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

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.

Keywords
SAR; Maritime Surveillance; ship detection; Generalized Likelihood Ratio Test (GLRT); polarimetry

People

Dr Armando Marino

Associate Professor, Biological and Environmental Sciences