Postgraduate research opportunities Cognitive Jamming Waveform Optimisation with Application of AI

Jamming is a form of electronic countermeasures (ECM) to radar systems. There are two key types of active jamming: noise and deceptive. Noise, also known as blanket jamming, aims to saturate the radar receiver through noise-like transmissions, while deceptive jamming generally emits altered copies of the radar signal to introduce false targets. In order to perform any form of jamming, the ECM systems should have a knowledge of the transmitted signal. Properties such as operating frequency and bandwidth are necessary for noise transmissions while further knowledge on the waveform modulation and pulse repetition frequency might be necessary for effective deceptive jamming. To combat jamming, surveillance systems may employ electronic counter-countermeasure techniques (ECCM), also known as antijamming, such as frequency hopping. In such cases the radar might switch its emissions to a different frequency than the one the jammer is operating at. It is hence important for a jamming system to not only operate based on prior knowledge on the radar transmissions but also monitor changes and adapt.

The PhD project aims to investigate adaptive jamming waveform designs optimised to mitigate the sensing capabilities of radar systems. Novel algorithms and signal processing schemes will be developed to offer jamming solutions in different channel and target scenarios including systems utilising counter-counter measure techniques. Artificial Intelligence (AI) architectures will be of main focus to enable high adaptability.