Nonuniform sampling reconstruction applied to sparse array beamforming

Abstract

We investigate the application of nonuniform sampling reconstruction to sparse array beamforming to gain insight into its potential and identify additional challenges. The central concept of the nonuniform sampling beamformer is to use the nonuniform samples to reconstruct the samples of a uniform array with the same sampling density as the nonuniform array and then perform conventional beamforming. Our results show the potential of replacing elements in a sparse uniform linear array with uniform linear subarrays and using a nonuniform sampling reconstruction formula in improving the near-in (bandwidth supported by the array sampling density) grating lobes performance. However, this improved performance comes at the expense of significantly worsened performance in the out-of-band region (beyond the near-in grating lobe region). Additionally, the performance of the nonuniform sampling beamformer is extremely sensitive to phase noise. Although increasing the sampling density improved performance, the out-of-band performance and sensitivity are still areas of concern for most sparse arrays.