Light scattering from self-affine fractal silver surfaces with nanoscale cutoff: Far-field and near-field calculations

We study the light scattered from randomly rough, one-dimensional self-affine fractal silver surfaces with nanoscale lower cutoff, illuminated by s- or p-polarized Gaussian beams a few microns wide. By means of rigorous numerical calculations based on the Green theorem integral equation formulation, we obtain both the far- and near-field scattered intensities. The influence of diminishing the fractal lower scale cutoff (from below a hundred, down to a few nanometers) is analyzed in the case of both single realizations and ensemble average magnitudes. For s polarization, variations are small in the far field, being only significant in the higher spatial frequency components of evanescent character in the near field. In the case of p polarization, however, the nanoscale cutoff has remarkable effects stemming from the roughness-induced excitation of surface-plasmon polaritons. In the far field, the effect is noticed both in the speckle pattern variation and in the decrease of the total reflected energy upon ensemble averaging, due to increased absorption. In the near field, more efficient excitation of localized optical modes is achieved with smaller cutoff, which in turn leads to huge surface electric field enhancements.Comment: REVTeX 4, 10 page

On the Indicatrixes of Waves Scattering from the Random Fractal Anisotropic Surface

Millimeter and centimeter wave scattering from the random fractal anisotropic surface has been theoretically investigated. Designing of such surfaces is based on the modifications of non-differentiable two-dimensional Weierstrass function. Wave scattering on a random surface is interesting for many sections of physics, mathematics, biology, and so on. Questions of a radar location and radio physics take the predominating position here. There are many real surfaces and volumes in the nature that can be carried to fractal objects. At the same time, the description of processes of waves scattering of fractal objects differs from classical approaches markedly. There are many monographs in the world on the topic of classical methods of wave scattering but the number of books devoted to waves scattering on fractal stochastic surfaces is not enough. These results of estimation of three-dimensional scattering functions are a priority in the world and are important in radar of low-contrast targets near the surface of the earth and the sea

Characterization of Rough Fractal Surfaces from Backscattered Radar Data

In this paper the scattering of electromagnetic (EM) waves, emitted by a monostatic radar, from rough fractal surfaces is examined by using the Kirchhoff approximation. Of particular interest here is the way that the level of roughness of the fractal surface affects the backscattered EM wave captured by a synthetic aperture radar (SAR) and whether the roughness of the surface can be estimated from these SAR radar measurements. More specifically, the scattering coefficient of the backscattered signal is calculated for a number of radar frequencies and for different values of the surface fractal dimension. It is found here that the slopes between the main lobe and the first sidelobes emerging in the backscattering coefficient as a function of the wavenumber of the incident EM waves increase with the surface fractal dimension. Therefore, we conclude in this paper that the magnitude of the above slopes provides a reliable method for the classification of the rough fractal surfaces. Applications of the proposed method can be found, for example, in the characterization of the sea state from measured SAR radar data

gprMax: open source software to simulate electromagnetic wave propagation for Ground Penetrating Radar

