Ya-Qiu Jin

Electromagnetic scattering response from a uniaxial chiral cylinder by using cylindrical vector wave functions

Based on the concept of characteristic waves and the method of angular spectral expansion, eigenfunction expansion of the electromagnetic waves scattering in uniaxial chiral medium is derived in terms of the vector wave functions. It is revealed that the solution of the source-free vector wave equation for uniaxial chiral medium is composed of two transverse and a longitudinal wave. Numerical results for the electromagnetic scattering characteristics of the scatterer. On examining the frequency-dependence of the backward echo width, it is shown that the uniaxial chiral cylinder can be employed to construct reflection-reduction curved surface in a wide-band frequency.

Efficient TDFEM schemes with second-order PML based on different temporal basis functions

The time domain finite element method (TDFEM) formulations have been presented using two kinds of temporal basis functions, B-spline and Lagrange interpolation polynomial, and the computational domain is truncated with second-order perfectly matched layer (PML). This is motivated by utilising good interpolation features of these temporal basis functions and better absorption performances of second-order PMLs. Numerical cases demonstrate that the proposed TDFEM schemes achieve more accurate results with about 5% to 7% increase of run time and 1.5% increase of memory usage compared with the TDFEM scheme with Sacks PML. However, the presented TDFEM schemes merely require 1/6th of the total run time for frequency domain FEM.

Research on scattering and imaging simulation from the object and randomly rough surface

Research progress on electromagnetic (EM) scattering and imaging simulation from the volumetric object and randomly rough surface in Fudan University is briefly reported in this paper.

Bistatic Scattering from a 3D Target above Randomly Rough Surface

This paper presents a hybrid iterative algorithm of analytic Kirchhoff approximation (KA) and numerical method of moment (MoM) for scattering computation from a three-dimensional (3D) perfect conducting target above a randomly rough surface. The coupling integral equations (IEs) are derived based on the Greens function and the boundary conditions. The MoM with the conjugate gradient (CG) approach is used to solve the targets IE, and the KA is applied to scattering from the rough surface. The coupling iteration takes account the interactions between the target and the underlying rough surface. Convergence of the hybrid KA-MoM algorithm is numerically validated. Since is only one numerical integral of induced current on the target performed by KA computation, much memory and computation time is reduced. Bistatic scattering from a PEC cubic or spheroid target above a Gaussian rough surface are numerically simulated.

Reconstruction of the Building Objects from Multi-Aspect High-Resolution SAR Images

In this paper, an approach to the automatic reconstruction of 3D simple building objects from multi-aspect metric-resolution SAR images is proposed. The edge detector of constant false alarm rate (CFAR) and a parallel Hough transform technique are first employed to extract the parallelogram-like image of the building walls in SAR image. A set of probability density functions is presented to describe the extracted random wall-images and their multi-aspect coherence. Then the maximum-likelihood estimation of object is derived from its multi-aspect object-images. A hybrid priority criterion is defined to evaluate the reliability of reconstruction result, based on which, an automatic reconstruction algorithm is further devised to match object-images of different aspects and finally reconstruct the building objects. Four-aspect Pi-SAR images over Sendai, Japan are adopted for reconstruction. The results show the fidelity of the whole process chain and the feasibility of 3D objects automatic reconstruction from multi-aspect SAR images.

Electromagnetic scattering of a target with strong or weak coupled underlying oceanic surface: a FEM approach with FFT accelerated iterative robin boundary condition

To study electromagnetic scattering of a target at high altitude above rough oceanic surface, the iterative robin boundary condition (IRBC) is employed to separate and enclose two isolate regions of the target and underlying surface. The fields in these two enclosed regions are strongly or weakly coupled by iteratively solving the scattering field integral equation in the finite element method (FEM) with updating the right-hand side residual of the robin BC. Most time consuming of the algorithm is spent on evaluating the robin BC on the fictitious planar boundary over the large-scale rough surface. The scattering field integral equation is written as the 1D (one-dimensional) convolution form and is solved efficiently by using the fast Fourier transform (FFT). This study presents a numerical description for the scattering mechanism associated with strong or weak coupled interactions of a volumetric target at various altitudes above randomly rough surface.

Implementation of the periodic boundary condition in FDTD algorithm for scattering from randomly rough surface

The periodic boundary employed in Finite-Difference Time-Domain (FDTD) algorithm is applied to scattering simulation from a two-dimensional randomly rough surface. Comparing with the conventional windowing function, this approach takes less illuminated length of rough surface and improves computational efficiency especially for the problem of low grazing angle.

Correlated scattering and clustering of very dense random spherical particles using Monte-Carlo numerical realization

Monte Carlo (MC) numerical simulation has been applied to calculation of scattering and extinction coefficients k/sub s/, k/sub e/ and the effective propagation constant K of random dense particles. These discussions are based on the case for ice grains of snowpack with f/sub v/ < 0.4. However, correlated scattering from very dense random particles such as f/sub v/ > 0.4 has not been studied. In this paper, two MC methods (i.e. sequential addition method and random shuffling method) are adopted to generate randomly spatial positions of very dense spherical particles. Numerical approaches for calculations of k/sub s/, k/sub e/ and K for very dense particles f/sub v/ > 0.4 are developed. Numerical simulations show that random media of very dense particles demonstrate particles clustering and enhance scattering as bigger or clustered particles.

Polarized scattering from random clusters of spatially-oriented, non-spherical scatterers

Identification of atmospheric precipitation and different Earth surfaces and algorithms of the parameter retrieval have been extensively studied during the course of SSM/I calibration/validation effort. However, we have found that some conventional algorithms are not valid in many applications due to their empirical restriction. We have developed the vector radiative transfer modeling at SSM/I channels for Earth surfaces such as snow/vegetation, rough sea surface, scattering media of sea ice, etc., and derived several new algorithms from theoretical simulations to invert some parameters from SSM/I data. Our retrieval results and analysis are well compared with the ground truth data measurements.

VRT models for SSM/I channels and new algorithms for data calibration/validation

Identification of atmospheric precipitation and different Earth surfaces and algorithms of the parameter retrieval have been extensively studied during the course of SSM/I calibration/validation effort. However, we have found that some conventional algorithms are are not valid in many applications due to their empirical restriction. We have developed the vector radiative transfer modeling for SSM/I channels for Earth surfaces such as snow/vegetation, rough sea surface, scattering media of sea ice, etc., and derived several new algorithms from theoretical simulations to invert some parameters from SSM/I data. Our retrieval results and analysis compare well with the ground truth data measurements.