radiometer data, which are key information in separating RFI from natural radiations. Furthermore, it is not optimal for radiometer data observed over ocean regions due to the inherent large natural variability of spectral difference over ocean. In this paper, we first analyzed multivariate WindSat and Scanning Multichannel Microwave Radiometer (SMMR) data in terms of channel correlation, information content, and principal components of WindSat and SMMR data. Then two methods based on channel correlation were developed for RFI detection over land and ocean. Over land, we extended the spectral difference technique using principal component analysis (PCA) of RFI indices, which integrates statistics of target emission/scattering characteristics (through RFI indices) and multivariate correlation of radiometer data into a single statistical framework of PCA. Over ocean, channel regression of X-band can account for nearly all of the natural variations in the WindSat data. Therefore, we use a channel regression-based model difference technique to directly predict RFI-free brightness temperature, and therefore RFI intensity. Although model difference technique is most desirable, it is more difficult to apply over land due to heterogeneity of land surfaces. Both methods improve our knowledge of RFI signatures in terms of channel correlations and explore potential RFI mitigation, and thus provide risk reductions for future satellite passive microwave missions such as the NPOESS Conical Scanning Microwave Imager/Sounder. The new RFI algorithms are effective in detecting RFI in the C-and X-band Windsat radiometer channels over land and ocean.Index Terms-Microwave remote sensing, radio-frequency interference (RFI), WindSat.
The first experiments utilizing high-power radio waves in the ion cyclotron range of frequencies to heat deuterium–tritium (D–T) plasmas have been completed on the Tokamak Fusion Test Reactor [Fusion Technol. 21, 13 (1992)]. Results from the initial series of experiments have demonstrated efficient core second harmonic tritium (2ΩT) heating in parameter regimes approaching those anticipated for the International Thermonuclear Experimental Reactor [D. E. Post, Plasma Physics and Controlled Nuclear Fusion Research, Proceedings of the 13th International Conference, Washington, DC, 1990 (International Atomic Energy Agency, Vienna, 1991), Vol. 3, p. 239]. Observations are consistent with modeling predictions for these plasmas. Efficient electron heating via mode conversion of fast waves to ion Bernstein waves has been observed in D–T, deuterium-deuterium (D–D), and deuterium–helium-4 (D–4He) plasmas with high concentrations of minority helium-3 (3He) (n3He/ne≳10%). Mode conversion current drive in D–T plasmas was simulated with experiments conducted in D–3He–4He plasmas. Results show a directed propagation of the mode converted ion Bernstein waves, in correlation with the antenna phasing.
A pulsed, 193 nm excimer laser is utilized to photoionize the organic gas tetrakisdimethylamino-ethylene ͑TMAE͒. The laser ionizes a plasma sheet with a width of 7.8 cm and an adjustable thickness of 0.7-1.4 cm. The axial scale length of the plasma density is a function of TMAE neutral pressure and is typically 50 cm. X-band ͑10 GHz͒ microwaves are incident on the plasma with the electric field polarized parallel to the laser beam axis. The power reflection coefficient and the phase of the reflected signal are studied as a function of time. A monostatic homodyne detection system with a response time of 10 ns is utilized to determine the amplitude and phase of the reflected wave. The peak plasma density is n e Ϸ4ϫ10 13 cm Ϫ3 , sufficiently above the critical density (n crit ϭ1.2ϫ10 12 cm Ϫ3 ) to produce reflections comparable to a conducting sheet placed in the same position as the plasma. A computer model is developed to interpret and optimize the plasma conditions which provide the highest backscatter and phase-stable reflection coefficient for the longest period of time. The presence of axial density gradients causes the reflected wave to be scattered through a wide angle. As the gradients relax, the backscatter reflection coefficient increases to a value of nearly 100%. The plasma density and two-body recombination coefficient are measured by means of microwave backscatter plasma reflectivity and Langmuir probes.
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