Scope of the project is to perform activities and provide deliverables in relation to Use of ML techniques to optimize the adaptive beam-steering capabilities of CRPAs for GNSS user receivers.
The core objectives of the project are:
• Identify the best ML algorithm for adaptive null-steering beamformer with a compact antenna (elements spacing <λ/2)
• Develop and evaluate the real-time adaptive performances of a CRPAs receiver demonstrator with a compact antenna based on the selected ML algorithm.
• Compare the real-time adaptive performances of the ML algorithm against a conventional null-steering beamformer with a compact antenna.
• Compare the real-time adaptive performances of the ML algorithm with a compact
CRPA antenna against a conventional null-steering beamformer with two standard- dimensions antennas (i.e. with element spacing equal to λ/2). 
The target TRL for the demonstrator is 4.