Local Incidence Angle Research Articles

Investigation of SOL plasma interaction with graphite PFC

Morphological changes of graphite plasma facing component (PFC) were investigated with various ion irradiation conditions which may change the sputtering yield and the scrape-off layer (SOL) plasma property. The experiments were carried out by using electron cyclotron resonance deuterium plasma with the conditions of electron density range of 2.5–3.5×1011cm−3, electron temperature range of 3.3–4.1eV, and ion energy range of 17–100eV. The graphite morphology was changed from plane to conical tip with increasing ion energy and dose. In addition, morphological changes increase the sputtering yield due to the increase of local angle of ion incidence. The inflow of hydrocarbon causes the increase of electron density and the decrease of electron temperature due to its higher dissociation and ionization rates than those of deuterium. This result suggests that the morphological changes of graphite should be considered in the SOL plasma interaction with graphite PFC.

DEM shading method for the correction of pseudoscopic effect on multi-platform satellite imagery

The pseudoscopic effect in satellite imagery causes perception problems for rugged terrain. The topographic relief is perceived in reverse in images with southeast illumination because of the position of land shadows and the mechanisms of human vision and depth perception. This article presents a correction method for false topographic perception phenomena. Superposition of the orthoimage and the correctly shaded digital elevation model (DEM) provides the correct three-dimensional visualization of the relief. This study demonstrates the applicability of this processing technique for the correction of such effects to provide cartography with a more useful interpretation. The resolution of the DEM employed should be in accordance with the spatial resolution of each image. The opacity level proposed for the overlapping DEM is 50%, 30% and 45% for each image type. The selection of the most appropriate local incidence angle is determined by the level of terrain roughness in the work area.

Baltic Sea Ice Concentration Estimation Based on C-Band Dual-Polarized SAR Data

High-resolution ice concentration information is required for navigation purposes, validating ice models, and data assimilation. The currently available operational ice concentration products are based on microwave radiometer data, and their typical resolution is several kilometers. We present an algorithm for the estimation of ice concentration based on dual-polarized (HH/HV) C-band synthetic aperture radar (SAR) data. The algorithm is based on the multilayer perceptron (MLP) neural network. Ice concentration estimated based on the HH channel is used as one MLP input, and the local incidence angle is used as another. The additional inputs are based on the HV channel. Digitized Finnish Ice Service ice charts, which were also used as the training data, the SAR-based HH-channel ice concentration, and the ice concentration based on a radiometer algorithm are used as reference data sets. The results for the dual-polarized algorithm show improvement compared to the algorithm based on HH-polarized SAR data only.

Impact of Topographic Correction on Estimation of Aboveground Boreal Biomass Using Multi-temporal, L-Band Backscatter

Synthetic aperture radar (SAR) has been shown to be a useful tool for estimating aboveground biomass (AGB), due to the strong correlation between the biomass and backscatter. In particular, L-band SAR is effective for estimating the lower range of biomass that characterizes most boreal forests. Unfortunately, the topographic impact on backscatter can dominate the normal forest signal variation. Since many boreal environments have significant topography, we investigate several topographic correction techniques to determine their effect upon AGB prediction accuracy. Different approaches to addressing the topography include: 1) no correction, 2) local incidence angle (LIA) correction, 3) pixel-area correction, and 4) a novel empirical slope correction. The investigation was performed for a data-rich experimental area near Tok, Alaska, for which Advanced Land Observing Satellite Phased Array type L-Band Synthetic Aperture Radar (ALOS PALSAR), field plots, lidar acquisitions, and a high-quality digital elevation model (DEM) existed. Biomass estimations were performed using both single- and dual-polarization (HH and HV) regressions against field plot data. The biomass estimation for each of the topographic corrections was compared with the field plot biomass, as well as more extensive lidar biomass estimations. The results showed a clear improvement in AGB estimation accuracy from no correction, to LIA, to pixel-area, to the novel pixel-area plus empirical slope correction. Using the field plot data for validation, the SAR root mean square error (RMSE) derived from the best approach was found to be 37.3 Mg/ha over a biomass range of 0-250 Mg/ha, only marginally less accurate than the 33.5 Mg/ha accuracy of the much more expensive lidar technique.

