Our team and mission

The Sentinel-1 Project is responsible for the development of the Sentinel-1 Next Generation (NG) mission concept, the spacecraft and the Synthetic Aperture Radar (SAR) and Automatic Identification System (AIS) payloads. In addition, the Sentinel-1 team has responsibility for the satellite launch and in-orbit commissioning, i.e. end-to-end system performance and calibration. This also involves the development of prototype SAR and SAR interferometry (InSAR) data processors and the Calibration and Performance Analysis Facility (CPAF).

Sentinel-1NG is the successor of the Earth Observation Copernicus Sentinel-1 SAR mission. Copernicus is the most ambitious Earth observation programme to date. It is a cornerstone of Europe’s efforts to monitor the planet and its many ecosystems. Sentinel-1 enables an instantaneous mapping of wide-area surface deformation, caused, e.g., by tectonic processes or ground subsidence, as well as the monitoring of ice sheet and glacier dynamics.

S1 Mission

https://sentiwiki.copernicus.eu/web/s1-mission

The goal of Sentinel-1NG is to provide an enhanced long-term continuity of C-band SAR observations beyond the next decade (2030) in support of operational Copernicus services that are routinely using Sentinel-1 data. In addition, the enhanced capabilities of Sentinel-1NG, compared to Sentinel-1, along with novel imaging capabilities enable the further development and improvement of operational applications.

This improvement of the Sentinel-1NG imaging capabilities (i.e. a better spatial resolution, a shorter revisit time, a longer orbital SAR duty cycle, a better radar sensitivity and a shorter repeat-pass orbit interval for SAR interferometry) over the performance currently achievable with Sentinel-1 is possible by employing an envisioned new multi-channel SAR architecture that enables novel techniques, such as SCORE (Scan On Receive) and MAPS (Multiple Azimuth Phases),combined with a ScanSAR mode. Another advantage of systems with multiple channels in azimuth is the inherent Along Track Interferometry (ATI) capability, which can be used for accurate velocity estimation of ocean surface currents and vessels.

The Sentinel-1 NG is expected to enable an efficient maritime surveillance, i.e., the detection of vessels of different sizes, due to its wide-area coverage and all-weather monitoring capability.
Information on the characteristics of ocean-going vessels, such as location, dimensions, heading and velocity, is required for coastal security, maritime safety, and fisheries and environmental enforcement. Recently, the importance of ship detection and identification has risen significantly due to the increase of piracy acts, smuggling, and the demand for accountability of polluting tankers causing oil spills.

Conventional ship detection is based upon detecting bright point-like target signatures against a background of radar sea clutter noise in SAR intensity images. In practice, a Constant False Alarm Rate (CFAR) is specified, which implies that a threshold of detection is set according to the local statistics of the radar sea clutter. The threshold method works well for large ships due to their high intensity value compared to sea clutter. However, in cases of heavy sea state, the sea clutter intensity rises to levels close to that of the ship making this method unreliable for small ships.

CFAR detection is based on a statistical model of the intensity of the sea surface signal (clutter). In the literature, the K-distribution is arguably the most used, which however has some limitations. Recently, a new sea clutter model, i.e., the 3MD model, has been proposed by a Canadian team from DRDC-Ottawa, which outperforms the K-distribution especially under challenging, heterogeneous, sea state conditions.

Alternatively, the Displaced Phase Centre Antenna (DPCA) method suppresses effectively the interfering clutter signal (i.e. clutter cancellation), thus improving significantly the probability of detection of vessels under challenging sea state conditions, and the phase-based Along-Track Interferometry (ATI) provides additional information about the vessel’s velocity.

Candidates interested are encouraged to visit the ESA website: http://www.esa.int

Field(s) of activity for the internship

Topic of the internship: Ship Detection using Multi-Channel SAR Systems in support of Sentinel-1 Next Generation

The following tasks shall be performed during the internship considering your interest and experience.

Your activities will focus on implementing a ship detection algorithm in Python that is already established within the field of SAR applications for maritime surveillance and has been developed by experts from DRDC-Ottawa (Canada). Your primary objective will be to adapt and apply this algorithm to Sentinel-1C (S1C) data, assessing its performance by comparing detected vessels with Automatic Identification System (AIS) data acquired simultaneously by S1C.

As part of your tasks, you will:

• become familiar with the principles of Synthetic Aperture Radar (SAR) remote sensing of both current conventional SAR systems and future multichannel SAR systems, such as Sentinel-1 Next Generation (S1NG);
• study the fundamentals of Along Track Interferometry (ATI) and their applications to maritime surveillance, with a particular emphasis on vessel detection and velocity estimation;
• implement and validate ship detection algorithms based on different sea clutter models (K-distribution and 3MD) using Sentinel-1SAR data considering different sea states and vessel sizes, systematically comparing the results with AIS ground truth to evaluate detection performance and limitations;
• analyze the results and extrapolate how S1NG’s enhanced capabilities, particularly its multi-channel azimuth system, could improve ship detection through DPCA clutter suppression, velocity estimation, and overall performance;
• propose strategies or recommendations for optimizing ship detection algorithms to fully utilize the advantages offered by S1NG’s advanced sensor characteristics.

Behavioural competencies

Result Orientation
Operational Efficiency
Fostering Cooperation
Relationship Management
Continuous Improvement
Forward Thinking

For more information, please refer to ESA Core Behavioural Competencies guidebook

Education

You must be a university student, preferably studying at master’s level. In addition, you must be able to prove that you will be enrolled at your University for the entire duration of the internship.

Additional requirements

The working languages of the Agency are English and French. A good knowledge of one of these is required. Knowledge of another ESA Member State language is an asset.

During the interview, your motivation for applying to this role will be explored.

Specific competence in one of the following disciplines shall be considered an asset:

• knowledge of signal processing, geophysics, electromagnetics, remote sensing;
• familiarity with development of data analysis tools using, e.g., Python or MATLAB.