No abstract

In the radar cross section (RCS) prediction of complex target, the intensive computational burden occurs while calculating the multiple scattering effect. In order to overcome the large computing, we present the program executing on graphics processing units (GPU's). In this paper, we analyze the scattering properties of the satellite, on which the antennas are described as cubes and columns, by employing the GPU-based combinational method of geometrical optics (GO) and physical optics (PO) together with the kd-tree technique. Furthermore, due to this distinctive treatment, the improved method yields a superior performance at high frequency. Some examples will be displayed in the following text. The agreement of the results yielded in this paper with the experimental and other exact results demonstrates the accuracy and efficiency of this useful technique.Index Terms-Compute unified device architecture (CUDA), kd-tree, complex satellite

In this paper, a fi eld experiment was carried out to study train-induced environmental vibrations. During the fi eld experiment, velocity responses were measured at different locations of a six-story masonry structure near the BeijingGuangzhou Railway and along a small road adjacent to the building. The results show that the velocity response levels of the environmental ground and the building fl oors increase with train speed, and attenuate with the distance to the railway track. Heavier freight trains induce greater vibrations than lighter passenger trains. In the multi-story building, the lateral velocity levels increase monotonically with fl oor elevation, while the vertical ones increase with fl oor elevation in a fl uctuating manner. The indoor fl oor vibrations are much lower than the outdoor ground vibrations. The lateral vibration of the building along the direction of weak structural stiffness is greater than along the direction with stronger stiffness. A larger room produces greater fl oor vibrations than the staircase at the same elevation, and the vibration at the center of a room is greater than at its corner. The vibrations of the building were compared with the Federal Transportation Railroad Administration (FTA) criteria for acceptable ground-borne vibrations expressed in terms of rms velocity levels in decibels. The results show that the train-induced building vibrations are serious, and some exceed the allowance given in relevant criterion.

The small slope approximation (SSA) method is a practical method to calculate the electromagnetic (EM) scattering from rough surfaces. However, the SSA method requires that the interval for sampling surfaces must be small enough, such as less than one-tenth of incident wavelength. This constraint condition will cause the problem of huge memory consumption and insufficient memory when the EM scattering of large rough surfaces is calculated. Although the hard disk has large space to keep data and can solve the insufficient memory problem, its read/write speed is still too slow. In addition, massive data transmission will reduce the computational efficiency for the compute unified device architecture (CUDA) parallel computation under some conditions. In this paper, the main idea of the spectral decomposition modeling method is that the whole spectrum of rough surface is divided into several parts and these parts can be used to generate differentscale rough surfaces. Then, by analyzing the different-scale rough surfaces, the large rough surface can be achieved and applied to the calculation of EM scattering with the SSA method. Due to the small memory consumption of different-scale rough surfaces, it takes less time to translate data for the different-scale rough surfaces than that for the standard large surface. Thus, the spectral decomposition modeling method could readily be applied to CUDA parallel computation.Index Terms-Compute unified device architecture (CUDA), rough surface, scattering, small-slope approximation, spectral decomposition modeling.

An improved facet model for the predication of the normalized radar cross section (NRCS) of electrically large rough sea surface was proposed based on the first-order small slope approximation (SSA-1) method, the Bragg scattering mechanism, and the specular scattering mechanism. The proposed method is able to evaluate both the complex reflective function and NRCS of electrically large sea surfaces from as low as ultrahigh frequency band to as high as Ka-band. The main idea is that a tilt sea facet can be regarded as the superposition of a planner facet and the microscopic profile; the latter is assumed to be a set of sinusoidal ripple patches. Thus, the integration kernel in SSA-1 over several small facets can be replaced by a large facet with a short wave modification. The efficiency increases because of the much larger mesh size than SSA. Then, both the backscattering and bistatic scattering NRCS results calculated by the proposed method were compared with those predicated by SSA-1, and all of the results show that the proposed method has the merits of high calculation efficiency as well as calculation accuracy.Index Terms-Bragg scattering, facet model, small slope approximation (SSA), specular scattering.