Stochastic Approach in Wet Snow Detection Using Multitemporal SAR Data

This paper introduces an alternative strategy for wet snow detection using multitemporal SAR data. The proposed change detection method is primarily based on comparison between two X band SAR images acquired during accumulation (winter) and melting (spring) seasons, in French Alps. The new decision criterion relies on local intensity statistics of SAR images by considering backscattering ratio as a stochastic process: probability that the intensity ratio fits into predetermined range of is larger than a defined confidence level. Both conducted snow backscattering simulations and state of art measurements indicate more complex relation between backscattering properties of two snow types, with respect to conventional assumption of augmented electromagnetic absorption associated to wet snow. Therefore, rather than adopting standard hypothesis, we analyse wet/dry snow backscattering ratio as a function of local incidence angle (LIA). After employing multi-layer snow backscattering simulator, calibrated with scatterometer measurements in C band, we modify, to some extent, range of ratio values indicating presence of wet snow, by including positive ratio values for lower LIA. By simultaneously accounting for speckle noise, proposed stochastic approach derives refined wet snow probability map. The performance analyses are carried out both through comparison with ground air temperature map and by comparing two co-polarized channels processed separately.

Local flux governing mechanism for the self-assembly of silver nanoparticles on ripple patterned templates

On ripple patterned substrates produced by ion beam sputtering, silver nanoparticles are successfully produced by using angular varied PVD electron beam evaporation method. Nanoparticle self-assembly is observed even in a non-shadow deposition region, though ripple pattern has a shallow modulation of ∼2 nm. Therefore, the contribution of the surface adatom diffusion kinetics and the local flux variation seems to be important for this self-assembly process. Due to lower incident flux and lower adatom energy PVD e-beam evaporation deposition method is proven to be superior to sputter deposition for the nanoparticles self-assembly. The self-assembly of nanoparticles is largely dependent on angle of incidence θ, rate of deposition, and deposition direction with respect to the surface topography. We propose the local flux variation model based on the ripple asymmetric tilt and the local incident angle which explains the self-assembly process nicely in terms of the nanoparticle size distribution. The optimum incident angles are calculated to be θ = ± 70° with respect to surface normal by using an analytical rippled surface model for the best alignment of nanoparticles as well as nanowires that are indeed obtained experimentally even though these angles are out of the shadow deposition regime.

Formation and evolution of ripples on ion-irradiated semiconductor surfaces

We have examined the formation and evolution of ripples on focused-ion-beam (FIB) irradiated compound semiconductor surfaces. Using initially normal-incidence Ga+ FIB irradiation of InSb, we tuned the local beam incidence angle (θeff) by varying the pitch and/or dwell time. For single-pass FIB irradiation, increasing θeff induces morphological evolution from pits and islands to ripples to featureless surfaces. Multiple-pass FIB irradiation of the rippled surfaces at a fixed θeff leads to island formation on the ripple crests, followed by nanorod (NR) growth. This ripple-NR transition provides an alternative approach for achieving dense arrays of NRs.

Discrimination of Water Surfaces, Heavy Rainfall, and Wet Snow Using COSMO-SkyMed Observations of Severe Weather Events

An automatic method to distinguish water surfaces (either flooded or permanent water bodies) from artifacts caused by heavy precipitation and wet snow is designed to improve flood detection accuracy in X-band synthetic aperture radar (SAR) images. The algorithm implementing the proposed method, mainly based on image segmentation techniques and on the fuzzy logic, consists of two principal steps: 1) detection of regions (or segments) of low-radar backscatter that appear dark in a SAR image, and 2) classification of each detected segment. Ancillary data, such as a local incidence angle map, a land cover map, and an optical image (helpful to detect wet snow), are also used. Through the fuzzy logic, the algorithm integrates different rules for the detection of dark areas, as well as for their classification based on radiometric, geometrical and shape features extracted from the segmented SAR image and on the ancillary data. The algorithm is tested on the COSMO-SkyMed imagery of the severe weather event that hit Northwest Italy on November 2011. A comparison with measured data, provided by the weather radars belonging to the Italian radar national network, and with the ground precipitation, forecasted by a numerical weather prediction model routinely used within the framework of the EUMETSAT Hydrology Satellite Application Facility project, indicates that the algorithm produces reliable classification maps, being able to distinguish the rainfall signature on X-band SAR images from that of flooded areas.

