| 多波束测深误差改进模型构建与验证EI北大核心CSCD |
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| 引用本文： | 李凡,金绍华,边刚,崔杨,汤寓麟,张永厚.多波束测深误差改进模型构建与验证EI北大核心CSCD[J].测绘学报,2022,51(5):762-771. |
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| 作者姓名： | 李凡 金绍华 边刚 崔杨 汤寓麟 张永厚 |
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| 作者单位： | 1. 92899部队, 浙江 宁波 315300;2. 海军大连舰艇学院军事海洋与测绘系, 辽宁 大连 116018;3. 海军工程大学电气工程学院, 湖北 武汉 430033;4. 海图信息中心, 天津 300450 |
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| 基金项目： | 国家自然科学基金(41876103;41576105)~~； |
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| 摘 要： | 为更准确地评估多波束测量数据质量,以常梯度声线跟踪模型为基础,结合Rob Hare经典误差分类,构建了回波检测方式、吃水改正和升沉改正误差综合影响下的多波束测深误差改进模型。通过对实例误差源分解对比和交叉点中误差对比分析,验证了改进模型的正确性。实例计算表明,该模型较Rob Hare模型可减少CUBE曲面2%的交叉点中误差,验证了改进模型的有效性和优势。改进模型考虑的误差因素更多,误差成因分析更为完善,有助于更准确地分析各误差源导致的误差量级大小,研究成果为数据质量控制、数据检核提供理论依据和技术支撑。
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| 关 键 词： | 海道测量 多波束测深 误差模型 误差分类 误差源分析 CUBE |
| 收稿时间： | 2020-10-12 |
| 修稿时间： | 2021-10-31 |
Construction and verification of improved error model of MBES |
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| LI Fan,JIN Shaohua,BIAN Gang,CUI Yang,TANG Yulin,ZHANG Yonghou.Construction and verification of improved error model of MBES[J].Acta Geodaetica et Cartographica Sinica,2022,51(5):762-771. |
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| Authors: | LI Fan JIN Shaohua BIAN Gang CUI Yang TANG Yulin ZHANG Yonghou |
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| Institution: | 1. Troops 92899, Ningbo 315300, China;2. Department of Hydrography and Cartography, Dalian Naval Academy, Dalian 116018, China;3. College of Electrical Engineering, Naval University of Engineering, Wuhan 430033, China;4. Chart Information Center, Tianjin 300450, China |
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| Abstract: | To evaluate the quality of MBES's data more accurately, an improved error model is derived that combines effects of echo detection methods and draft and heave correction errors, based on the constant gradient sound velocity tracking model and Rob Hare's classic error classification. The correctness of the improved model is verified through the decomposition and comparison of error sources and the comparison of the errors in the intersections; the example calculations show that the model can reduce the errors in the intersections of the CUBE surface by 2% compared with the Rob Hare model. The improved model considers more error factors, describes the error distribution law of measuring points more finely, and the error composition is more perfect. The improved model is helpful to find out the problem and strip the error source, analyze the magnitude of the error caused by each error source more accurately, and the research results provide theoretical basis and technical support for data quality control and data verification. |
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