AbstractgprMax is open source software that simulates electromagnetic wave propagation, using the Finite-Difference Time-Domain (FDTD) method, for the numerical modelling of Ground Penetrating Radar (GPR). gprMax was originally developed in 1996 when numerical modelling using the FDTD method and, in general, the numerical modelling of GPR were in their infancy. Current computing resources offer the opportunity to build detailed and complex FDTD models of GPR to an extent that was not previously possible. To enable these types of simulations to be more easily realised, and also to facilitate the addition of more advanced features, gprMax has been redeveloped and significantly modernised. The original C-based code has been completely rewritten using a combination of Python and Cython programming languages. Standard and robust file formats have been chosen for geometry and field output files. New advanced modelling features have been added including: an unsplit implementation of higher order Perfectly Matched Layers (PMLs) using a recursive integration approach; diagonally anisotropic materials; dispersive media using multi-pole Debye, Drude or Lorenz expressions; soil modelling using a semi-empirical formulation for dielectric properties and fractals for geometric characteristics; rough surface generation; and the ability to embed complex transducers and targets.Program summaryProgram title: gprMaxCatalogue identifier: AFBG_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AFBG_v1_0.htmlProgram obtainable from: CPC Program Library, Queen’s University, Belfast, N. IrelandLicensing provisions: GNU GPL v3No. of lines in distributed program, including test data, etc.: 627180No. of bytes in distributed program, including test data, etc.: 26762280Distribution format: tar.gzProgramming language: Python.Computer: Any computer with a Python interpreter and a C compiler.Operating system: Microsoft Windows, Mac OS X, and Linux.RAM: Problem dependentClassification: 10.External routines: Cython[1], h5py[2], matplotlib[3], NumPy[4], mpi4py[5]Nature of problem: Classical electrodynamicsSolution method: Finite-Difference Time-Domain (FDTD)Running time: Problem dependentReferences:[1]Cython, http://www.cython.org[2]h5py, http://www.h5py.org[3]matplotlib, http://www.matplotlib.org[4]NumPy, http://www.numpy.org[5]mpi4py, http://mpi4py.scipy.or

Brine percolation and the transport properties of sea ice

Journal ArticleSea ice is distinguished from many other porous composites, such as sandstones or bone, in that its microstructure and bulk material properties can vary dramatically over a small temperature range. For brine-volume fractions below a critical value of about 5%, which corresponds to a critical temperature of about -5oC for salinity of 5 ppt, columnar sea ice is effectively impermeable to fluid transport

Imaging Of Perfectly Magnetic Conducting Rough Surface Through Single Frequency Single View Data

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2008Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2008Bu çalışmada, manyetik iletkenlik özelliğine sahip bir yüzeye ait ters problem çözümü sunularak, cismin şeklinin ve elektriksel özelliklerinin bulunması için yeni ve hızlı bir metot verilmiştir. Öngörülen sistemde, yüzeyden saçılan elektromanyetik dalgalar yüzeyden yukarıda bir düzlem boyunca ölçülür. Kullandığımız yöntemde ölçün yapılan uzayla, bulunması hedeflenen yüzeyin arası varsayımsal bir düzlemle iki yarım uzaya bölünür. Üst kısımda kalan her noktadaki saçılma, Fourier transformu ifadesiyle tanımlanır. Daha sonra manyetik iletkenlik özelliğine sahip bir yüzeydeki sınır koşulları kullanılarak problem lineer olmayan bir denkleme indirgenirThe main aim of this thesis is to give a new, simple and fast method to determine the location and shape of a perfectly magnetic conducting rough surface. The surface is reconstructed using the illumination by a single plane monochromatic wave and the near field measurements of the scattered field are performed on a line parallel to the mean surface. The novelty of the method is that the lossy half-space above the surface is first separated into two parts by an estimated plane, and then the scattered field in the upper region above this plane is expressed in terms of a Fourier transform while it is expanded into a Taylor series in the lower part. The boundary condition on the Perfect Magnetic Conductive surface requires that the normal derivative of the total electric field should vanish. The use of this condition allows the reduction of the problem to the solution of a non-linear equation for the unknown surface function.Yüksek LisansM.Sc

Theoretical and experimental models of the diffuse radar backscatter from Mars

The general objective for this work was to develop a theoretically and experimentally consistent explanation for the diffuse component of radar backscatter from Mars. The strength, variability, and wavelength independence of Mars' diffuse backscatter are unique among our Moon and the terrestrial planets. This diffuse backscatter is generally attributed to wavelength-scale surface roughness and to rock clasts within the Martian regolith. Through the combination of theory and experiment, the authors attempted to bound the range of surface characteristics that could produce the observed diffuse backscatter. Through these bounds they gained a limited capability for data inversion. Within this umbrella, specific objectives were: (1) To better define the statistical roughness parameters of Mars' surface so that they are consistent with observed radar backscatter data, and with the physical and chemical characteristics of Mars' surface as inferred from Mariner 9, the Viking probes, and Earth-based spectroscopy; (2) To better understand the partitioning between surface and volume scattering in the Mars regolith; (3) To develop computational models of Mars' radio emission that incorporate frequency dependent, surface and volume scattering

