Identification of Initial Areas for Maritime Search and Rescue Operations Through Drifting Buoy Data Assimilation

The Search and Rescue at Sea Manual defines several uncertainties related to the initial position and the time elapsed between an accident and the onset of SAR operations. The present article seeks an approach to address this problem through the assimilation of drifting buoy data and their use in correcting the system parameters via an ill-posed inverse problem. The results demonstrate that, in the search for objects at sea, the uncertainty of their initial position must be explicitly considered. Quantitatively, the proposed methodology reduced the uncertainty of the initial search area by approximately 55–60% compared with the traditional approach that assumes a single deterministic initial point. This outcome underscores the potential of data assimilation techniques to enhance the probabilistic accuracy of maritime search and rescue planning.

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Publication Details

Journal
Mathematics
Published
2025-10-28
DOI
https://doi.org/10.3390/math13213435
Primary Topic
Ocean Waves and Remote Sensing
Type
article
Field-Weighted Citation Impact
0.00

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article

Identification of Initial Areas for Maritime Search and Rescue Operations Through Drifting Buoy Data Assimilation

Serguei A. Lonin, Jesús Navarro, Iván Plata, Carlos Romero-Balcucho
Mathematics
Ocean Waves and Remote Sensing
article

Identification of Initial Areas for Maritime Search and Rescue Operations Through Drifting Buoy Data Assimilation

Serguei A. Lonin, Jesús Navarro, Iván Plata, Carlos Romero-Balcucho
article en

Abstract

The Search and Rescue at Sea Manual defines several uncertainties related to the initial position and the time elapsed between an accident and the onset of SAR operations. The present article seeks an approach to address this problem through the assimilation of drifting buoy data and their use in correcting the system parameters via an ill-posed inverse problem. The results demonstrate that, in the search for objects at sea, the uncertainty of their initial position must be explicitly considered. Quantitatively, the proposed methodology reduced the uncertainty of the initial search area by approximately 55–60% compared with the traditional approach that assumes a single deterministic initial point. This outcome underscores the potential of data assimilation techniques to enhance the probabilistic accuracy of maritime search and rescue planning.

MathematicsVol. 13(21)
Universidad de Bogotá Jorge Tadeo Lozano (CO), Instituto Hidrográfico (PT), Science and Technology Corporation for Naval, Maritime and Riverine Industry Development (CO)
Science and Technology Directorate
Openalex Percentile: Top 69%
Ocean Waves and Remote Sensing
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Identification of Initial Areas for Maritime Search and Rescue Operations Through Drifting Buoy Data Assimilation — Serguei A. Lonin, Jesús Navarro, et al. · Mathematics (2025) | TGRS Research Map | TGRS