ASPIRE
Advanced Signal Processing in Radar and Electronic Warfare
The scope of this focus group within the EMSIG network is to bring together academics, industrialists, and potential end-users working on the development of signal processing techniques for radar sensing and electronic warfare.
Signal processing has a fundamental importance in radar and electronic warfare thanks to its capability to maximize the sensors potentials and provide a wide range of additional functionalities. It has historically shown high capability in enhancing target detection, clutter mitigation, the direction of arrival estimation, beamforming, target classification and imaging and enabling advanced radar modes such as SAR/ISAR, passive radar, multi-static and MIMO.
This focus group will consider both fundamental and applied signal processing solutions that can provide benefits to the radar and EW community.
Statistical signal processing, sub-space techniques, non-linear and adaptive signal processing, sparse representation, compressive sensing, convex and non-convex optimization, time-frequency analysis, and machine learning are just some of the most powerful signal processing tools that have been used to boost the radar and EW capabilities in the recent years and that will probably continue to do so in the future together with more advanced and innovative techniques not yet investigated in this domain.
This focus group is aimed to discuss, investigate and promote the use of advanced signal processing in areas including but not limited to:
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Long range radars: air traffic control, surveillance radar, ballistic missile detection, space situation awareness and over the horizon radars;
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Short Range radars: automotive, healthcare, UAV detection, autonomy;
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Imaging radars: SAR, ISAR, passive SAR/ISAR, Shadow Inverse Synthetic Aperture Radar, polarimetry, interferometry, tomography;
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Multi-function radar systems: MIMO, communicating radars and radar communication systems (RF steganography), digital receiver digital array, LPI radars, electronic protection measures.
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EW systems: angle/frequency/direction of arrival sensors, emitter identification, counter LPI radars, electronic counter measures.
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Advanced concepts: Forward Scattering, multi-static, Orbital Angular Momentum based systems, quantum radars, bio-inspired systems;
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System Friendly signal processing: low size weight and power requirements solutions, high degree of integrations, sensor fusion and resource management.
Chairs
Mohammed Jahangir
Mohammed Jahangir (B.Sc. Ph.D., C.Eng, MIET) is the lead research fellow at the University of Birmingham Quantum Technology Hub Timing and Navigation programme. He is responsible for the development of a fully coherent quantum enabled networked staring radar. Having graduated with 1st class honours from Imperial College he joined the UK MoD research centre in Worcestershire to embark on a research career on surveillance radars. He obtained his PhD from UCL in 2000 on coherent radar clutter statistics. He has nearly three decades experience of working on many aspects of surveillance systems for both defence and the civil sector. He has widely collaborated with academia and industry in his pursuit to drive innovation in radar techniques. In 2013 he joined Aveillant in Cambridge to be the R&D lead for the staring holographic radar and was recognised as a world leading expert on wind farm mitigation and counter drone surveillance. His current focus is on multi-function networked radar that harnesses persistent dwell to track difficult targets in complex clutter environment. He has several patents and published over 50 journal and conference papers. He is an IET Chartership professional registration assessor and interviewer and also active as a STEM ambassador.
Murat Uney
Dr Murat Uney is a lecturer in signal processing at the University of Edinburgh. Previously, he was a Research Fellow at the University of Edinburgh (2013-18), a Research Scientist at the Centre for Maritime Research and Experimentation (2018-21), and a lecturer at the University of Liverpool (2021-25), where he was the Principal Investigator in a collaborative project that developed and analysed coherent long-time integration track-before-detect algorithms for radar signal processing.
His research interests are in the theory of signal processing and machine learning, and probabilistic models and Bayesian computations for applications in sensor signal and data processing.
Murat is a member of the IEEE Signal Processing Society, IEEE Aerospace and Electronic Systems Society, and a fellow of the Higher Education Academy.