Work

From Kelvin Wave Patterns to Ship Displacement: An Inverse Prediction Framework Based on a Hull Form Database

Year: 2025

Type: article

Abstract: The estimation of a ship’s displacement volume, ∇, from remote sensing data is of considerable practical value for maritime surveillance and vessel characterization. This paper introduces a practical framework for the inverse estimation of displacement volume from Kelvin ship waves, building upon a prior study through two key extensions. First, the wave amplitude function is recovered using Fourier series expansions combined with the stationary phase method. The displacement volume is then estimated via a two-step procedure: an initial estimate is obtained by identifying a hull with similar amplitude characteristics from a database, followed by a refinement that incorporates discrepancies between the target and candidate wave amplitude functions. In the case studied, the proposed approach achieves a prediction error of 4.02%, demonstrating its potential for non-invasive extraction of hull information from remote sensing data.

Source: Journal of Marine Science and Engineering

DOI: 10.3390/jmse13102019

Authors: Chao Ma, Linwei Wang, Yingjiang Zhao, Haolin Yang, Haoqing Huang, Bohan Cao

Institution: Wuhan University of Technology

Language: English

Topic: Ocean Waves and Remote Sensing

Subfield: Oceanography

Field: Earth and Planetary Sciences

Domain: Physical Sciences

SDG: Life below water

Open Access status: gold

Estimated APC paid: $3,137