Abstract

Polarimetric synthetic aperture radar (SAR) is currently drawing more attention due to its advantage in Earth observations, especially in ship detection. In order to establish a reliable feature selection method for marine vessel monitoring purposes, forty features are extracted via polarimetric decomposition in the full-polarimetric (FP), compact-polarimetric (CP), and dual-polarimetric (DP) modes. These features were comprehensively quantified and evaluated using the Euclidean distance and mutual information, and the result indicated that the features in CP SAR are better than those of FP or DP SAR in general. The CP SAR features are thus further studied, and a new feature, named phase factor, in CP SAR mode is presented that can distinguish ships and the sea surface by the constant 0 without complex calculation. Furthermore, the phase factor is independent of the sea surface roughness, and hence it performs stably for ship detection even in high sea states. Experiments demonstrated that the ship detection performance of the phase factor detector is better than that of roundness, delta, HESA and CFAR detectors in low, medium and high sea states.

Highlights

  • Ship detection is of great significance in maritime traffic, immigration control, and fishing activity monitoring

  • The key to the Constant false alarm rate (CFAR) method is the selection of a threshold, and the threshold depends on the probability density function (PDF) of the sea clutter

  • Experiments were performed using circular transmission and linear reception (CTLR) mode emulated from C-band RADARSAT-2 FP Synthetic aperture radar (SAR) data to validate the superiority of the phase factor in ship detection

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Summary

Introduction

Ship detection is of great significance in maritime traffic, immigration control, and fishing activity monitoring. With the higher resolution of the SAR image, the sea clutter becomes complex in the time and spatial domains, and the existing models are not suitable, resulting in the severe degradation of the CFAR detection performance and many false alarms [4]. Gui et al [16] extracted a new feature from the proposed power-entropy decomposition, called the high-entropy scattering amplitude (HESA), to detect ships, and experiments verified that HESA achieves good detection performance. In order to develop new CP SAR features that are simple and suitable for complex sea states, we analyzed the scattering difference between the ships and the sea surface by introducing the sea surface roughness. Experiments are carried out to verify the better ship detection performance based on the new feature compared with the roundness, delta, HESA and CFAR methods in low, medium and high sea states.

Data and Polarization Features
Features from FP Data
Features from CP and DP Data
Sample Selection
Mutual Information Analysis
Roundness
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Detection Results and Discussion
Comparisons Between Phase Factor and CFAR Detectors

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