Ship Detection in GF-3 NSC Mode SAR Images

Abstract

GF-3, the first C-band full-polarimetric Synthetic Aperture Radar (SAR) satellite with a space resolution up to 1 m, has multiple strip and scan imaging modes. In this paper, we propose a maritime ship detection algorithm that detects ship targets via pixel classification in a Bayesian framework and employ effective enhancement methods to improve detection performance based on the data characteristics. We compare and analyze the results of detection experiments using the proposed algorithm with those of several Constant False Alarm Rate (CFAR) algorithms. The experimental results verify the effectiveness of the proposed algorithm.

Journal

Title: Journal of Radars

Publisher: Chinese Academy of Sciences

Publication date (Electronic): 01 October 2017

Volume: 6

Issue: 5

Pages: 473-482

Affiliations

[1 ] ①(Shanghai Key Laboratory of Intelligent Sensing and Recognition, Shanghai Jiao Tong University, Shanghai 200240, China)

[2 ] ②(China Academy of Space Technology-Xi’an, Xi’an 710100, China)

Article

Doaj ID: 804eb6578d5d41d8ae8c065293b30e7e

DOI: 10.12000/JR17059

License:

This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Product

Self URI: http://radars.ie.ac.cn/fileup/HTML/R17059.htm

Self URI (journal page): http://radars.ie.ac.cn/EN/volumn/home.shtml

Categories

Subject: Technology (General)

Subject: T1-995