Low Coherence Sensing Matrices Based on Best Spherical Codes

A method for constructing low coherence sensing matrices based on best spherical codes is proposed. Such matrices are applied in Compressed Sensing (CS) to obtain measurements of a sparse vector. With the means of CS, it is possible to reconstruct the sparse vector from a small number of measurements. Several properties have been considered in order to determine the CS-suitability of matrices, e.g. the restricted isometry property or the coherence. By the proposed construction method, the coherence of the sensing matrix is optimized. Numerical simulation results demonstrating the p