Abstract
This paper uses the sparse representation framework to investigate localization of near‐field sources (e.g., underwater bottom or buried targets) from the data captured using two uniform linear sensor (hydrophone) subarrays. The connection between the two array steering transformation matrices of the near‐field sources corresponding to the two subarrays is first analyzed using the second Taylor expansion. This connection allows the construction of a new equivalent far‐field steering matrix for each near‐field source, hence converting the near‐field source localization problem to a more convenient far‐field one. The relationship between the signals observed by the two subarrays and the new constructed far‐field directional matrix is investigated indicating that the DoA estimates of the sources can be cast into finding a solution to a sparse representation problem. The resolution of the sparse equation will also be discussed. Finally, simulation results are presented to demonstrate the effects of different noise levels on the accuracy of the DoA estimation for the cases of single and multiple sources.
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