This article proposes an accelerated ray-tracing algorithm to improve the computational efficiency of composite scattering from the 3-D ship target located on a random sea surface. The ray tracing is accelerated by using a new neighbor search technique, with a new 0-1 transformation rule and arrangement of octree nodes. It can reduce the code complexity and improve the computational efficiency. Combined with this technique, an accelerated algorithm based on the geometrical optics, physical optics with physical theory of diffraction (GO-PO/PTD) and capillary wave modification facet scattering model (CWMFSM) is further established. This is meaningful for the simulation of scattered echoes for wideband synthetic aperture radar (SAR), enabling SAR images to be formed using an imaging algorithm. The effectiveness of the proposed method was verified by comparing the simulation results with those produced by the FEKO-based multilevel fast multipole method (MLFMM). Further confirmation of its accuracy was obtained by comparing the simulated images with the measured ship image.

In this study, an accelerated shooting and bouncing ray (SBR) method was proposed to improve the computational efficiency of electromagnetic (EM) scattering from the electrically large complex objects. Initially, an open graphics library was employed to speed up the shadow faces removal. Then, the neighbor search technique was utilized to accelerate the ray tracing process, which was different from traditional SBR based on the traversal algorithms of Octree. The validation of the proposed method was verified by comparing the simulation results with those of the FEKO multilevel fast multipole method. Moreover, the EM scattering from two electrically large complex ship models was analyzed, and a desirable acceleration ratio was achieved. Therefore, the accelerated SBR method yields a superior performance for scattering analysis of electrically large complex targets, especially at high frequency.

The accuracy and the efficiency of hybrid methods that combine geometrical optics (GO) and physical optics (PO), and physical theory of diffraction (PTD), have been improved by the use of backward-ray-tracing technique and Gordon’s integral algorithm. However, the overall accuracy of the method is still limited by the errors in the process of backward-ray-tracing. In this study, both the advantages and the disadvantages of the two techniques, namely, the backward-ray-tracing and the forward-ray-tracing are compared. Also, the reasons for the errors in the backward ray-tracing are explored in detail. On this basis, an improved ray tracing technique is presented, called the Two Scale Division Method (TSDM). This technique combines the advantages of the forward and the backward tracing, and it improves the accuracy of the GO-PO/PTD hybrid method. Meanwhile, the efficiency of the ray tracing is improved by using two scale facets to structure the targets’ geometric model. The implementation principle of this method will be comprehensively discussed and it is validated by comparing the simulation results from FEKO-MLFMM, FEKO-RL-GO and those from an un-optimized method.

In this study, fast calculations for the electromagnetic (EM) scattering of complex targets coated by radar absorbing materials have been reported. The Geometric Optics and Physical Optics (GO/PO) methods are combined with the modified surface reflection coefficient method, to solve the problem of EM scattering. Moreover, two acceleration techniques have been employed to improve the efficiency of computations. Firstly, the neighbor search technique is adopted to accelerate the ray tracing process in GO/PO. In this technique, an Octree structure is applied to divide the space into multiple subspaces, namely sub-nodes, where the efficiency of ray tracing can be improved through Morton code transform. In order to further reduce the computational time, parallel acceleration technique, based on GPU platform within the Compute Unified Device Architecture (CUDA) framework is introduced. Our proposed method has been verified from the nice correlation of simulated and multilevel fast multipole method (MLFMM) and CPU-based GO/PO methods. The runtime is compared with that of GO/PO method in serial model, responsible for a good speedup ratio. Finally, the influence of coating thicknesses and types of material on the EM scattering characteristics of the coated targets are also analyzed.

The signal source of synthetic aperture radar (SAR) usually adopts the linear frequency modulation (LFM) signal, which exhibits the characteristics of a wide pulse. Hence, in the case of usage of the LFM signal by time-domain shooting and bouncing ray (TDSBR) to simulate the SAR echo signal, numerous time sampling points are generated, resulting in huge computational efforts; thereby, it is hard to exploit the TDSBR algorithm for simulating the SAR echo. In order to unlock this dilemma, the hybrid approach, the transfer function in conjunction with the range frequency-domain pulse coherence (RFPC), is developed, in which the transfer function is stated by the radar cross section (RCS). The proposed methodology is capable of enhancing the computational efficiency through avoiding the massive time sampling, so that the suggested TDSBR approach could be more conveniently applied to the SAR echo simulations. Furthermore, because of the efficiency advantage of the TDSBR in the calculation of wideband scattering field, the proposed methodology exhibits higher computational efficiency than the frequency-domain shooting and bouncing ray (FDSBR) in the SAR image simulation. Finally, the key equation of the TDSBR for the transient scattering field of dielectric targets based on a closed-form integration formula is analytically derived, which is the basis of SAR imaging simulation for the composite scene of ships above the sea surface.

An Improved Particle Swarm Optimization Algorithm-Support Vector Regression Machine (IPSO-SVR) prediction model is developed in this paper to predict the electromagnetic (EM) scattering coefficients of the three-dimensional (3D) sea surface for large scenes in real-time. At first, the EM scattering model of the 3D sea surface is established based on the Semi-Deterministic Facet Scattering Model (SDFSM), and the validity of SDFSM is verified by comparing with the measured data. Using the SDFSM, the data set of backscattering coefficients from 3D sea surface is generated for different polarizations as the training samples. Secondly, an improved particle swarm optimization algorithm is proposed by combining the Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The combined algorithm is utilized to optimize the parameters and train the SVR to build a regression prediction model. In the end, the extrapolated prediction for backscattering coefficients of the 3D sea surface is performed. The Root Mean Square Error (RMSE) of the IPSO-SVR-based prediction model is less than 1.2 dB, and the correlation coefficients are higher than 91%. And the prediction accuracy of the PSO-SVR-based, GA-SVR-based and IPSO-SVR-based prediction models is compared. The average RMSE of the PSO-SVR-based and GA-SVR-based prediction models is 1.4241 dB and 1.6289 dB, respectively. While the average RMSE of the IPSO-SVR-based prediction model is reduced to 1.1006 dB. Besides, the average correlation coefficient of the PSO-SVR-based and GA-SVR-based prediction models is 94.36% and 93.93%, respectively. While the average correlation coefficient of the IPSO-SVR-based prediction model reached 95.12%. It demonstrated that the IPSO-SVR-based prediction model can effectively improve the prediction accuracy compared with the PSO-SVR-based and GA-SVR-based prediction models. Moreover, the simulation time of IPSO-SVR-based prediction model is significantly decreased compared with the SDFSM, and the speedup ratio is greater than 15.0. Therefore, the prediction model in this paper has practical application in the real-time computation of sea surface scattering coefficients in large scenes.