Polarimetric Properties of Burned Forest Areas at C- and L-Band

Fully polarimetric C- and L-band synthetic aperture radar (SAR) data have been investigated to determine the relationship between polarimetric target decomposition components and forest burn severity over two sites located in a Mediterranean environment. The dependence of the polarimetric decomposition metrics on SAR acquisition geometry and environmental conditions was also analyzed at C-band. Multiple linear regression models with interactions (i.e., the incidence angle was included as a predictor variable and its interaction with the radar metrics was accounted for as a multiplicative effect) were used to quantify burn severity retrieval accuracy. According to our experiment, we found that for steep SAR acquisition geometries C-band polarimetric components related to surface scattering mechanisms had increased sensitivity to burn severity levels, while for datasets acquired with more grazing geometries the polarimetric components related to volume scattering and dihedral scattering mechanisms were more correlated with burn severity levels. At L-band only volume and dihedral scattering related decomposition components provided significant relationships with burn severity levels. Relatively low burn severity estimation errors (less than 20% of burn severity range) were obtained for all datasets, with L-band data presenting the highest sensitivity to fire effects. Using a single regression model provided sufficient accuracy for burn severity estimation when taking into account the local incidence angle. The use of fully polarimetric data improved the estimation accuracy of forest burn severity with respect to backscatter intensities by a small margin for our study sites. However, since backscatter intensity metrics already provide high retrieval accuracies, whatever improvement was bound to be low.

The use of radar satellite data from multiple incidence angles improves surface water mapping

Satellite radar data has been employed extensively to monitor flood extents, where cloud cover often prohibits the use of satellite sensors operating at other wavelengths. Where total inundation occurs, a low backscatter return is expected due to the specular reflection of the radar signal on the water surface. However, wind-induced waves can cause a roughening of the water surface which results in a high return signal. Additionally, in arid regions, very dry sand absorbs microwave energy, resulting in low backscatter returns. Where such conditions occur adjacent to open water, this can make the separation of water and land problematic using radar. In the past, we have shown how this latter problem can be mitigated, by making use of the difference in the relationship between the incidence angle of the radar signal, and backscatter, over land and water. The mitigation of wind-induced effects, however, remains elusive. In this paper, we examine how the variability in radar backscatter with incidence angle may be used to differentiate water from land overcoming, to a large extent, both of the above problems.We carry out regression over multiple sets of time series data, determined by a moving window encompassing consecutively-acquired Envisat ASAR Global Monitoring Mode data, to derive three surfaces for each data set: the slope β of a linear model fitting backscatter against local incidence angle; the backscatter normalised to 30° using the linear model coefficients (σ300), and the ratio of the standard deviations of backscatter and local incidence angle over the window sample (SDR). The results are new time series data sets which are characterised by the moving window sample size.A comparison of the three metrics shows SDR to provide the most robust means to segregate land from water by thresholding. From this resultant data set, using a single step water–land classification employing a simple (and consistent) threshold applied to SDR values, we produced monthly maps of total inundation of the variable south-western basin of the Aral Sea through 2011, with an average pixel accuracy of 94% (kappa=0.75) when checked against MODIS-derived reference maps.

The potential of linear discriminative Laplacian eigenmaps dimensionality reduction in polarimetric SAR classification for agricultural areas

