A Semi-Empirical Model Of Sea Clutter Based On Zero Memory Nonlinearity

Abstract

Based on the computer simulation technology of zero memory nonlinearity (ZMNL), this paper combines with the backscattering features of sea clutter and conducts simulation for four typical backscattering coefficient empirical models of sea clutter, namely, Technology Service Corporation, Georgia Institutes of Technology, Hybrid Sea Clutter Model, and Naval Research Laboratory. According to the results, the signals of sea clutter simulated by zero memory nonlinearity are able to well satisfy the requirements of spectrum characteristics and amplitude distribution according to experiments on the fitting characteristics of simulated signals. After that, the above-mentioned sea clutter scattering coefficient fitting characteristics are applied to the finite difference time domain (FDTD) electromagnetic scattering equation of the numerical method, and the optimal recursive solution to the backward scattering area fitted by the above four semi-empirical models is proposed for the first time. Then, the method of discretizing the power spectrum equation of the differential form is combined with the FDTD discrete form. The numerical results of discrete simulation take the form of the random phase ω between 0 and 2π and then are converted into a basic iteration of one-dimensional rough length, thus realizing time domain power spectrum inversion. Finally, combined with the above conclusions, this paper proposes a new statistical model based on sea surface backscatter coefficient to invert the two-dimensional sea surface, that is, the three-parameter statistical model. At the same time, this paper further deduces the backscattering function of sea clutter based on random distribution and points out that the incident frequency and the rubbing angle are the main factors affecting the sea clutter scattering model. Based on this conclusion, this paper combines the sea clutter estimation model and the directional function model to simulate a two-dimensional random rough sea surface satisfying the physical laws of the ocean.INDEX TERMS Zero memory nonlinearity, empirical models, finite difference time domain, twodimensional sea surface.

A Novel SAR Fractal Roughness Modeling of Complex Random Polar Media and Textural Synthesis Based on a Numerical Scattering Distribution Function Processing

“…In general, the scattering modeling of random media can be categorized into three areas: experimental methods, analytical models, and numerical simulations [23]. Despite the obvious limitations of experimental methods, much work has been devoted to understanding the validity domains of these approximations [24][25]. Analytical scattering theories are of importance in modeling applications.…”

“…The main drawbacks of analytical models are the lack of domain categorization, the long computation time and the scarce evaluation scenarios [26][27]. To overcome the limitations of analytical modeling and to provide validation for experimental methods, numerical simulations have been proposed [23][24][28][29][30][31][32]. The bulk of numerical simulations in surface roughness modeling have been restricted to 1D surfaces relative to their mean direction, which makes them similar to the surface cross-section [4, 12, 14-15, 20, 26, 28, 31, 33].…”

“…Currently, both theoretical methods and numerical simulations are being applied to the study of physical phenomena that arise in ocean surface modeling that are inherently 2D and cannot be observed using 1D approximations, specifically while dealing with ocean waves known as sea state conditions [35][36][39][40][41][42][43]. Hence, characterizing the stochastic scattering properties of such nondeterministic complex media with a given statistical distribution of concentration and normal absorption data is considered a complicated approach to model ocean roughness [24,42,[44][45]. Accordingly, a numerical modeling of the MIZ under sea state conditions as an extreme ocean medium will not only be more complicated due to its complex structure but will also be a novel statistical scattering approach to visualize CRPM, which has not been reported in polar observations [1-3, 7-12, 16, 18-19, 22, 36, 40-42, 44-49].…”

Computational Simulation and Modeling of Freak Waves Based on Longuet-Higgins Model and Its Electromagnetic Scattering Calculation

“…In the early practical application, based on the numerical simulation of one-and two-dimensional space freak waves, we have calculated and analyzed the electromagnetic scattering coefficient of freak waves to study the formation mechanism, remote sensing recognition, and other related characteristics [21]. Based on the Two-Scale Method (TSM) and the Harger distribution surface, Franceschetti proposed two kinds of sea surface SAR simulator models [22]; however, this research method has great limitations because of its failure to fully consider the strong non-Gaussian statistical characteristics and velocity bunching effect of the height distribution of freak waves [23,24]. In recent years, freak waves have attracted much attention because of their potential for serious damage to shipping and offshore structures.…”

Numerical computational modeling of random rough sea surface based on JONSWAP spectrum and Donelan directional function

“…During the course of exploring the simulation of random rough sea surface, two important methods applied to the reconstruction of sea surface have been developed, 9,10 namely, classical Monte Carlo method and fractal‐like function method. In addition, known as linear filtering method, the Monte Carlo method mainly uses the power spectrum in the frequency domain to filter the one‐dimensional rough power function.…”