This letter presents the graphics processing unit (GPU)-based finite-difference time-domain (FDTD) algorithm to investigate the electromagnetic (EM) scattering from a target above a rough sea surface. The proposed method is validated by comparing the numerical results to those obtained through sequential FDTD execution on a central processing unit (CPU), as well as through method of moments (MOM). The comparison results show a significant improvement in computation efficiency for GPU-based FDTD versus the message passing interface (MPI)-based FDTD. Furthermore, our parallel implementation is employed to study the influences of wind speed and the tilt angle of the target on composite scattering from the target above a sea surface.

Oil spill SAR images are characterized by high noise, low contrast, and irregular boundaries, which lead to the problems of overfitting and insufficient capturing of detailed features of the oil spill region in the current method when processing oil spill SAR images. An improved DeepLabV3+ model is proposed to address the above problems. First, the original backbone network Xception is replaced by the lightweight MobileNetV2, which significantly improves the generalization ability of the model while drastically reducing the number of model parameters and effectively addresses the overfitting problem. Further, the spatial and channel Squeeze and Excitation module (scSE) is introduced and the joint loss function of Bce + Dice is adopted to enhance the sensitivity of the model to the detailed parts of the oil spill area, which effectively solves the problem of insufficient capture of the detailed features of the oil spill area. The experimental results show that the mIOU and F1-score of the improved model in an oil spill region in the Gulf of Mexico reach 80.26% and 88.66%, respectively. In an oil spill region in the Persian Gulf, the mIOU and F1-score reach 81.34% and 89.62%, respectively, which are better than the metrics of the control model.

Wideband electromagnetic scattering from multiple objects partially buried beneath rough earth soil surfaces is an important topic during recent years due to its extensive applications in several fields, such as ground remote sensing, ground penetrating radar applications, and target identification. Due to the advantages of finite-difference time-domain (FDTD) method in calculating the wideband electromagnetic scattering from rough surface in the presence of multiple objects, the FDTD method under ultrawideband (UWB) Gaussian pulse wave incidence is utilized in the present study for analyzing the frequency response of rough soil surfaces with periodically distributed multiple rectangular cross-section columns buried partially. In this paper, the dielectric property of the actual land surface is expressed using the four-component model, and the actual rough land surface is simulated utilizing Monte Carlo method with exponential correlation function. The emphasis of the present study is on analyzing the wideband response signatures of composite backscattering coefficient varying with frequency on the basis of extensive numerical simulations, in particular for calculating and discussing in detail the influence of the root-mean-square height and the correlation length of rough soil surface, soil moisture, the length and the width of the rectangular cross-section column, separation distance, burial depth, and tilt angle on the composite backscattering coefficient.

Polarimetric scattering model of second-order small-slope approxi-mation combined with “choppy wave" model (CWM) for describing nonlinear hydrodynamic interactions between ocean waves is utilized in this paper to investigate the influence of sea surface nonlinearities on backscattering coefficient as well as Doppler spectrum signatures including Doppler shift and spectral bandwidth. Simulation results show that at moderate to large incidence angles the Doppler shift and spectral bandwidth of the CWM nonlinear sea surfaces are significantly larger than those of linear sea surfaces, in particular at low grazing angles. In addition, Doppler signatures show distinct polarization dependence, and most importantly the cross-polarized Doppler signatures significantly differ from the co-polarized ones. It is also indicated that co-polarized Doppler shift increases obviously with wind speed increasing, whereas the cross-polarized Doppler shift looks less sensitive to wind speed variations. The difference of Doppler signatures between co- and cross-polarization is potentially valuable for ocean remote sensing applications, especially for observing very high winds.