In this paper, the linear discriminative Laplacian eigenmaps (LDLE) dimensionality reduction (DR) algorithm is introduced to C-band polarimetric synthetic aperture radar (PolSAR) agricultural classification. A collection of homogenous areas of the same crop class usually presents physical parameter variation, such as the biomass and soil moisture. Furthermore, the local incidence angle also impacts a lot on the same crop category when the vegetation layer is penetrable with C-band radar. We name this phenomenon as the “observed variation of the same category” (OVSC). The most common PolSAR features, e.g., the Freeman–Durden and Cloude–Pottier decompositions, show an inadequate performance with OVSC. In our research, more than 40 coherent and incoherent PolSAR decomposition models are stacked into the high-dimensionality feature cube to describe the various physical parameters. The LDLE algorithm is then performed on the observed feature cube, with the aim of simultaneously pushing the local samples of the same category closer to each other, as well as maximizing the distance between local samples of different categories in the learnt subspace. Finally, the classification result is obtained by nearest neighbor (NN) or Wishart classification in the reduced feature space. In the simulation experiment, eight crop blocks are picked to generate a test patch from the 1991 Airborne Synthetic Aperture Radar (AIRSAR) C-band fully polarimetric data from of Flevoland test site. Locality preserving projections (LPP) and principal component analysis (PCA) are then utilized to evaluate the DR results of the proposed method. The classification results show that LDLE can distinguish the influence of the physical parameters and achieve a 99% overall accuracy, which is better than LPP (97%), PCA (88%), NN (89%), and Wishart (88%). In the real data experiment, the Chinese Hailaer nationalized farm RadarSat2 PolSAR test set is used, and the classification accuracy is around 94%, which is again better than LPP (90%), PCA (88%), NN (89%), and Wishart (85%). Both experiments suggest that the LDLE algorithm is an effective way of relieving the OVSC phenomenon.

A rectification model for lunar surface circular polarization ratio (CPR) images based on range-dependent incidence angle

Miniature Radio Frequency (Mini-RF) system is a synthetic aperture radar (SAR) onboard Lunar Reconnaissance Orbiter (LRO), with the principle objective to study lunar surface geophysical properties using the observed radar circular polarization ratio (CPR) at a fixed nominal incidence angle. However, it is noteworthy that, in most Mini-RF CPR images there are obvious CPR gradients along the range direction. For a typical S band CPR image with a swath width of 15 km, a systematical increase in CPR is generally between 0.2 and 0.3, and this will result in incorrect interpretations in CPR data deciphering. Further analyses show that CPR gradient is most probably caused by the increased incidence angle along range direction that was thought to be constant previously. To eliminate this incidence-angle-induced CPR gradient, three models were firstly proposed to fit CPR with respect to local incidence angle. Then, an incidence-angle-based CPR rectification model was presented for image correction. Experiment results for a region in the northern floor of Baillaud crater showed that our rectification model can effectively reduce the CPR gradient while retain its statistical characteristics. The proposed model in this study can be used to produce seamless CPR mosaics for large regions and help to better interpret the geophysical properties of the Moon.

Thermal barrier coating deposition by rarefied gas jet assisted processes: Simulations of deposition on a stationary airfoil

The uniform coating of a complex shaped substrate, such as a gas turbine airfoil, by collisionless physical vapor deposition processes requires rotation/translation of the substrate or sources and is inconceivable for regions on the substrate that are never in the line-of-sight of the vapor source. Recently developed directed vapor deposition processes use electron beam evaporation and inert gas jets to entrain, transport, and deposit metal oxide vapor in an environment where many vapor atom collisions occur prior to deposition. Direct simulation Monte Carlo simulations and experimental depositions of a rare earth modified thermal barrier coating are used to investigate fundamental aspects of the deposition process, including coating thickness and column orientation, over the surface of a nonrotated model airfoil substrate with substantial non-line-of-sight regions. The coating thickness uniformity was found to depend on the deposition chamber pressure and the pressure ratio between the low-pressure deposition chamber and high-pressure reservoir upstream of the gas jet forming nozzle. Under slow flow conditions, significant coating of the non-line-of-sight regions was possible. The growth column orientation is found to also vary over the substrate surface due to changes in the local incidence angle distribution of depositing vapor atoms. The variation in growth column orientation is not predictable by the Tangent rule widely used for predicting columnar growth orientation in physical vapor deposition processes.

