Ship Detection in SAR Image Based on the Alpha-stable Distribution.

Changcheng Wang,Xiaofeng Li,Mingsheng Liao

doi:10.3390/s8084948

Abstract

This paper describes an improved Constant False Alarm Rate (CFAR) ship detection algorithm in spaceborne synthetic aperture radar (SAR) image based on Alpha-stable distribution model. Typically, the CFAR algorithm uses the Gaussian distribution model to describe statistical characteristics of a SAR image background clutter. However, the Gaussian distribution is only valid for multilook SAR images when several radar looks are averaged. As sea clutter in SAR images shows spiky or heavy-tailed characteristics, the Gaussian distribution often fails to describe background sea clutter. In this study, we replace the Gaussian distribution with the Alpha-stable distribution, which is widely used in impulsive or spiky signal processing, to describe the background sea clutter in SAR images. In our proposed algorithm, an initial step for detecting possible ship targets is employed. Then, similar to the typical two-parameter CFAR algorithm, a local process is applied to the pixel identified as possible target. A RADARSAT-1 image is used to validate this Alpha-stable distribution based algorithm. Meanwhile, known ship location data during the time of RADARSAT-1 SAR image acquisition is used to validate ship detection results. Validation results show improvements of the new CFAR algorithm based on the Alpha-stable distribution over the CFAR algorithm based on the Gaussian distribution.

Highlights

Synthetic Aperture Radar (SAR) is an active radar that can provide high resolution images in the microwave band under all weather conditions
The Constant False Alarm Rate (CFAR) algorithm is widely used for setting a threshold so that we can find targets that are statistically significant above the background signal while maintaining a constant false alarm rate [1, 12]
SAR image used in this study was obtained from the Alaska SAR Demonstration (AKDEMO) program

Summary

Introduction

Synthetic Aperture Radar (SAR) is an active radar that can provide high resolution images in the microwave band under all weather conditions. SAR images have been widely used for fishing vessel detection, ship traffic monitoring and immigration control [1,2]. Numerous studies have been performed to develop ship detection algorithms in SAR images automatically. Ships can be identified as hard targets or by their wakes [3,4,5] in the SAR image. Of ships is higher than the surrounding sea clutter. This is due to the effect of multiple bounces of incoming radar waves from the ships superstructure [6]. Ships can be separated from the sea cluster with an appropriate choice of RCS threshold.

Methods

Results

Conclusion