A Density Clustering-Based CFAR Algorithm for Ship Detection in SAR Images-Reference-Cited by-同舟云学术

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A Density Clustering-Based CFAR Algorithm for Ship Detection in SAR Images

Published:2024 Issue: Volume:21 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Li Yang¹^ORCID,Wang Zeyu¹^ORCID,Chen Hongmeng²^ORCID,Li Yachao³^ORCID

Affiliation:

1. State Key Laboratory of Networking and Switching Technology, School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China

2. Beijing Institute of Radio Measurement, Beijing, China

3. National Laboratory of Radar Signal Processing, Xidian University, Xi’an, Shaanxi, China

Funder

National Natural Science Foundation of China

Foundation of National Key Laboratory of Radar Signal Processing

National Key Research and Development Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/8859/10365397/10521727.pdf?arnumber=10521727

Reference19 articles.

1. A CFAR Target-Detection Method Based on Superpixel Statistical Modeling

2. Ship Detection in SAR Images via Local Contrast of Fisher Vectors

3. Ship Surveillance With TerraSAR-X

4. A New CFAR Ship Detection Algorithm Based on 2-D Joint Log-Normal Distribution in SAR Images

5. Superpixel-Level CFAR Detector Based on Truncated Gamma Distribution for SAR Images

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