Circular polarization ratio characteristics of impact craters from Mini‐RF observations and implications for ice detection at the polar regions of the Moon

In an attempt to reduce the ambiguity on radar detection of water ice at the permanently shadowed regions near the lunar poles, radar echo strength and circular polarization ratio (CPR) of impact craters are analyzed using the Miniature Radio Frequency (Mini‐RF) radar data from the Lunar Reconnaissance Orbiter mission. Eight typical craters, among over 70 craters, are selected and classified into four categories based on their locations and CPR characteristics: polar anomalous, polar fresh, nonpolar anomalous, and nonpolar fresh. The influences on CPR caused by surface slope, rocks, and dielectric constant are analyzed quantitatively using high‐resolution topography data and optical images. A two‐component mixed model for CPR that consists of a normal surface and a rocky surface is developed to study the effect of rocks that are perched on lunar surface and buried in regolith. Our analyses show that inner wall of a typical bowl‐shaped crater can give rise to a change of about 30° in local incidence angle of radar wave, which can further result in a CPR difference of about 0.2. There is a strong correlation between Mini‐RF CPR and rock abundance that is obtained from high‐resolution optical images, and predictions from the two‐component mixed model match well with the observed CPRs and the estimated rock abundances. Statistical results show that there is almost no apparent difference in CPR characteristics between the polar and nonpolar anomalous craters, or between the polar and nonpolar fresh craters. The enhanced CPR in the interior of anomalous craters is most probably caused by rocks that are perched on lunar surface or buried in regolith, instead of ice deposits as suggested in previous studies.

Experimental study of the organic ion intensity distribution in the ion imaging of coated polymer fibres with S-SIMS

Time-of-Flight Static Secondary Ion Mass Spectrometry excels in probing the molecular composition of the outer monolayer of flat samples with a lateral resolution in the sub-μm range. However, the method faces significant methodological problems in the case of non-conducting samples with high topography or surface curvature, such as fibres, yarns or fabrics. Specifically, the useful secondary ion yield in a given spot on the fibre depends on the local incidence angle, the height above the earthed sample holder, the position relative to the axis of the mass analyser and the extent of the local surface charging. This study has focused on the empiric reduction of the useful ion yield variations observed in the ion images of fibres with diameter of 25 and 100μm. Up to now, most literature data consider the analysis of fibres positioned along or perpendicular to the projection of the projectile beam in the plane of the sample surface because these specific geometries facilitate the interpretation of the ion images. However, it has been discovered that the diagonal orientation of the fibre in the field-of-view largely reduces the ion yield variations for fibres with a small diameter (25μm). The situation is different for fibres with a diameter of 100μm. In that case, the ion images contain no secondary ion counts for the pixels referring to a significant part of the fibre. In particular, the resulting lack of delineation between the shadow zone in the front of the fibre and the boundary of the fibre hampers the practical use of the ion images A fourfold decrease of the extraction voltage or a 20% increase of the distance between sample holder and extraction electrode is found to improve the detection of secondary ions from the part of the fibre facing towards the impinging primary ion beam. These observations have been tentatively related to the mass analyser acceptance and its dependence on the delicate balance between conflicting effects such as field strength and curvature of the field lines, secondary ion emission angle and initial kinetic energy and difference in local surface potential due to the position in the extraction field and charge build-up during analysis.

Assessment of the Accuracy of SRTM C- and X-Band High Mountain Elevation Data: a Case Study of the Polish Tatra Mountains

Global digital elevation models (DEMs) are an invaluable source of information in large area studies. Of particular interest are shuttle radar topography mission (SRTM) data that are freely available for the scientific community worldwide. Prior to any application, global datasets should be evaluated using reference data of higher accuracy. Therefore, the main objective of this study was to assess the accuracy of the SRTM C-band (version 4) DEM and SRTM X-band DEM of mountainous areas located in Poland and to examine the quality of data in relation to topographic parameters, radar beam geometry, initial voids in data and the presence of forest cover. A DEM from the Central National Geodetic and Cartographic Inventory, Poland, served as a reference. The study consisted of three steps: (i) the computation of vertical errors of the SRTM C- and X-band DEMs, (ii) the examination of any systematic bias in the data, and (iii) the analysis of the relationships between the elevation errors and terrain slope, aspect, local incidence angle, occurrence of voids and land cover. We found that the SRTM C- and X-band DEMs have mean errors equal to 4.31 ± 14.09 and 9.03 ± 37.40 m and root mean square errors equal to 14.74 and 38.47 m, respectively. Only 82 % of the C-band DEM and 74 % of the X-band DEM vertical errors had absolute values below 16 m. We found that the most important factors determining the occurrence of high errors were the distribution of initial voids and high slope angles for the C-band DEM, and local incidence angle, slope, aspect and radar beam geometry for the X-band DEM. In both cases, the presence of forest cover increased the mean error by approximately 10 m.

