Sea Surface Monostatic and Bistatic EM Scattering Using SSA-1 and UAVSAR Data: Numerical Evaluation and Comparison Using Different Sea Spectra

Abstract

The microwave scatterometer is one of the most effective instruments in ocean remote sensing, which urges the need for some theoretical models to accurately estimate the scattering coefficient of the sea surface. For the simulation of the scattering from an ocean surface, the sea spectrum, or its inverse Fourier transform, autocorrelation function is essential. Currently, many sea spectral models have been proposed for describing sea waves. However, which spectrum should be adopted during electromagnetic (EM) computations? A systematic comparison of these models is needed to evaluate their accuracies. In this paper, we focus on numerical simulations of scattering from a rough sea surface in monostatic and bistatic configurations by using six different sea spectral models and the first-order small slope approximation (SSA-1). First, sea spectral models proposed by Elfouhaily et al., Hwang et al., Romeiser et al., Apel et al., Fung et al., and Pierson et al., are compared with each other from different points of view, e.g., the omnidirectional parts, the angular spreading functions, the autocorrelation functions, and the slope variances. We find that the spectra given by Elfouhaily and Hwang could reflect realistic wind sea waves more accurately. Then, the scattering coefficients are simulated in fully monostatic and bistatic configurations. Regarding the monostatic scattering, the results simulated using EM scattering models are compared with those obtained from the measured UAVSAR data in the L band and the empirical model CMOD5 in the C band. Comparisons are made for various incident angles, wind speeds, and wind directions. Meanwhile, special attention is paid to low to moderate incident angles. The comparisons show that, it is difficult to find one certain spectral model to simulate scattering coefficient accurately under all wind speeds or wind directions. Accurate estimations will be obtained using different methods according to different situations.

Modeling and SAR Imaging of the Sea Surface: a Review of the State-of-the-Art with Simulations

“…However, for the other spectra, this agreement was not observed where S P M and S J showed better agreement than S F L . The results, in general, are consistent with results shown in previous studies [34], [81], [133]. For example, in [81] the slope variance of different spectra has also been compared with the slope variances according to the Cox and Munk's model.…”

“…To the best of our knowledge, an analysis in this respect has not been performed before. There are limited studies where various spectra are compared, but then only in terms of ensuing absolute NRCS values [81]- [84]. By contrast we employ five well-known sea wave spectra including Pierson-Moskowitz [85], JONSWAP [86], Fung and Lee [87], Elfouhaily et al [88] and Romeiser et al [73], and compare the contribution of these spectra to ship wake visualization in SAR images.…”

Angular Composite Facet Model with Shadowing Treatment for Backscattering from Two-Dimensional Rough Sea Surface

“…Gravity and capillary-gravity waves are often treated as two different kinds of roughness in microwave frequency band and more attention should be paid to small-scale waves for their dominant effects at middle and large incident angles. Of all the spectral models, the PM spectrum and JONSWAP spectrum are only able to describe large-scale waves, which means they fail to fully express the small-scale roughness [27]. Therefore, we chose the Fung spectrum [28] to generate the sea surface height map and to be employed in EM computations later.…”

Investigation of EM Backscattering from Slick-Free and Slick-Covered Sea Surfaces Using the SSA-2 and SAR Images

“…where ( )  is the angle between the observation angle and upwind direction. In the literature, various sea spectral models have been proposed; among these models, the Elfouhaily spectrum is one of the most widely used sea spectra in ocean remote sensing [24,25]. In this work, the Elfouhaily spectrum is employed to describe sea waves.…”