Horizontal Wavenumber Estimation Technique Based on Compressive Sensing in Shallow Water

The horizontal wavenumber of normal mode contains environmental information of ocean waveguide, which is an important environmental sensing parameter. To solve the problem of large array aperture requirement and poor resolution performance of the existing horizontal array wavenumber spectrum estimation methods, a horizontal wavenumber estimation technique based on sparse processing is proposed. On the basis of normal mode theory in shallow water, the sparsity of horizontal wavenumber in shallow water is utilized. For the case of coherent and incoherent processing of multiple snapshot data, Basis Pursuit De-Noising(BPDN) and Sparse Bayesian Learning(SBL) methods are used to estimate the horizontal wavenumber. The resolution of horizontal wavenumber spectrum with Sparse Bayesian Learning method is verified to be best through simulation.