Abstract

Due to the difficulties in actual measurement of sea clutter and uncertainties of experimental data, the electromagnetic (EM) scattering model becomes a better alternative means to acquire the sea clutter. However, the EM scattering model still faces the problems of huge memory consumption and low-computational efficiency when dealing with the large size of sea surface or the long time case. Thus, this paper presents a statistical model to simulate the temporal-spatial correlated three-dimensional (3D) sea clutter, which is based on the statistical properties obtained from the EM scattering model, such as probability density function and correlation function. The comparisons show that the texture feature, autocorrelation function, and PDF of the sea clutter simulated by the statistical model have a good agreement with the results given by the EM model. Furthermore, the statistical model is with high efficiency and can be used to simulate the large scene or long time temporal-spatial correlated 3D sea clutter.

Highlights

  • It is the basic working mechanism of radar to discover and identify the target by using the electromagnetic (EM) scattering characteristics of the target

  • It is seen that 1D plot of the autocorrelation function and probability density function (PDF) of 2D spatial correlated sea clutter generated by the statistical model agree well with the results simulated by the EM model

  • A statistical model extended from the zero-memory nonlinear transform (ZMNL) method to the 3D case is proposed to simulate the temporalspatial correlated 3D sea clutter

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Summary

Introduction

It is the basic working mechanism of radar to discover and identify the target by using the electromagnetic (EM) scattering characteristics of the target. Many sea clutter simulation models based on the EM scattering model have been developed, such as Kirchhoff Approximation (KA) [3, 4], two-scale model (TSM) [5, 6], small slope approximation (SSA) [7,8,9], and some other facet-based models [10, 11]. The EM scattering models mentioned above are harder to deal with the scattering of sea surface with large area or long time case Another kind of sea clutter simulation models are based on the statistical model, such as the zero-memory nonlinear transform (ZMNL) [12, 13] and spherically invariant random process (SIRP) [14, 15].

Simulation Models for 3D Sea Clutter
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