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Lecture

Detection and Classification of Sea Surface Signatures Using Synthetic Aperture Radar Imagery

Hosted by IET Bristol

About

Synthetic Aperture Radar (SAR) has become a key remote sensing modality for maritime surveillance, offering all-weather, day-and-night imaging capabilities. This talk addresses recent advances in the detection and classification of sea surface signatures in SAR imagery, with a particular focus on ships and their associated wake patterns. We begin by examining classical and modern approaches to ship detection, including statistically grounded Constant False Alarm Rate (CFAR) methods and their extension to superpixel-based formulations, which improve robustness in heterogeneous sea clutter. These are complemented by deep learning-based detection frameworks that leverage contextual information to enhance performance in both inshore and offshore environments.
Beyond direct target detection, the talk explores the role of ship wakes as rich physical signatures that can aid in vessel detection and provide insight into motion characteristics such as speed and heading. Inverse problem formulations involving the Radon transform and model-based analysis are discussed alongside recent machine learning approaches for wake detection and exploitation. A key enabler for these developments is the realistic simulation of SAR sea surface imagery, allowing the generation of large-scale annotated datasets for training and evaluation. Finally, the integration of these methodologies into automated pipelines for ship classification is presented, demonstrating how combined analysis of targets and their wakes can support robust maritime situational awareness and large-scale spatio-temporal monitoring.

Electromagnetics
Information and Communications
Transport
Security in the Modern World

2

Continuing Professional Development

This event can contribute towards your Continuing Professional Development (CPD) hours as part of the IET's CPD monitoring scheme.

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13 May 2026 

6:30pm - 8:30pm

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Organiser

  • Bristol Local Network

Registration information

Room details and timings :
Queens Building Pugsley Lecture Theatre (QB1.40)
University of Bristol
University Walk
Bristol
BS8 1TR

QB front door ///solve.harder.shaped
https://w3w.co/solve.harder.shaped

https://www.bristol.ac.uk/directory/learning-facilities/central-teaching-spaces/queens-building/140-pugsley-lecture-theatre/

Parking available on Woodland Road (metred, pay via RingGo) or in nearby Trenchard St multi-storey.

Speakers

Alin Achim

Professor - University of Bristol

Professor Alin Achim received the B.Sc. and M.Sc. degrees in electrical engineering from “Politechnica” University of Bucharest, Romania, in 1995 and 1996, respectively, and the Ph.D. degree in biomedical engineering from the University of Patras, Greece, in 2003. He then obtained an European Research Consortium for Informatics and Mathematics (ERCIM) Post-doctoral Fellowship, which he spent with the Institute of Information Science and Technologies (ISTI-CNR), Pisa, Italy, and the French National Institute for Research in Computer Science and Control (INRIA) Sophia Antipolis, France. In October 2004, he joined the Department of Electrical and Electronic Engineering, University of Bristol, Bristol, U.K., as a Lecturer, where he became a Senior Lecturer (Associate Professor) in 2010 and a Reader in biomedical image computing in 2015. Since August 2018, he holds the Chair of Computational Imaging, at the University of Bristol. From 2019 to 2020, he was a Leverhulme Trust Research Fellow with the Laboratoire I3S, Université Cote d’Azur. He was awarded a Chair of Excellence by the University of the Code d’Azur in 2020.
Alin has coauthored over 200 scientific publications, including 69 journal articles. His research interests include statistical signal, image, and video processing and machine learning, with applications in both biomedical imaging and Earth Observation. He was/is an Elected Member of the Bio Imaging and Signal Processing Technical Committee of the IEEE Signal Processing Society, an Affiliated Member (invited) of the Signal Processing Theory and Methods Technical Committee, and a member of the IEEE Geoscience and Remote Sensing Society’s Image Analysis and Data Fusion Technical Committee. He was/is an Associate Editor / Senior Area Editor of the IEEE Transactions on Image Processing, and of the IEEE Transactions on Computational Imaging.

Reasons to attend

Come and learn about cutting-edge technologies, have some free refreshments, and network with local engineers if you wish.

Location

Pugsley Lecture Theatre (1.40), Queen's Building

University Walk
Bristol
Bristol City
BS8 1TR
United Kingdom

Queens Building Pugsley Lecture Theatre (QB1.40)
University of Bristol
University Walk
Bristol
BS8 1TR

QB front door ///solve.harder.shaped
https://w3w.co/solve.harder.shaped


https://www.bristol.ac.uk/directory/learning-facilities/central-teaching-spaces/queens-building/140-pugsley-lecture-theatre/

Parking available on Woodland Road (metred, pay via RingGo) or in nearby Trenchard St multi-storey.

Programme

Arrival, Networking and Refreshments: 18.30
Presentation: 19:00 – 20:00
Networking: 20:00 - 20:30

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Registration

Register

Free of charge