An efficient hybrid algorithm is proposed to analyze the electromagnetic scattering properties of metal objects in the lower terahertz (THz) frequency. The metal object can be viewed as perfectly electrical conducting object with a slightly rough surface in the lower THz region. Hence the THz scattered field from metal object can be divided into coherent and incoherent parts. The physical optics and truncated-wedge incremental-length diffraction coefficients methods are combined to compute the coherent part; while the small perturbation method is used for the incoherent part. With the MonteCarlo method, the radar cross section of the rough metal surface is computed by the multilevel fast multipole algorithm and the proposed hybrid algorithm, respectively. The numerical results show that the proposed algorithm has good accuracy to simulate the scattering properties rapidly in the lower THz region.
Microwave backscattering from sea surface at low grazing angle (LGA) is important in predicting radar detection of targets on or near the surface, since the probability of a false alarm depends upon the observed signal-to-clutter ratio. However, the large area illuminated by incident beam at LGA leads to a number of unknown when using numerical method to calculate backscattering from sea surface. In addition, the calculation of backscattering from hundreds of random sea surface samples is needed to obtain the statistical properties of random rough surface. The sparse matrix canonical grid (SMCG) and compute unified device architecture (CUDA) libraries are used to accelerate the computation. By using these techniques, Doppler spectral characteristics of electromagnetic scattering from sea surface is effectively calculated.
Research on the electromagnetic scattering of ocean surface is significant in target
recognition and signal separation technologies and its application are widely involved in remote
sensing, radar imaging and early warning. In this paper the statistical wave model are introduced.
It uses physical optics (PO), one of high frequency approximation methods, to calculate the
backward scattering coefficients of sea surface composed of a large number of triangle patches.
PO based on some reasonable approximation needs less memory and execution time than
numerical methods; however it should judge the patches whether they are exposed or not to the
incident wave which costs a lot of time. We take advantage of the massively parallel compute
capability of NVIDIA Fermi GTX480 with the Compute Unified Device Architecture (CUDA) to
judge the patches and compute the scattering field of them. Our parallel design includes the
pipelined multiple-stream asynchronous transfer and parallel reduction with shared memory. By
using these techniques, we achieved speedup of 26-fold on the NVIDIA GTX 480 GPU.
Electromagnetic scattering of vegetation is represented by a double-layer model
comprising of vegetation layer and ground layer. The vegetation layer is composed of discrete
leaves which are approximated as ellipsoids. The ground layer is modeled as a random rough
surface. Investigation of the scattering field of a single leaf is carried out first. Then the leaves are
divided into different groups depending on their orientation. Considering the incoherent addition
property of Stokes parameters, the Stokes matrix and the phase matrix of every group are
calculated, adding them eventually to get the total scattering coefficient. In the original
CPU-based sequential code, the Monte Carlo simulation to calculate the electromagnetic
scattering of vegetation takes 97.2% of the total execution time. In this paper we take advantage
of the large-scale parallelism of Compute Unified Device Architecture (CUDA) to create and
compute all the groups simultaneously. As a result, a speedup of up to 213x is achieved on a single
Fermi-generation NVIDIA GPU GTX 480.