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Advanced Target discrimination using fingerprinting based on High Resolution Range and micro-Doppler profiles


Project Description

Applications are invited for a PhD studentship fully funded by the University of Strathclyde and Leonardo MW.

Ground-based airborne imaging radar systems are frequently required to provide enhanced situational awareness information beyond target detection and tracking. In particular, target recognition is an important challenging task that modern radars are frequently requested to provide. Understanding the characteristics of targets, including profiles, polarimetric responses and micro-motions is fundamental to be able to characterise and discriminate cooperative and non-cooperative targets such as vehicles, ballistic missiles and ships. Novel radar systems are now able to provide enriched target information, such as High Resolution Range Profiles (HRRPs) and micro-Doppler (MD) signatures, however there has been much less research reported on how to exploit and maximise the benefits of these systems for the target recognition task. This project will develop models and algorithms to exploit and assess the capabilities of what we will call " a target’s fingerprint" extracted from both HRRP and MD to perform advanced target recognition.
Micro-motion characteristics of different targets will be utilised in order to extract unique signatures leading to accurate discrimination between a number of classes. Of particular interest is the derivation of realistic motion models of targets and the way that different motion and observation parameters, e.g. manoeuvring and observation angle, affect the received radar returns. Individual characteristics in range and Doppler domain will be combined and used to generate both detailed, image-like representations and more abstract feature vectors through novel signal processing approaches.

The successful candidate will: 1)Develop novel target signal models 2) Develop algorithms for target fingerprinting based target tracking in multi-target scenario 3) Develop algorithms for target behaviour prediction based on fingerprinting and tracking 4) Acquire experimental data in controlled environment using radar sensors available at Strathclyde 5) Validate models and algorithms on lab data and on data provided by Leonardo MW.

This is a unique opportunity to work at the Sensor Signal Processing & Security Laboratories (SSP&S labs) of the Centre of Excellence in Signal and Image Processing of the University of Strathclyde and to collaborate with a world leading company in Defence sector as Leonardo MW. SSP&S labs are located in the new Technology and Innovation Centre (TIC) of the University of Strathclyde, a stimulating cross-disciplinary environment where the core of the industrial research of Strathclyde is developed.

For enquiries contact Dr Carmine Clemente ()


Funding Notes

Project duration 3.5 years

Fundings available of UK applicants only

How good is research at University of Strathclyde in Electrical and Electronic Engineering, Metallurgy and Materials?

FTE Category A staff submitted: 59.20

Research output data provided by the Research Excellence Framework (REF)

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