Angle Independence Properties of Fractal Dimension Maps Estimated From SAR Data

The extremely remarkable properties of angle independence exhibited by an innovative SAR product, the fractal dimension map estimated from a single SAR image, are discussed. The theoretical analysis is supported by a noticeable data set of actual SAR images acquired, with look angles varying from 20° to 45°, in the stripmap operational mode by the COSMO-SkyMed constellation. The behavior of the fractal dimension maps at different look angles is discussed for both natural and urban scenarios and emphasis is also posed on areas within the same image that, according to the scene macroscopic topography, are characterized by different incidence angles. The whole analysis is aimed at highlighting, on the one hand, the specific independencies of natural surface fractal dimension maps from the look angle and from the local incidence angle, which can be very useful in information extraction and SAR post-processing techniques and, on the other hand, the different fractal dimension maps behavior whereas urban areas are analyzed.

Impact of the 24 September 2011 solar radio burst on the performance of GNSS receivers

Intense solar radio bursts occurring at the L‐band frequencies can significantly impact the performance of Global Navigation Satellite System (GNSS) receivers in the sunlit hemisphere of the Earth. An intense solar radio burst occurred on 24 September 2011, with a maximum power of 110,000 solar flux units (10−22 W/m2/Hz) at 1.415 GHz. This manuscript aims to contribute insight on the impact of this solar radio burst on the performance of the GNSS receivers in the European and Latin American sectors. Maximum reductions of 11.0, 22.0, and 10.0 dB Hz in the carrier‐to‐noise density ratio (C/N0) of the GPS L1C/A, L2P, and L2C signals, respectively, were observed. The C/N0 reduction is modulated by the local solar incidence angle for the GPS L1C/A and L2P signals, whereas such modulation was not observed for the GPS L2C signal. The solar radio burst also had an adverse effect on the recorded GNSS pseudorange and carrier phase data, thereby causing positioning errors, which are also presented herein.

Relationship of local incidence angle with satellite radar backscatter for different surface conditions

This paper examines the relationship of C-band radar backscatter from the Advanced Synthetic Aperture Radar on board the ENVISAT satellite with the local angle of incidence, whose influence on the received signal is significant, particularly in the modes of sensor operation that use the full swath of the orbit track. Linear regression is carried out for each pixel throughout a large time series of radar data over the whole of the state of Queensland, Australia, and at Great Salt Lake, Utah, USA. In the first case, the resultant coefficients are analysed for correlation against various parameters, with regolith showing the highest correlation. Class separability analysis shows the potential to use the resultant coefficients as a supplement to absolute threshold values in order to distinguish between classes of vegetation and/or geology, where cloud cover may preclude the use of optical data. It is observed that the separability between water and land is greatly higher using the slope coefficient B than using backscatter σ0, which may be of great benefit in the remote sensing of water where cloud cover is present (from which radar is largely independent). This is especially the case when considering the observed overlapping of backscatter values from water, with values from aeolian sand and lacustrine and alluvial sediments, rendering the use of backscatter alone problematic. In order to test the potential use of B to map water extents, the study over the Great Salt Lake compares the classification accuracy of B against that of σ0. It is found that the σ0 classification misrepresents desert, salt flat and dry lake basin areas, where the B classification differentiates these regions accurately. The resultant classification achieves a kappa statistic around 0.9, which shows very high conformance. An accurate and novel method to classify water is therefore demonstrated, which awaits the launch of anticipated improved synthetic aperture radar instruments on satellite missions in the coming few years.

GUIDED-MODE RESONANCE FILTER COMPENSATED TO OPERATE ON A CURVED SURFACE

Guided-mode resonance fllters (GMRFs) are highly compact structures that can produce a strong frequency response from a single thin layer of dielectric. When a GMRF is formed onto a curved surface, the local angle of incidence varies over the aperture of the device and the overall performance signiflcantly degrades. In the present work, we spatially varied the grating period of a curved GMRF to perfectly compensate for the local angle of incidence. The performance of our curved device actually surpassed that of our ∞at device because it also compensated for the spherical wave front from the source. This paper summarizes our design process and experimental results obtained around 25GHz.