Real‐valued sparse representation for single snapshot direction‐of‐arrival estimation in shipborne high‐frequency surface wave radar

Abstract

By exploiting the intrinsic sparsity of the spatial spectrum for a given resolution cell of range and Doppler, this study introduces the recently developed sparse representation approaches for direction-of-arrival estimation in shipborne high-frequency surface wave radar (HFSWR). These approaches can reconstruct the sparse signal and obtain highresolution spatial spectrum with a small number of snapshots or even single snapshot. A generalised real-valued sparse representation, which seeks to replace the complex-valued problem with a real one, is proposed to reduce the computational complexity and improve the resolution probability and the estimation accuracy. The advantage of the proposed method is demonstrated by theoretical analysis and numeral simulations. Furthermore, validation of the proposed method is verified by the experiment of shipborne HFSWR on the Yellow Sea of China.

Direction of arrival estimation under Class A modelled noise in shallow water using variational Bayesian inference method

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Research on the Primary Features of the Internet of Things System and the Corresponding Data Communication Characteristics based on Sparse Coding and Joint Deep Neural Network

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