{"title":"基于主动协同目标摄影测量的海底沉管隧道对接定位","authors":"Huachuan Ma, Qingquan Li, Lin Tian, Zhipeng Chen, Xuhong Suo, Dejin Zhang","doi":"10.1111/mice.70064","DOIUrl":null,"url":null,"abstract":"Deep water, distant sea, unmanned is the inevitable trend of the development of marine engineering, the underwater positioning system for the accuracy, real‐time, and environmental adaptability of the aspects of the increasingly high requirements. The mainstream underwater positioning methods face limitations such as multipath effects, cost, water depth, and water quality, making it difficult to meet diverse needs. This study presents a novel underwater photogrammetry solution based on an active cooperative target that combines optical hardware with intelligent algorithms to achieve millimeter‐level positioning in complex marine environments. Specifically, the system designs and optimizes the hardware configuration, including binocular vision camera, LED array target, and auxiliary optics, through multi‐parameter association to ensure the continuity and stability of positioning. At the algorithmic level, a multilevel image processing module is established through spatiotemporal distribution analysis, expected template matching, physical light intensity modeling, and geometric configuration constraints, which effectively overcomes the dynamic occlusion, scattering degradation and feature extraction errors of cooperative targets. In a standard test cell, the system achieves an angular accuracy of 0.24° and a ranging accuracy of 0.72 mm. A number of positioning systems have been developed to assist in the docking of submarine immersed tube tunnels, and the absolute positioning error is still better than 5 mm even under dynamic high turbidity conditions, which proves its effectiveness.","PeriodicalId":156,"journal":{"name":"Computer-Aided Civil and Infrastructure Engineering","volume":"37 1","pages":""},"PeriodicalIF":9.1000,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Undersea immersed tube tunnel docking positioning via active cooperative target photogrammetry\",\"authors\":\"Huachuan Ma, Qingquan Li, Lin Tian, Zhipeng Chen, Xuhong Suo, Dejin Zhang\",\"doi\":\"10.1111/mice.70064\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Deep water, distant sea, unmanned is the inevitable trend of the development of marine engineering, the underwater positioning system for the accuracy, real‐time, and environmental adaptability of the aspects of the increasingly high requirements. The mainstream underwater positioning methods face limitations such as multipath effects, cost, water depth, and water quality, making it difficult to meet diverse needs. This study presents a novel underwater photogrammetry solution based on an active cooperative target that combines optical hardware with intelligent algorithms to achieve millimeter‐level positioning in complex marine environments. Specifically, the system designs and optimizes the hardware configuration, including binocular vision camera, LED array target, and auxiliary optics, through multi‐parameter association to ensure the continuity and stability of positioning. At the algorithmic level, a multilevel image processing module is established through spatiotemporal distribution analysis, expected template matching, physical light intensity modeling, and geometric configuration constraints, which effectively overcomes the dynamic occlusion, scattering degradation and feature extraction errors of cooperative targets. In a standard test cell, the system achieves an angular accuracy of 0.24° and a ranging accuracy of 0.72 mm. A number of positioning systems have been developed to assist in the docking of submarine immersed tube tunnels, and the absolute positioning error is still better than 5 mm even under dynamic high turbidity conditions, which proves its effectiveness.\",\"PeriodicalId\":156,\"journal\":{\"name\":\"Computer-Aided Civil and Infrastructure Engineering\",\"volume\":\"37 1\",\"pages\":\"\"},\"PeriodicalIF\":9.1000,\"publicationDate\":\"2025-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer-Aided Civil and Infrastructure Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1111/mice.70064\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer-Aided Civil and Infrastructure Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1111/mice.70064","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Undersea immersed tube tunnel docking positioning via active cooperative target photogrammetry
Deep water, distant sea, unmanned is the inevitable trend of the development of marine engineering, the underwater positioning system for the accuracy, real‐time, and environmental adaptability of the aspects of the increasingly high requirements. The mainstream underwater positioning methods face limitations such as multipath effects, cost, water depth, and water quality, making it difficult to meet diverse needs. This study presents a novel underwater photogrammetry solution based on an active cooperative target that combines optical hardware with intelligent algorithms to achieve millimeter‐level positioning in complex marine environments. Specifically, the system designs and optimizes the hardware configuration, including binocular vision camera, LED array target, and auxiliary optics, through multi‐parameter association to ensure the continuity and stability of positioning. At the algorithmic level, a multilevel image processing module is established through spatiotemporal distribution analysis, expected template matching, physical light intensity modeling, and geometric configuration constraints, which effectively overcomes the dynamic occlusion, scattering degradation and feature extraction errors of cooperative targets. In a standard test cell, the system achieves an angular accuracy of 0.24° and a ranging accuracy of 0.72 mm. A number of positioning systems have been developed to assist in the docking of submarine immersed tube tunnels, and the absolute positioning error is still better than 5 mm even under dynamic high turbidity conditions, which proves its effectiveness.
期刊介绍:
Computer-Aided Civil and Infrastructure Engineering stands as a scholarly, peer-reviewed archival journal, serving as a vital link between advancements in computer technology and civil and infrastructure engineering. The journal serves as a distinctive platform for the publication of original articles, spotlighting novel computational techniques and inventive applications of computers. Specifically, it concentrates on recent progress in computer and information technologies, fostering the development and application of emerging computing paradigms.
Encompassing a broad scope, the journal addresses bridge, construction, environmental, highway, geotechnical, structural, transportation, and water resources engineering. It extends its reach to the management of infrastructure systems, covering domains such as highways, bridges, pavements, airports, and utilities. The journal delves into areas like artificial intelligence, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, internet-based technologies, knowledge discovery and engineering, machine learning, mobile computing, multimedia technologies, networking, neural network computing, optimization and search, parallel processing, robotics, smart structures, software engineering, virtual reality, and visualization techniques.