Electromagnetic Scattering and Statistic Analysis of Clutter from Oil Contaminated Sea Surface

Qi, Conghui; Zhao, Zhiqin

doi:10.13164/re.2015.0087

Cited by 6 publications

(4 citation statements)

References 17 publications

(20 reference statements)

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“…So, the current paper is expected to lead to the creation of the P-NATE-CA-CFAR (Pareto-Neural Adaptive Threshold Estimation-Cell AveragingConstant False Alarm Rate) detector. At the same time, the new neural method helps improving the identification of anomalous sea surface conditions such as fish gatherings [48], oil spills [49,50] or shipwrecks [51,52]. These conditions cause deviations in the clutter statistics, which may be identified with a precise estimator of the shape parameter such as the one proposed.…”

Section: A Comparison With the Mle Estimatormentioning

confidence: 99%

Improved Shape Parameter Estimation in Pareto Distributed Clutter with Neural Networks

Bacallao-Vidal¹,

Machado-Fernández²

2016

IJIMAI

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-The main problem faced by naval radars is the elimination of the clutter input which is a distortion signal appearing mixed with target reflections. Recently, the Pareto distribution has been related to sea clutter measurements suggesting that it may provide a better fit than other traditional distributions. The authors propose a new method for estimating the Pareto shape parameter based on artificial neural networks. The solution achieves a precise estimation of the parameter, having a low computational cost, and outperforming the classic method which uses Maximum Likelihood Estimates (MLE). The presented scheme contributes to the development of the NATE detector for Pareto clutter, which uses the knowledge of clutter statistics for improving the stability of the detection, among other applications.

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Section: A Comparison With the Mle Estimatormentioning

confidence: 99%

Improved Shape Parameter Estimation in Pareto Distributed Clutter with Neural Networks

Bacallao-Vidal¹,

Machado-Fernández²

2016

IJIMAI

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“…To calculate a backscattering field, a specific integral equation has to be solved. Recently, the numerical solutions are more considered for this purpose . By this manner, the computation depends on the size of desired scene and the target dimensions.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, the numerical solutions are more considered for this purpose. 8,9 By this manner, the computation depends on the size of desired scene and the target dimensions. Unfortunately, most of these methods are limited to 2D models due to the high amount of calculations required for the 3D cases.…”

Section: Introductionmentioning

confidence: 99%

An efficient raw data simulation algorithm for large complex marine targets and extended sea clutter in spotlight SAR

Sofiani

Heidar

Kazerooni

2018

Micro & Optical Tech Letters

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An efficient algorithm is proposed to simulate the backscattering field of a complex marine target and surrounding 3D sea surface as clutter. Sea surface backscattering is simulated based on the numerical solution of the Electric Field Integral Equation by an improved meshing algorithm. The complex target is modeled using the discrete scattering centers independently. Combining the target and sea surface backscattered fields is used to extract the SAR raw data. The effectiveness of the proposed algorithm is verified for 2 hypothetical cases.

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“…However, these works are either ineffective or not applied further on actual layered models. To date, several methods have been used to calculate the properties of layered rough surfaces or to analyze the polarimetric scattering from two-layer random rough surfaces with and without buried objects, such as rigorous numerical method multilevel fast multipole algorithm (MLFMA) [22], KA model [23], the steepest descent fast multipole method (SDFMM) [24], and geometrical optics (GO) models [25,26]. Obviously, approximate methods can improve computational efficiency while maintaining the desirable precision.…”

Section: Introductionmentioning

confidence: 99%

Three Dimensional Electromagnetic Scattering of Two-Layer Rough Surfaces Using Physical Optics Approximation Algorithm

Li¹,

Guo²,

Li³

2018

PIER M

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In this study, the physical optics approximation (POA) algorithm is described for predicting the electromagnetic (EM) scattering of three dimensional (3D) two-layer rough surfaces. The POA is initially used to calculate the composite scattering of an object and single layer rough surface under two dimensional (2D) situations. We extend this method to the case of a rough layer with two rough interfaces. The multiple coupling interactions between the upper and lower layer are considered based on an iterative strategy. Because the coupling effect is considered, the 3D model is quite time-consuming. In order to obtain numerical results rapidly, a parallel technique based on the OpenMP is adopted to accelerate the coupling iterative calculation. The model is applicable for moderate to large surface roughness. However, the rough surface should have small to moderate slopes so as to meet the conditions of POA. In numerical results, the normalized radar cross section of two-layer rough surfaces model under different polarizations is calculated, and the model is validated by comparison with a numerical reference method based on the method of moment. In addition, the influence of roughness on the scattering model is analyzed and discussed.

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Electromagnetic Scattering and Statistic Analysis of Clutter from Oil Contaminated Sea Surface

Abstract: Abstract. In order to investigate the electromagnetic (EM

Cited by 6 publications

References 17 publications

Improved Shape Parameter Estimation in Pareto Distributed Clutter with Neural Networks

Improved Shape Parameter Estimation in Pareto Distributed Clutter with Neural Networks

An efficient raw data simulation algorithm for large complex marine targets and extended sea clutter in spotlight SAR

Three Dimensional Electromagnetic Scattering of Two-Layer Rough Surfaces Using Physical Optics Approximation Algorithm

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