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Details of Grant 

EPSRC Reference: EP/R009260/1
Title: Assessment of Sea Surface Signatures for Naval Platforms Using SAR Imagery (AssenSAR)
Principal Investigator: Achim, Professor AM
Other Investigators:
Hogan, Professor SJ Bull, Professor D
Researcher Co-Investigators:
Project Partners:
BAE Systems Qioptiq Limited
Department: Electrical and Electronic Engineering
Organisation: University of Bristol
Scheme: Standard Research
Starts: 01 January 2018 Ends: 31 December 2021 Value (£): 720,036
EPSRC Research Topic Classifications:
Artificial Intelligence Digital Signal Processing
Image & Vision Computing
EPSRC Industrial Sector Classifications:
Aerospace, Defence and Marine
Related Grants:
Panel History:
Panel DatePanel NameOutcome
05 Sep 2017 EPSRC ICT Prioritisation Panel Sept 2017 Announced
Summary on Grant Application Form
In space imaging, enhanced image quality is key to the detection and characterisation of difficult and transient targets. For example, accurate evaluation of the sea surface conditions can help with the detection and characterisation of ship wakes. These provide key information for tracking (illegal) vessels and are also useful in classifying the characteristics of the wake generating vessel.

Until recently, one of the main factors hampering research into sea surface modelling was the lack of sufficient data of high enough quality, able to accurately describe the sea surface. Remote-sensing technologies have however shown remarkable progress in recent years and the availability of remotely sensed data of the Earth and sea surface is continuously growing. Several European missions (e.g., the Italian COSMO/SkyMed or the German TerraSAR-X) have developed a new generation of satellites exploiting synthetic aperture radar (SAR) to provide spatial resolutions previously unavailable from space-borne remote sensing. The UK is currently developing the first of a constellation of four satellites that will constitute the NovaSAR mission. This represents a milestone for Earth-observation capabilities but also requires the development of novel image modelling, analysis, and processing techniques, able to cope with this new generation of data and to optimally exploit them for information-extraction purposes.

Indeed, the mathematical modelling and understanding of wakes and other sea surface signatures can be greatly enhanced through image analysis and information extraction from SAR imagery. Hence, this project is concerned not only with the development and validation of new sea surface models, but also with the design of very advanced methods for enhancing SAR image quality and for subsequent information extraction.

The results of this project will be important in the detection and tracking of illegal vessels involved in smuggling goods or humans. They will also be indicative in terms of understanding and classifying the characteristics of the wake generating vessel. As a consequence, the work will directly benefit the design of stealthy vessels that can avoid such detections, reducing the risk to naval operations.

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Organisation Website: http://www.bris.ac.uk