Combined CS and DL techniques for DOA with a Rotman Lens

Grand Challenges in Radar Signal Processing

“…Over the last decade, CS and sparse signal reconstruction methods have been widely applied to tackle traditional radar problems, e.g., highresolution target Direction of Arrival (DOA) estimation (Fortunati et al, 2014), as well as emerging problems, e.g., spectrum sensing in cognitive radar (Aubry et al, 2019). More recently, sparse sensing was combined with machine learning to solve the problem of missing or limited data (Cheng et al, 2020;Weiß et al, 2020). Optimization methods with sparse regularizations and constraints have been applied in both phased arrays and multiple-input multiple-output (MIMO) radar platforms for efficient radar aperture design under a given number of frontend receivers.…”