Scope:

The high speed and significant manoeuvrability of hypersonic vehicles, particularly hypersonic glide vehicles, create difficult conditions for target detection and tracking, which are exacerbated by changes in radar cross section characteristics. Radar waveforms and signal processing become essential to counter the effects induced by hypersonic threat dynamics. In addition, the last decade has seen a global increase in the use of unmanned aerial vehicles (UAVs) for battlefield intelligence gathering and reconnaissance. Anti-UAV radars therefore need to be developed to detect, identify and track such systems. Innovative approaches (e.g. AI and cognitive methods) can provide the means to select the best waveform receiver filter combination to maximise radar detection and tracking performance also using a feedback loop between the received and transmitted signal characteristics.

This topic therefore focuses on the development of an engineering development model (i.e. demonstrator) capable of supporting tasks such as demonstrating the maturity of innovative technologies in the radar domain and supporting the feasibility of implementing such technologies in terms of time, investment cost, complexity and applicability to military operations. The ultimate aim is to reduce the risks associated with future full sensor development that includes these features.

Beyond defence technologies, this topic also contributes to the STEP objectives as defined in the STEP Regulation in the target investment area of deep and digital technologies.