J. Eur. Opt. Society-Rapid Publ. 2026, 22, 6 Ó The Author( s), published by EDP Sciences, 2026 https:// doi. org / 10.1051 / jeos / 2026001 Available online at: https:// jeos. edpsciences. org
Journal of the European Optical Society-Rapid Publications
RESEARCH ARTICLE
Underwater 3D target detection: Semi-analytic Monte Carlo model and UAV-based scanning lidar system
Xinke Hao 1, 2, 3, Yan He 1, 2, 3,*, Huixin He 1, 3, Deliang Lv 1, 3, Yingjie Ruan 1, 2, 3, Hui Qi 1, 3, 4, Guangxiu Xu 5, and Junwu Tang 6
1 Aerospace Laser Technology and System Department, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, PR China 2 Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, PR China 3 Wangzhijiang Innovation Center for Laser, Aerospace Laser Technology and System Department, Shanghai Institute of Optics and
Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, PR China 4 School of Physical Science and Technology, Shanghai Tech University, Shanghai 201210, PR China 5 Naval Research Institute, Tianjin 300061, PR China 6 Laoshan Laboratory, Qingdao 266237, PR China
Received 26 November 2025 / Accepted 3 January 2026
Abstract. Lidar has been widely applied in marine research due to its strong penetration capability in water. To study the lidar detection of underwater targets, a semi-Monte Carlo model of target detection( MCT) is developed to simulate the scanning signals, incorporating three-dimensional interaction processes between the beam and the target, the wind-driven surface waves and stratified water columns. A UAV-based linear scanning oceanic lidar system( SOL) is developed for model validation. The model is validated by the lidar equation results with a less than 5 % mean relative error within the upper 50 m, and further confirmed by the SOL field experiments through consistent target localization. The detection capabilities of SOL are analyzed based on the MCT model for Jerlov II and Jerlov 3C water types, and an extended detection range is introduced to evaluate the variation of horizontal scanning resolution with target depth, providing guidance for balancing detection capability and efficiency under varying conditions.
Keywords: Lidar application, Monte Carlo method, UAV-based lidar, Underwater target detection.
1 Introduction
Ocean plays a vital role in regulating the global climate, sustaining biodiversity, and supporting essential resource [ 1 – 3 ]. Ocean sensing is therefore a fundamental prerequisite for understanding and sustainably utilizing the ocean. However, conventional detection methods face intrinsic limitations: sonar systems aren’ t able to detect through air – water interface, while passive satellite remote sensing is not able to provide the vertical information on the upper ocean layers [ 4 – 7 ]. Among ocean sensing techniques, Light Detection and Ranging( Lidar) has emerged as an effective alternative. As an active remote sensing system, lidar penetrates the air – water interface and captures high spatial and temporal resolution profiles of subsurface structures [ 8 – 10 ]. These capabilities establish lidar as an essential complement to existing ocean sensing approaches.
* Corresponding author: heyan @ siom. ac. cn
Lidars has been developed for diverse applications, among which one of the earliest and most prominent uses is topobathymetry [ 11 ]. Modern topobathymetry lidar systems are capable of achieving high-precision integrated coastal and terrestrial topographic mapping [ 12 – 15 ], seabed substrate classification [ 10, 16 ], as well as surveying in turbid waters and shallow areas [ 17 ]. Moreover, lidar profiling information provides essential support for studying marine organisms and retrieving seawater optical properties. Investigating the distribution and dynamics of phytoplankton [ 18 – 22 ] based on lidar profiling data contributes to a deeper understanding of the mechanisms driving marine primary productivity and the global carbon cycle. Lidar has also been proven to be highly effective in surveying fishery resources [ 23 – 27 ] near the sea surface, and its performance on deriving optical properties [ 28 – 32 ], such as the attenuation coefficient and volume backscattering, has been validated by shipborne in-situ measurements. Additionally, lidar enables measurements of wave characteristics without contacting the water body or disturbing
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