SAR Ship Detection for Rough Sea Conditions

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

Automatic refocus and feature extraction of single-look complex SAR signatures of vessels

In recent years, spaceborne synthetic aperture radar ( SAR) technology has been considered as a complement to cooperative vessel surveillance systems thanks to its imaging capabilities. In this paper, a processing chain is presented to explore the potential of using basic stripmap single-look complex ( SLC) SAR images of vessels for the automatic extraction of their dimensions and heading. Local autofocus is applied to the vessels' SAR signatures to compensate blurring artefacts in the azimuth direction, improving both their image quality and their estimated dimensions. For the heading, the orientation ambiguities of the vessels' SAR signatures are solved using the direction of their ground-range velocity from the analysis of their Doppler spectra. Preliminary results are provided using five images of vessels from SLC RADARSAT-2 stripmap images. These results have shown good agreement with their respective ground-truth data from Automatic Identification System ( AIS) records at the time of the acquisitions.Postprint (published version

Ship detection on open sea and coastal environment

Synthetic Aperture Radar (SAR) is a high-resolution ground-mapping technique with the ability to effectively synthesize a large radar antenna by processing the phase of a smaller radar antenna on a moving platform like an airplane or a satellite. SAR images, due to its properties, have been the focus of many applications such as land and sea monitoring, remote sensing, mapping of surfaces, weather forecasting, among many others. Their relevance is increasing on a daily basis, thus it’s crucial to apply the best suitable method or technique to each type of data collected. Several techniques have been published in the literature so far to enhance automatic ship detection using Synthetic Aperture Radar (SAR) images, like multilook imaging techniques, polarization techniques, Constant False Alarm Rate (CFAR) techniques, Amplitude Change Detection (ACD) techniques among many others. Depending on how the information is gathered and processed, each technique presents different performance and results. Nowadays there are several ongoing SAR missions, and the need to improve ship detection, oil-spills or any kind of sea activity is fundamental to preserve and promote navigation safety as well as constant and accurate monitoring of the surroundings, for example, detection of illegal fishing activities, pollution or drug trafficking. The main objective of this MSc dissertation is to study and implement a set of algorithms for automatic ship detection using SAR images from Sentinel-1 due to its characteristics as well as its ease access. The dissertation organization is as follows: Chapter 1 presents a brief introduction to the theme of this dissertation and its aim, as well as its structure; Chapter 2 summarizes a variety of fundamental key points from historical events and developments to the SAR theory, finishing with a summary of some well-known ship detection methods; Chapter 3 presents a basic guideline to choose the best ship detection technique depending on the data type and operational scenario; Chapter 4 focus on the CFAR technique detailing the implemented algorithms. This technique was selected, given the data set available for testing in this work; Chapter 5 presents the results obtained using the implemented algorithms; Chapter 6 presents the conclusions, final remarks and future work

Imaging radar contributions to a major air-sea-ice interaction study in the Greenland Sea

By virtue of the Synthetic Aperture Radar (SAR's) imaging capabilities, such as all-weather imaging, relatively high resolution, and large dynamic range of backscatter from SAR ice and open ocean, information on the important marginal ice zone (MIZ) parameters can be derived from the SAR data. Information on ice edge location and location of ice-edge eddies, for example, can be obtained directly from examination of the imagery as can detection of ocean fronts and internal waves. With machine-assisted manual image analysis, estimates of ice concentration, floe size distributions, and ice field motion can also be derived. Full digital analysis, however, is required to obtain gravity wave spectral information and backscatter statistics for ice type discrimination and automated ice concentration algorithms

A ship detector applying Principal Component Analysis to the polarimetric Notch Filter

Ship detection using polarimetric synthetic aperture radar (PolSAR) data has attracted a lot of attention in recent years. Polarimetry can provide information regarding the scattering mechanisms of targets, which helps discriminate between ships and sea clutter. This enhancement is particularly valuable when we aim at detecting smaller vessels in rough sea states. This work exploits a ship detector called the Geometrical Perturbation-Polarimetric Notch Filter (GP-PNF), and it is aimed at improving its performance especially when less polarimetric images are available (e.g., dual-polarimetric data). The idea is to design a new polarimetric feature vector containing more features that are renowned to allow separation between ships and sea clutter. Then, a Principal Component Analysis (PCA) is further used to reduce the dimensionality of the new feature space. Experiments on four real Sentinel-1 datasets are carried out to demonstrate the validity of the proposed method and compare it against other ship detectors. Analyses of the experimental results show that the proposed algorithm can not only reduce the false alarms significantly, but also enhance the target-to-clutter ratio (TCR) so that it can more effectively detect weaker ships

A Multispectral Look at Oil Pollution Detection, Monitoring, and Law Enforcement

The problems of detecting oil films on water, mapping the areal extent of slicks, measuring the slick thickness, and identifying oil types are discussed. The signature properties of oil in the ultraviolet, visible, infrared, microwave, and radar regions are analyzed

