Rethinking Maritime Search Patterns from an IAMSAR Perspective: A Scenario-Based Evaluation of Novel Patterns

Search and Rescue (SAR) operations are conducted to locate and safely rescue individuals or objects in distress as rapidly as possible following maritime emergencies. In this process, operational performance depends not only on determining the target’s probable location but also on the specific search pattern used to scan the search area. The aim of this study is to develop alternative search patterns to the parallel and expanding square search patterns used within the International Aeronautical and Maritime Search and Rescue (IAMSAR) methodology. To this end, Hilbert, Moore, Morton, V-formation, pentagonal, hexagonal, octagonal, and spiral search patterns were mathematically defined and rendered for algorithmic implementation. The patterns underwent a three-stage evaluation process. The first stage assessed baseline performance independently of external factors; the second stage evaluated behaviour under different initial target locations; and the third stage assessed target detection performance for five distinct types of drifting targets under varying wind, current, and search area conditions. The results revealed that the Moore pattern achieved the highest number of fastest target detections in the parallel search group, followed by the Hilbert pattern, while the Morton pattern stood out in terms of second-fastest detection counts. In the expanding square search group, the spiral pattern achieved the highest number of fastest target detections, followed by the hexagonal and expanding square patterns, while the expanding square pattern ranked first in second-fastest detection counts, followed by the octagonal pattern. However, the relative performance of the patterns varied depending on search area size and environmental conditions. The study’s primary contribution is treating search pattern selection as an independent SAR planning variable, offering viable alternatives to IAMSAR patterns, and establishing a reproducible, extensible framework through mathematical and algorithmic definitions that can be used in future optimisation, decision support, and area-scanning initiatives. In doing so, the study frames the question “which search pattern can most effectively cover the designated search area?” as a systematic research problem alongside the fundamental SAR question: “Where should the target be searched for?”