About the Project
1. Develop statistical fluctuation models to analyse RCS characteristics of drones at millimetre-wave frequencies using data available at St Andrews.
2. Characterise RCS values of drones in terms of fuselage and propeller material, size, shape and aspect angles.
3. Study polarisation dependencies of the RCS values of the drones at millimetre-wave frequencies by using the available data and acquiring more data by using radars available at St Andrews.
4. Develop EM scattering models of commercial drones to study and characterise the micro-Doppler signatures produced by the propellers. Understanding of the features will be further strengthened by lab-based controlled environment experimental data collection and analysis.
5. Wavelet analysis of the micro-Doppler signatures of drones. Develop wavelet signature based drone classification algorithm for real-time application.
6. Inverse Synthetic Aperture Radar (ISAR) imaging of drones using high resolution range profiles (HRRP) data. Study the feasibility of distinguishing attached payloads and different models of drones using ISAR data.
7. Develop techniques for Neural Network based drone classification algorithm for real-time application. Extensive data is already available at St Andrews to create a training database. The candidate will also design and set up experimental trials to make the database larger and more diverse in terms of number of drones and surrounding environment.
The candidate should have a degree in Physics or Electronic Engineering, ideally with some knowledge of radar, signal processing or microwave technology. Familiarity with MATLAB and C programming would be an advantage.
The Millimetre Wave Group (https://www.st-andrews.ac.uk/~mmwave/) is extremely well equipped with test equipment, measurement facilities including an outdoor test range with dedicated lab, and a large array of components and subsystems enabling rapid development. We have built 13 radar systems at frequencies of 24, 77, 38, 94, 220 and 340 GHz, many of which would be available for data collection in this project.
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