2020/08/27 by Matilde Sánchez-Fernández, Sánchez-Fernández, Matilde, Vahid Jamali +5
Engineering · #FOS: Computer and information sciences #Information Theory (cs.IT) #Microwave Imaging and Scattering Analysis #Photoacoustic and Ultrasonic Imaging #Sparse and Compressive Sensing Techniques
paper · pdf · doi:10.48550/arxiv.2008.12323
openalex publication_date 2020/08/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
A full multi--dimensional characterization of the angle of arrival (AoA) has\nimmediate applications to the efficient operation of modern wireless\ncommunication systems. In this work, we develop a compressed sensing based\nmethod to extract multi-dimensional AoA information exploiting the sparse\nnature of the signal received by a sensor array. The proposed solution, based\non the atomic \ℓ0 norm, enables accurate gridless resolution of the AoA in\nsystems with arbitrary 3D antenna arrays. Our approach allows characterizing\nthe maximum number of distinct sources (or scatters) that can be identified for\na given number of antennas and array geometry. Both noiseless and noisy\nmeasurement scenarios are addressed, deriving and evaluating the resolvability\nof the AoA propagation parameters through a multi--level Toeplitz matrix\nrank--minimization problem. To facilitate the implementation of the proposed\nsolution, we also present a least squares approach regularized by a convex\nrelaxation of the rank-minimization problem and characterize its conditions for\nresolvability.\n