Ji-Fu Ma

Analysis of multiple FSS screens of unequal periodicity using an efficient cascading technique

In this paper, we present an efficient cascading procedure for analyzing frequency selective surface (FSS) systems consisting of multiple FSS screens of unequal periodicity embedded in multiple dielectric layers. In this procedure, we first find a global period for the FSS system by studying the composite in its entirety. Next, we compute the scattering matrix [S] of each of the FSS subsystems for the global Floquet harmonics by applying a relationship we establish that maps the [S] matrix of the subsystem for the individual Floquet harmonics to that for the global harmonics. This mapping-cum-filling process substantially reduces the effort needed to compute the [S] matrix of a subsystem. Finally, we compute the [S] of the entire system by applying a modified cascading formulation, in which one matrix inversion step is eliminated, resulting in a reduction in the total computing resource requirement as well as time. Two numerical examples are given to illustrate the efficiency and effectiveness of the technique.

CBMOM - an iteration free MoM approach for solving large multiscale EM radiation and scattering problems

Numerical solutions of electromagnetic radiation and scattering using the MoM are limited in their application to moderately-sized objects (in terms of wavelength) only, because of the CPU memory and execution time required by the method when dealing with larger structures. Researchers have explored ways to circumvent these problems. Most of these methods rely upon iteration methods, and this can lead to convergence difficulties. In contrast, the CBMOM significantly differs from these approaches in several aspects. First, the technique is more general. Second, it includes mutual coupling effects rigorously, and yet reduces the number of degrees of freedom (DOFs) dramatically. Third, it uses a new type of high-level basis functions, referred to as characteristic basis functions (CBFs), which are used to represent the unknown induced current. The use of CBFs enables us to bypass iteration methods altogether. The paper gives some examples of multiscale problems which can be solved by CBMOM.

Detection of buried dielectric cavities using the finite-difference time-domain method in conjunction with signal processing techniques

We address the problem of detecting low-dielectric contrast cavities buried deep in a lossy ground by using the finite-difference time-domain (FDTD) method in conjunction with signal processing techniques for extrapolation and object identification. It is well known that very low frequency probing is needed for deep penetration into the lossy ground, owing to a rapid decay of electromagnetic (EM) waves at higher frequencies. It is also recognized that numerical modeling using the FDTD method becomes very difficult, if not impossible, when the operating frequency becomes as low as 1 Hz. To circumvent this difficulty, we propose a hybrid approach in this paper that combines the FDTD method with signal processing techniques, e.g., rational function approximation and neural networks (NNs). Apart from the forward problem of modeling buried cavities, we also study the inverse scattering problem-that of estimating the depth of a buried object from the measured field values at the surface of the Earth or above. Numerical results for a buried prism are given to illustrate the application of the proposed technique.

Solving Large Body of Revolution (BOR) problems using the Characteristic Basis Function Method and the FFT-based Matrix Generation

The recently-developed characteristic basis function method (CBFM) is used in conjunction with the fast Fourier transform (FFT) for matrix generation to improve the efficiency of the method of moments (MoM) when analyzing electromagnetic scattering from large perfect electrically conducting (PEC) bodies of revolution (BORs). The CBFs are high-level basis functions comprising of conventional subdomain bases, and their use leads to a reduced matrix that is solved by using a direct method. By exploiting the CBFM along with the FFT technique for generating the MoM matrix, memory requirement as well as computational time can be significantly reduced for large BOR problems

Solving very large EM problems (10/sup 9/ DoFs or greater) using the MPI-CBFDTD method

We describe a novel FDTD approach, called CBFDTD, which is based on the characteristic basis function method (CBFM) and a serial/parallel approach. The method is useful for solving electromagnetic problems that are difficult to handle via a direct application of the FDTD algorithm because of their large size. Like the CBMOM technique (Parakash, V. and Mittra, R., Microwave and Optical Technology Letters, vol.36, no.2, p.95-100, 2003), CBFDTD is based on dividing a large structure into relatively small sub-regions, and evaluating the characteristic functions that are localized in each of these sub-regions. The excitation of the sub-regions can either be direct sources that yield primary bases, or be derived from the adjacent regions through interfaces that generate secondary bases. We briefly describe the technique and present some results that validate the approach. The advantage of using the CBFDTD approach is that it can handle very large problems - involving 10/sup 9/, or even larger, numbers of unknowns - that are well beyond the scope of direct methods.

Identifying buried objects using the neural network approach

We present a neural network approach for detecting conducting anomalies, e.g., underground buried objects and those located in sedimentary layers in seafloors. The first step in this approach is to simulate the scattering from buried objects by using a suitable computational modeling tool. The electric and magnetic field values, thus computed, are then used as inputs to a neural network and the associated conductivities are treated as targets. The neural network is trained to associate the conductivity profiles with the computed field values. Finally, we demonstrate that a trained neural network can be used to estimate the conductivities and sizes of new objects, not originally employed to train the network.

Analysis of FSS composites comprising of multiple FSS screens of unequal periodicity

In this paper, we have presented an efficient cascading procedure for analyzing an FSS composite system, comprising of multiple FSS screens of unequal periodicities, embedded in multiple dielectric layers. The numerical examples demonstrate the efficiency and effectiveness of the technique. Based on this procedure, a computer program has been developed for the analysis of dissimilar FSS systems.

Design of artificial magnetic ground planes (AMGs) utilizing frequency selective surfaces embedded in multilayer structures with electric and magnetic losses

In this paper we present a novel approach to improving the bandwidth of the microstrip antennas using frequency selective surfaces (FSSs) as an artificial magnetic ground plane (AMG). The micro-genetic algorithm (MGA) is employed to derive an optimal FSS composite configuration that achieves the near unity-magnitude and zero-phase condition for the reflection coefficient of an artificial surface at the desired frequency band. The FSS element shape, electric and magnetic losses of dielectric layers as well as metallic loss of FSSs are composite parameters optimized by the MGA.

Parallel Analysis of Multiple FSS Screens of Unequal Periodicity using an Efficient Cascading Technique

This paper presents a parallelized version of cascading procedure for analyzing the frequency selective surface (FSS) system comprising of multiple FSS screens of unequal periodicity embedded in multiple dielectric layers. The parallelism is implemented for computation of the [S] matrices of subsystems at the global harmonics, while the cascading operation (matrix calculations) is carried out in a single processor. The workload distribution among the processors is dynamic varying from subsystem to subsystem, and it is determined once the number of processors for the simulation is assigned. Besides the workload distribution that affects the performance of the parallel implementation, another factor is the ratio of amount of time needed for matrix/cascading operation to that required for the subsystem analysis for a single incident angle

Efficient RCS computation for multiple incident angles using the FMM/MNM technique

We extend the MNM (Markov and Maxwell) technique, originally developed for frequency sweeping in the context of RCS computation, to speed up the iterative solution of MoM matrix equations with multiple right hand sides, corresponding to different angles of incidence. We show that the use of this technique can reduce computation time while preserving the accuracy of the solution. The MNM itself places little additional computational burden on the iteration process and usually requires less than the time required for a single iteration in the CG (conjugate gradient) process. The time-saving realized over the zero initial guess can be significant, especially when the angular increment is small, which is needed to capture rapid variations of the RCS, typically associated with large or complex scatterers.