Based on the model of Lombardini et al. [J. Atmos. Ocean. Technol.6(6), 882–890 (1989)], which can predict the hydrodynamic damping of rough sea surfaces in the presence of oil films, the influence of sea slicks on the sea surface roughness spectrum and sea surface geometrical structure is examined briefly in the present study. On this basis, the influence of sea slicks on the angular distribution of the bistatic scattering coefficient of sea surfaces and the Doppler spectrum signature of backscattered radar sea-echo is investigated in detail based on a frequency-domain numerical method of the parallel fast multiple method. Simulation results show that Doppler spectrum signatures including Doppler shift and spectral bandwidth of radar sea-echo are significantly affected by sea slicks, which are qualitatively consistent with wave-tank or open sea measurements. Moreover, simulation results indicate that the Doppler spectrum signature is a promising technique for remote sensing of oil films floating on sea surfaces.
The graphics processor unit-based finite-difference time domain (FDTD) algorithm is applied to study the electromagnetic (EM) scattering from one-dimensional (1-D) large scale rough soil surface at a low grazing incident angle. The FDTD lattices are truncated by a uniaxial perfectly matched layer, and finite difference equations are employed in the whole computation domain for convenient parallelization. Using Compute Unified Device Architecture technology, we achieve significant speedup factors. Also, shared memory and asynchronous transfer are used to further improve the speedup factors. Our method is validated by comparing the numerical results with those obtained by using a CPU. The influences of the incident angle, correlation length l, and root-mean-square height δ on the bistatic scattering coefficient of a 1-D large scale rough surface at low grazing incidence are also discussed.
This paper presents the graphics processor unit (GPU)-based finite difference time domain (FDTD) algorithm to investigate the electromagnetic (EM) scattering from a two-dimensional target above a one-dimensional rough sea surface with the Pierson–Moskowitz spectrum. The proposed method is validated by comparing the numerical results with those obtained through sequential FDTD execution on a central processing unit, as well as through method of moments. Using compute unified device architecture technology, significant speed-up ratios are achieved. Furthermore, the speedup is improved by shared memory and asynchronous transfer.
In this study, an improved ray tracing propagation prediction model, which is based on creating a new virtual source tree, is used because of their high efficiency and reliable prediction accuracy. In addition, several acceleration techniques are also adopted to improve the efficiency of coverage prediction over large areas. However, in the process of employing the ray tracing method for coverage zone prediction, runtime is linearly proportional to the total number of prediction points, leading to large and sometimes prohibitive computation time requirements under complex geographical environments. In order to overcome this bottleneck, the compute unified device architecture (CUDA), which provides fine-grained data parallelism and thread parallelism, is implemented to accelerate the calculation. Taking full advantage of tens of thousands of threads in CUDA program, the decomposition of the coverage prediction problem is firstly conducted by partitioning the image tree and the visible prediction points to different sources. Then, we make every thread calculate the electromagnetic field of one propagation path and then collect these results. Comparing this parallel algorithm with the traditional sequential algorithm, it can be found that computational efficiency has been improved dramatically.
In this paper, the graphic processor unit (GPU) implementation of the finite-difference time domain (FDTD) algorithm is presented to investigate the electromagnetic (EM) scattering from one dimensional (1-D) Gaussian rough soil surface. The FDTD lattices are truncated by uniaxial perfectly matched layer (UPML), in which the finite-difference equations are carried out for the total computation domain. Using Compute Unified Device Architecture (CUDA) technology, significant speedup ratios are achieved for different incident frequencies, which demonstrates the efficiency of GPU accelerated the FDTD method. The validation of our method is verified by comparing the numerical results with these obtained by CPU, which shows favorable agreements.
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