Roughness parameters estimation of sea surface from SAR images

Abstract

Some knowledge of sea state and conditions is input in ship detection algorithms based on inversion of scattering models for Synthetic Aperture Radar (SAR) images. This paper shows a novel technique for the estimation of roughness parameters of the sea surface from SAR images. The estimation procedure is based on the minimization of the absolute error between the Radar Cross Section (RCS) of the sea surface measured on the SAR image and the expected RCS computed using the Kirchhoff approach within the Geometrical Optics (GO) solution. The technique is tested on three different TerraSAR-X images acquired in November 2012 over the Portsmouth harbour in the UK.

A Novel Ship Detector Based on the Generalized-Likelihood Ratio Test for SAR Imagery

“…where M is the number of samples and σ x,i is the RCS of the ith sample. In addition, it is assumed that the sample average of the SAR intensity is equal to the RCS reflected by a rough surface within the GO approximation as already done by Iervolino et al in [34]. In formulâ (6), σ GO is the RCS relevant to the single scattering contribution of the sea clutter; |S pq | c is the module of the generic element of the scattering matrix for the clutter, with p and q standing for horizontal H or vertical V polarization respectively; σ dev and L are the standard deviation and the correlation length, respectively, of the stochastic process representing the sea clutter; ϑ is the radar look angle and, finally, a and b are the dimensions of the rectangular portion of sea where the RCS is evaluated (generally set equal to the SAR spatial resolution).…”

“…3) Roughness ratio (σ dev /L) computable directly from the SAR image. It is evaluated by minimizing the absolute error between the RCS relevant to the single scattering of the sea surface and the RCS measured on the SAR image [34]. 4) Vector b: Unknown parameters.…”

“…The TCR can be expressed as a ratio of the target RCS (σ GOGO = σ target ) to the sea clutter RCS (σ GO = σ clutter ), [25], [34]:…”

“…In the same ROI, the roughness ratio σ dev /L has been computed by minimizing the absolute error between the RCS relevant to the single scattering of the sea surface and the RCS directly measured on the SAR image. The methodology is explained in [34], where the results (see [34, Fig. 2]) are also shown for the considered dataset.…”

A new GLRT-based ship detection technique in SAR images

“…In (1), pq S depends on the dielectric constant of the sea ( SW ε ), the dielectric constant of the hull ( HULL ε ), ϕ ,ϑ , the working wavelength λ and the Fresnel coefficient according to the polarization of the propagating wave [5]. The parameters ϑ and λ are a priori known and can be retrieved from the ancillary data of the SAR sensor; SW ε can be computed from the saline-water Double-Debye dielectric model presented in [6]; the ratio dev L σ can be evaluated directly on the SAR image according to [7]. For the remaining ones ( HULL ε , ϕ and h) suitable probability distribution functions need to be introduced bringing, in turn, to a probability density function for the RCS too [8].…”