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Sep 2026

Transformer-based joint two-dimensional range and depth synchronous localization of underwater acoustic target.

Matched-field processing (MFP) is a conventional method for underwater acoustic target localization but is often sensitive to systematic environmental mismatch. This paper presents a transformer-based deep learning framework for joint two-dimensional (2D) range and depth localization of a fixed underwater sound source....

Zi-Kun Meng, Wen Zhang, Jian Shi et al. · 0 citations
Open access Jul 2026

Analysis of the Adaptability and Application of Matched-Field Processors for Stationary and Maneuvering Targets in Shallow Water

Passive acoustic localization in complex shallow waters requires algorithms tailored to specific operational constraints. This paper investigates the adaptability, computational efficiency, and statistical performance boundaries of five matched-field processing (MFP) methods—Bartlett, Minimum Variance Distortionless Re...

Zikun Meng, Wen Zhang, Jian Shi et al. · 0 citations

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