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This research study focuses on the development of a forward model to understand the scattering of electromagnetic waves from layered rough surfaces with buried discrete random media, specifically for subsurface and root-zone soil moisture sensing. The study aims to explore the impact of root structures and other inhomogeneities on backscattering cross-section evaluation.
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Vector Electromagnetic Scattering from Layered Rough Surfaces with Buried Discrete Random Mediafor Subsurface and Root-Zone Soil Moisture Sensing Xueyang Duan and Mahta Moghaddam Radiation Laboratory, Dept. of EECS, University of Michigan IGARSS, Vancouver, Canada, July 24 – 29, 2011
Outline • Motivation and Background • Problem Description • Formulation • Model Validation • Simulation results • Conclusion and Future Work
Motivation and Background • Ground subsurface sensing is a high-priority topic in microwave remote sensing, where we focus on soil: • Monitoring facility constructions • Landslide warning • Locating the permafrost depth • Mapping the soil moisture profile • Low frequency radar systems receive scattering from both subsurfaces and sublayer inhomogeneities, e.g. vegetation roots, rocks, ice particles. Es Ei A forward model of scattering from discrete random media representing the root structures and other inhomogeneities is required to study their impact on the evaluation of backscattering cross section.
Significant Contribution • In the past investigations: • 3D single or multilayer rough surface scattering model without considering sublayer inhomogeneities • No 3D full wave solution to random media scattering, especially with rough surfaces • In this work: • First time to include the sublayer inhomogeneities, especially vegetation roots, in the subsurface scattering model • 3D full wave solution to scattering from discrete random media, especially root-like clusters, with rough surface
Problem Description • Simulate the roots: • Root of an individual plant can be simulated as cylinders distributed with certain patterns. Ei Region 1 • For a vegetated area with multiple plants, roots are modeled as layers of randomly arranged cylinders, whose sizes and orientations follow statistical distributions. Surface 1 Region 2 Surface 2 Region 3
Problem Description (cont.) • The inhomogeneities can be modeled • as collections of regular-shaped • or irregular-shaped scatterers: • background: • spherical scatterers: - radius - center location - dielectric property - length and radius - dielectric property - cylinder center location: - cylinder orientation: - cylinder axis: • cylindrical scatterers: • Randomly distributed within each layer • Solution Strategy: • Transition matrix (T-matrix): • spherical wave basis, for volumetric scattering S-matrix of random media is required • Scattering matrix (S-matrix): • plane wave basis, for layered problem
Formulation Overview of approach: • Random media of sphericalscatterers: • Obtain single sphere T-matrix analytically • Solve multiple sphere scattering using recursive T-matrix method • Obtain S-matrix from T-matrix to S-matrix transformation • Random media of cylindricalscatterers or cylindrical clusters: • Decompose the cylindrical cluster to cascaded short sub-cylinders • Solve single short cylinder T-matrix using extended boundary condition method (EBCM) • Solve T-matrix of random or root-like cylindrical cluster using generalized iterative EBCM and incident field variation • Obtain S-matrix from T-matrix to S-matrix transformation
Formulation – single scatterer T-matrix • T-matrix of a single scatterer: • T-matrix of single spherical scatterer is from Mie-scattering coef.: • T-matrix of single cylindrical scatterer is from extended boundary condition method: , , and are similar as the above formulation with different spherical harmonics.
Formulation – aggregate T-matrix (spheres) • Scattering from discrete random media is solved using the recursive T-matrix method • Basic idea: include one scatterer at a time into the cluster, and solve the new T-matrix including interaction between the added scatterer and the rest • Using Addition theorem and translational matrices: Where and are translational matrices • The aggregate T-matrix is computed recursively,
Formulation – Generalized iterative EBCM (cylindrical clusters) • Limitations when considering cylindrical structures representing roots: • Knowing the T-matrices of all sub-cylinders, scattered field from N sub-cylinders is obtained from iterative procedure: • EBCM: not valid for cylindrical scatterer with large length-to-diameter ratio • Recursive T-matrix method: external circumscribed circles of the scatterers must be exclusive • [1]: only valid for vertically oriented long cylinder • Our work: generalized to 3D randomly arranged cylinders • The long cylinder or cylindrical cluster can be treated as cascaded sub-cylinders. • Iteration starts assuming no field interaction among sub-cylinders • Compute scattered field and update the exciting field on every sub-cylinder • Repeat till the scattering coefficients of all sub-cylinders converge 2 1 • Field interactions among sub-cylinders need coordinates transformation using Addition theorem Generalized iterative EBCM • Total scattered field is the superposition of scattered fields from all sub-cylinders transformed to the main frame. [1]W.Z.Yan, Y.Du, D.Liu, and B.I.Wu, EM scattering from a long dielectric circular cylinder, PIERS, Vol. 85, pp. 39-67, 2008.
