Tensor‐based matched‐field processing applied to the SWellEx‐96 data

Abstract

AbstractThis study proposed a matched field source localization method based on tensor decomposition. By considering the advantages of tensors in multidimensional data processing, a three‐dimensional tensor signal model of space‐time‐frequency is constructed, and the signal subspace is estimated using high‐order singular value decomposition. The source position is estimated by matching the measured data tensor signal subspace with the replica field tensor signal subspace. The S5 event data of SWellEx‐96 is processed by the proposed tensor‐based matched‐field processing (TMFP). The comparison with the results of conventional matched field processing shows that TMFP has a better suppression effect on ambient noise under low SNR and better source localization performance.