Radar imaging mechanism of marine sand waves at very low grazing angle illumination

The investigations carried out between 2002-2004 during several field experiments within the Op-erational radar and optical mapping in monitoring hydrodynamic, morphodynamic and environ-mental parameters for coastal management project (OROMA) aimed to improve the effectiveness of new monitoring technologies such as shipborne imaging radars in coastal waters. The coastal monitoring radar of the GKSS Research Centre, Geesthacht, Germany, is based on a Kelvin Hughes RSR 1000 X-band (9.42 GHz) VV polarized river radar and was mounted on board the research vessel Ludwig Prandtl during the experiments in the Lister Tief, a tidal inlet of the German Bight in the North Sea. The important progress realized in this investigation is the availability of calibrated X-band radar data. Another central point of the study is to demonstrate the applicability of the quasi-specular scattering theory in combination with the weak hydrodynamic interaction the-ory for the radar imaging mechanism of the sea bed. It is shown that specular point scattering con-tributes significantly to the normalized radar cross section (NRCS) modulation due to marine sand waves. According to the theory quasi-specular scattering can be applied for wind speeds Uw ≤ 8 m s-1. Measured and simulated NRCS modulations caused by flood and ebb tide oriented marine sand waves have been compared and agree fairly wel

JRC - Metasensing Coupled Spaceborne & Airborne SAR Campaign in Rotterdam

The European maritime area is one of Europe’s most important assets with regard to resources, security and ultimately prosperity of the Member States. A significant part of Europe’s economy relies directly or indirectly on it. It is not just the shipping or fisheries industries and their related activities. It is also shipbuilding and ports, marine equipment and offshore energy, maritime and coastal tourism, aquaculture, submarine telecommunications, blue biotech and the protection of the marine environment. The European maritime area faces several risks and threats posed by unlawful activities, such as drugs trafficking, smuggling, illegal immigration, organised crime and terrorism. Piracy in international waters also constitutes a threat to Europe since it can disrupt the maritime transport chain. These risks and threats can endanger human lives, marine resources and the environment, as well as significantly disrupt the transport chain and global and local security. It is anticipated that these risks and threats will endure in the mid and long run. In order to keep Europe as a world leader in the global maritime economy, an effective integrated/interoperable, sustainable maritime surveillance system and situational awareness are needed. A significant number of unlawful maritime activities, such as illegal immigration, drugs trafficking, smuggling, piracy and terrorism involve mainly small boats, because small boats are faster and more difficult to detect using conventional means. Hence, it is very important to find out the feasibility of using new sensors and platforms, such as SAR or Unmanned Aerial Systems (UAS) for small boat detection, tracking, classification and identification, as well as to study the potential of airborne SAR for maritime surveillance. Since 2010 the EC-JRC has carried out a number of coupled UAS and spaceborne SAR maritime surveillance campaigns to assess the potential of UAS for maritime surveillance, in particular for small boat detection. This report presents the results and conclusions of the JRC – Metasensing Coupled Spaceborne SAR and Airborne SAR campaign carried out in Feb. 2011 in Rotterdam, The Netherlands.JRC.G.4-Maritime affair

Ship detection with spectral analysis of synthetic aperture radar: a comparison of new and well-known algorithms

The surveillance of maritime areas with remote sensing is vital for security reasons, as well as for the protection of the environment. Satellite-borne synthetic aperture radar (SAR) offers large-scale surveillance, which is not reliant on solar illumination and is rather independent of weather conditions. The main feature of vessels in SAR images is a higher backscattering compared to the sea background. This peculiarity has led to the development of several ship detectors focused on identifying anomalies in the intensity of SAR images. More recently, different approaches relying on the information kept in the spectrum of a single-look complex (SLC) SAR image were proposed. This paper is focused on two main issues. Firstly, two recently developed sub-look detectors are applied for the first time to ship detection. Secondly, new and well-known ship detection algorithms are compared in order to understand which has the best performance under certain circumstances and if the sub-look analysis improves ship detection. The comparison is done on real SAR data exploiting diversity in frequency and polarization. Specifically, the employed data consist of six RADARSAT-2 fine quad-polacquisitions over the North Sea, five TerraSAR-X HH/VV dual-polarimetric data-takes, also over the North Sea, and one ALOS-PALSAR quad-polarimetric dataset over Tokyo Bay. Simultaneously to the SAR images, validation data were collected, which include the automatic identification system (AIS) position of ships and wind speeds. The results of the analysis show that the performance of the different sub-look algorithms considered here is strongly dependent on polarization, frequency and resolution. Interestingly, these sub-look detectors are able to outperform the classical SAR intensity detector when the sea state is particularly high, leading to a strong clutter contribution. It was also observed that there are situations where the performance improvement thanks to the sub-look analysis is not so noticeable