Sparse array design using statistical restricted isometry property

Abstract

The numerical application of the statistical reduced isometry property (StRIP) and statistical null space property (SNSP) is presented and demonstrated for the design of underwater acoustic line arrays. This recent approach predicts the theoretical utility of specific subsampled arrays for compressive sensing. Three subsamplings are presented: Random, Golomb, and Wichmann. The Golomb array has no repeated spacings. The Wichmann array includes every possible interval of spacings. The SNSP is shown insensitive to the cases presented. The StRIP of the Golomb array predicts superior invertibility and is shown to perform well using at-sea data.