A novel Digital Alias-free Signal Processing method by using Weighted Periodic Nonuniform Sampling

摘要

Weighted Periodic Nonuniform Sampling (WPNS) for Digital Alias-free Signal Processing is analysed. The methodology of measuring the level of aliasing within the required range of frequencies is proposed. The optimal WPNS is found by searching a carefully selected subspace of feasible solutions and applying Lawson algorithm for weight calculation. We describe the improvements that have been made to the algorithm of searching the optimal sampling instants. It is shown that WPNS has better alias-suppression properties than traditional PNS.