Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/30890
Appears in Collections:Biological and Environmental Sciences Conference Papers and Proceedings
Author(s): Iervolino, Pasquale
Guida, Raffaella
Amitrano, Donato
Marino, Armando
Title: SAR Ship Detection for Rough Sea Conditions
Citation: Iervolino P, Guida R, Amitrano D & Marino A (2019) SAR Ship Detection for Rough Sea Conditions. In: IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium Proceedings. IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 28.07.2019-02.08.2019. Piscataway, NJ, USA: IEEE. https://doi.org/10.1109/igarss.2019.8900332
Issue Date: 2019
Date Deposited: 27-Feb-2020
Conference Name: IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium
Conference Dates: 2019-07-28 - 2019-08-02
Conference Location: Yokohama, Japan
Abstract: In the Synthetic Aperture Radar (SAR) framework many detection algorithms and techniques have been published in the recent literature; however the detection of vessels whose dimensions are in the order of the image spatial resolution is still challenging in rough sea state scenarios. This issue is addressed in the paper presented here by comparing rationale and performance of two detectors developed by the same authors: the Generalized Likelihood Ratio Test (GLRT) and the Intensity Dual-Polarization Ratio Anomaly Detector (iDPolRAD). Both detectors are tested on a dual-polarization VV/VH Interferometric Wide Swath Sentinel-1 image acquired over the Suruga Bay on the Pacific Coast of Japan. The theory is presented here and the two detectors are compared against the Cell Average-Constant False Alarm Algorithm (CA-CFAR) showing both better performance than CFAR in terms of false alarms rejection.
Status: AM - Accepted Manuscript
Rights: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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