Quantitative Estimation of Surface Soil Moisture in Agricultural Landscapes using Spaceborne Synthetic Aperture Radar Imaging at Different Frequencies and Polarizations

Soil moisture and its distribution in space and time plays an important role in the surface energy balance at the soil-atmosphere interface. It is a key variable influencing the partitioning of solar energy into latent and sensible heat flux as well as the partitioning of precipitation into runoff and percolation. Due to their large spatial variability, estimation of spatial patterns of soil moisture from field measurements is difficult and not feasible for large scale analyses. In the past decades, Synthetic Aperture Radar (SAR) remote sensing has proven its potential to quantitatively estimate near surface soil moisture at high spatial resolutions. Since the knowledge of the basic SAR concepts is important to understand the impact of different natural terrain features on the quantitative estimation of soil moisture and other surface parameters, the fundamental principles of synthetic aperture radar imaging are discussed. Also the two spaceborne SAR missions whose data was used in this study, the ENVISAT of the European Space Agency (ESA) and the ALOS of the Japanese Aerospace Exploration Agency (JAXA), are introduced. Subsequently, the two essential surface properties in the field of radar remote sensing, surface soil moisture and surface roughness are defined, and the established methods of their measurement are described. The in situ data used in this study, as well as the research area, the River Rur catchment, with the individual test sites where the data was collected between 2007 and 2010, are specified. On this basis, the important scattering theories in radar polarimetry are discussed and their application is demonstrated using novel polarimetric ALOS/PALSAR data. A critical review of different classical approaches to invert soil moisture from SAR imaging is provided. Five prevalent models have been chosen with the aim to provide an overview of the evolution of ideas and techniques in the field of soil moisture estimation from active microwave data. As the core of this work, a new semi-empirical model for the inversion of surface soil moisture from dual polarimetric L-band SAR data is introduced. This novel approach utilizes advanced polarimetric decomposition techniques to correct for the disturbing effects from surface roughness and vegetation on the soil moisture retrieval without the use of a priori knowledge. The land use specific algorithms for bare soil, grassland, sugar beet, and winter wheat allow quantitative estimations with accuracies in the order of 4 Vol.-%. Application of remotely sensed soil moisture patterns is demonstrated on the basis of mesoscale SAR data by investigating the variability of soil moisture patterns at different spatial scales ranging from field scale to catchment scale. The results show that the variability of surface soil moisture decreases with increasing wetness states at all scales. Finally, the conclusions from this dissertational research are summarized and future perspectives on how to extend the proposed model by means of improved ground based measurements and upcoming advances in sensor technology are discussed. The results obtained in this thesis lead to the conclusion that state-of-the-art spaceborne dual polarimetric L-band SAR systems are not only suitable to accurately retrieve surface soil moisture contents of bare as well as of vegetated agricultural fields and grassland, but for the first time also allow investigating within-field spatial heterogeneities from space