Formulation – Generalized iterative EBCM (cylindrical clusters) • 3D coordinates translation is implemented using rotation with z-axis translation. Euler angles are, Where (x’,y’,z’) denotes the coordinates after 1st rotation, and • T-matrix of the overall cluster:
Formulation – T matrix to S matrix transformation • Scattering matrix is obtained from multipole expansion of plane wave and numerical plane wave expansion of spherical harmonics with near-to-far field transformation. [1] • Transformation: incident plane wave to spherical harmonics, using multipole expansion and • Addition theorem • Each row ( ) of matrix P corresponds to a given direction of incidence. • Numerical plane wave expansion of vector spherical wave => • non-trivial ! • when , where is an integer relaxation constant, and is the number of truncated terms in the expansion [MacPhie and Wu, 2003], • - practically computable in near-field only • Near-to-far field transformation • S-matrix can be obtained from the T-matrix as [1] X. Duan and M. Moghaddam, ‘3D Electromagnetic Scattering from Discrete Random Media Comprising Long Finite-Length Cylinders and Root-like Cylinder Clusters’, APS&URSI, Spokane, WA, July 3 – 8, 2011.
Model Validation – Experiment Setup • Vector Network Analyzer and switching matrix based • measurement system. • freq: 2.2 GHz – 2.8 GHz • 1 transmitter and 14 receivers mounted on an octagon • ‘E’-shape wideband patch antennas • Rotation platform in the center y x • Measurement objects: • PEC/dielectric spheres: dia. 1” • PEC cylinders: length of 2” and 3”, diameter of 3/8, 5/8, 13/16 inches • positioned ‘randomly’
Model Validation – Simulation • Antenna Model [1]: relating the vector fields and S-parameters measured • Propagation Model: computing the transmission parameter Sji between • antennas j and i in the presence of object. With Addition theorem, RX Antenna TX Antenna • The cylindrical cluster T-matrix is computed from cascading half-inch sub-cylinder. [1]Haynes, M., and M. Moghaddam, “Multipole and S-parameter based antenna model,” IEEE Trans. Antennas Propagat., vol. 59, no. 1, pp. 225-235, January 2011
Model Validation – PEC spheres • Measurement of 3D ‘randomly’ arrangedPEC spheres • Comparison between predicted and measured scattering parameters at 14 receivers for HH and VV.
Model Validation – PEC cylinders • Measurement of 3D ‘randomly’ arrangedPEC cylinders (dia. 5/8 inch) • Comparison between predicted and measured scattering parameters at 14 receivers for HH and VV. • The amplitude comparisons show some agreements; better agreements in phase can be observed. VV HH
Simulation results for single rough surface above random spheres • Enhancement in all scattered field components, especially crosspol component
Simulation results for single rough surface above random cylinders • Enhancement in all scattered field components, especially crosspol component
Tree Root model • Tree root facts: depending on the soil conditions, • 85% tree roots are within the top 0.5 m of soil • Usually the roots extend the range of one (at least) to three times of the radius of the canopy spread or two or three times the height of the tree. • implemented tree root model: • Model parameters: • Depth of the root zone; • Horizontal range of the root zone; • Trunk diameter : assumed to be the upper end of cylinders • Distribution: • Azimuth plane: uniformly distributed roots at • Elevation plane: N cylinders in every root group, with elevation angle • Lower end is at Reference: Dennis S. Schrock, ‘How to Prevent construction Damage’, University of Missouri Extension, 2000. • In this model, determines the root density, which in reality depends on soil moisture.
Simulation results for single rough surface above one single root • Enhancement is small in copol components, but large in crosspol component
Simulation results for single rough surface above multiple roots • Enhancement is small in copol components, but large in crosspol component
Conclusion and Future Work In this work, we showed: • Solution to scattering from randomly arranged spherical scatterers • Solution to scattering from randomly arranged cylindrical clusters that can be used to represent root structures • Experimental validation of the scattering model of discrete random media of both spherical and cylindrical scatterers • Simulations results of single rough surface with buried random media or simplified roots • The presence of roots can significantly impact overall scattering cross section from the subsurface, especially in cross-pol • Root geometry, density, and dielectric properties have strong impact on the scattering cross section. Future work: • Further integration of the discrete random media model with multilayer rough surface model, soil moisture profile, and above-ground vegetation • Use in root-zone soil moisture retrieval
Acknowledgement • Measurement setup from Mark Haynes and Steven Clarkson Thank you ! Question?