On Semiparametric Clutter Estimation for Ship Detection in Synthetic Aperture Radar Images | IEEE Journals & Magazine | IEEE Xplore

On Semiparametric Clutter Estimation for Ship Detection in Synthetic Aperture Radar Images


Abstract:

The statistical behavior of the sea clutter in synthetic aperture radar (SAR) images is characterized by both the marginal distribution and the spatial correlation. Howev...Show More

Abstract:

The statistical behavior of the sea clutter in synthetic aperture radar (SAR) images is characterized by both the marginal distribution and the spatial correlation. However, simultaneous modeling of the joint information remains a difficult job because of the non-Gaussian clutter nature. In this paper, a semiparametric approach is proposed for addressing this problem. First, we investigate the applicability of the nonparametric kernel density estimator (KDE) for estimating the marginal distribution of the SAR clutter and show that the KDE is most applicable in the log-intensity domain. Second, we propose to estimate the underlying spatial correlation structure with a copula approach and show that the Gaussian copula is a sufficiently accurate model. Consequently, the KDE, together with the Gaussian copula, offers a full characterization of the joint probability distribution, based on which a quadratic detector of null distribution governed by the well-known chi-squared law can be conveniently designed for constant false alarm rate detection. In the experiment, results with both simulated and real SAR data demonstrate that, compared with the single-point detector using only the marginal distribution, the proposed method, which incorporates spatial correlation, significantly improves the detection performance with regard to either the receiver-operating-characteristic curve or detected target pixels. The tradeoff, however, lies in a loss of false alarm rate control resulting from increased uncertainty in estimating higher dimensional distributions.
Published in: IEEE Transactions on Geoscience and Remote Sensing ( Volume: 51, Issue: 5, May 2013)
Page(s): 3170 - 3180
Date of Publication: 16 November 2012

ISSN Information:


I. Introduction

Ship surveillance has gained great attention in recent years owing to the increasing maritime concerns, e.g., on piracy and illegal fishing. In particular, ship detection via synthetic aperture radar (SAR) has become a popular choice, due its many advantages including the all-time/all-weather operational capability, high resolution, wide coverage, etc. Applications have been reported using TerraSAR-X [1], RADARSAT-2 [2], and ALOS-PALSAR [3].

References

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