Electromagnetic modeling for SAR polarimetry and interferometry

Investigation of the globe remotely from hundreds of kilometers altitude, and fast growing of environmental and civil problems, triggered the necessity of development of new and more advanced techniques. Electromagnetic modeling of polarimetry and interferometry has always been a key driver in remote sensing research, ever since of the First pioneering sensors were launched. Polarimetric and interferometric SAR (Synthetic Aperture Radar) surveillance and mapping of the Earth surface has been attracting lots of interest since 1970s. This thesis covers two SAR's main techniques: (1) space-borne Interferometric Synthetic Aperture Radar (InSAR), which has been used to measure the Earth's surface deformation widely, and (2) SAR Polarimetry, which has been used to retrieve soil and vegetation physical parameters in wide areas. Time-series InSAR methodologies such as PSI (Permanent Scatterer Interferometry) are designed to estimate the temporal characteristics of the Earth's deformation rates from multiple InSAR images acquired over time. These techniques also enable us to overcome the limitations that conventional InSAR suffer, with a very high accuracy and precision. In this thesis, InSAR time-series analysis and modeling basis, as well as a case study in the Campania region (Italy), have been addressed. The Campania region is characterized by intense urbanization, active volcanoes, complicated fault systems, landslides, subsidence, and hydrological instability; therefore, the stability of public transportation structures is highly concerned. Here Differential Interferometric Synthetic Aperture Radar (DInSAR), and PSI techniques have been applied to a stack of 25 X-band radar images of Cosmo-SkyMed (CSK) satellites collected over an area in Campania (Italy), in order to monitor the railways' stability. The study area was already under investigation with older, low-resolution sensors like ERS1&2 and ENVISAT-ASAR before, but the number of obtained persistent scatterers (PSs) was too limited to get useful results. With regard to SAR polarimetry, in this thesis a fully polarimetirc SAR simulator has been presented, which is based on the use of sound direct electromagnetic models and it is able to provide as output the simulated raw data of all the three polarization channels in such a way as to obtain the correct covariance or coherence matrixes on the final focused polarimetic radar images. A fast Fourier-domain approach is used for the generation of raw signals. Presentation of theory is supplemented by meaningful experimental results, including a comparison of simulations with real polarimetric scattering data

Digital Image Processing

Newspapers and the popular scientific press today publish many examples of highly impressive images. These images range, for example, from those showing regions of star birth in the distant Universe to the extent of the stratospheric ozone depletion over Antarctica in springtime, and to those regions of the human brain affected by Alzheimer’s disease. Processed digitally to generate spectacular images, often in false colour, they all make an immediate and deep impact on the viewer’s imagination and understanding. Professor Jonathan Blackledge’s erudite but very useful new treatise Digital Image Processing: Mathematical and Computational Methods explains both the underlying theory and the techniques used to produce such images in considerable detail. It also provides many valuable example problems - and their solutions - so that the reader can test his/her grasp of the physical, mathematical and numerical aspects of the particular topics and methods discussed. As such, this magnum opus complements the author’s earlier work Digital Signal Processing. Both books are a wonderful resource for students who wish to make their careers in this fascinating and rapidly developing field which has an ever increasing number of areas of application. The strengths of this large book lie in: • excellent explanatory introduction to the subject; • thorough treatment of the theoretical foundations, dealing with both electromagnetic and acoustic wave scattering and allied techniques; • comprehensive discussion of all the basic principles, the mathematical transforms (e.g. the Fourier and Radon transforms), their interrelationships and, in particular, Born scattering theory and its application to imaging systems modelling; discussion in detail - including the assumptions and limitations - of optical imaging, seismic imaging, medical imaging (using ultrasound), X-ray computer aided tomography, tomography when the wavelength of the probing radiation is of the same order as the dimensions of the scatterer, Synthetic Aperture Radar (airborne or spaceborne), digital watermarking and holography; detail devoted to the methods of implementation of the analytical schemes in various case studies and also as numerical packages (especially in C/C++); • coverage of deconvolution, de-blurring (or sharpening) an image, maximum entropy techniques, Bayesian estimators, techniques for enhancing the dynamic range of an image, methods of filtering images and techniques for noise reduction; • discussion of thresholding, techniques for detecting edges in an image and for contrast stretching, stochastic scattering (random walk models) and models for characterizing an image statistically; • investigation of fractal images, fractal dimension segmentation, image texture, the coding and storing of large quantities of data, and image compression such as JPEG; • valuable summary of the important results obtained in each Chapter given at its end; • suggestions for further reading at the end of each Chapter. I warmly commend this text to all readers, and trust that they will find it to be invaluable. Professor Michael J Rycroft Visiting Professor at the International Space University, Strasbourg, France, and at Cranfield University, England