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顾及声线高度角的水下定位随机模型优化
引用本文:刘以旭,薛树强,卢秀山,王薪普,齐珂,王胜利.顾及声线高度角的水下定位随机模型优化[J].海洋测绘,2021(5):21-25.
作者姓名:刘以旭  薛树强  卢秀山  王薪普  齐珂  王胜利
作者单位:山东科技大学 测绘与空间信息学院,山东 青岛 266590;中国测绘科学研究院大地测量与地球动力学研究所,北京 100830;山东科技大学 海洋科学与工程学院,山东 青岛 266590;山东理工大学 建筑工程学院,山东 淄博 255049
基金项目:国家自然科学基金(41931076);国家重点研发计划(2018YFB1600300;2018YFB1600302)
摘    要:先验随机模型本身的误差会给参数估计带来随机性影响,水下定位等权随机模型简单却不符合实际。基于这一事实,在水下声纳定位模型和随机模型基础上,讨论了随机模型不完善对参数估计的影响。考虑了影响定位主要误差源与高度角之间的关系,结合统计经验提出了基于声线高度角相关的水下定位随机模型。试验表明,优化后的高度角相关随机模型在定位精度上较等权随机模型有所提高。因此,在水下定位中,应减少低高度角观测值的权重,利用提出的随机模型可以减小高度角观测误差对定位精度的影响。

关 键 词:水下定位  声线跟踪  等权随机模型  参数估计  声线高度角

Optimization on underwater positioning stochastic model based on sound ray elevation angle
LIU Yixu,XUE Shuqiang,LU Xiushan,WANG Xinpu,QI Ke,WANG Shengli.Optimization on underwater positioning stochastic model based on sound ray elevation angle[J].Hydrographic Surveying and Charting,2021(5):21-25.
Authors:LIU Yixu  XUE Shuqiang  LU Xiushan  WANG Xinpu  QI Ke  WANG Shengli
Institution:College of Geodesy and Geomatics,Shandong University of Science and Technology,Qingdao 266590 ,China;Institute of Geodesy and Geomatics,Chinese Academy of Surveying and mapping,Beijing 100830 ,China;College of Ocean Science and Engineering,Shandong University of Science and Technology,Qingdao 266590 ,China;School of Architectural Engineering,Shandong University of Technology,Zibo 255049 ,China
Abstract:The error of the a priori random model itself will bring random influence to the parameter estimation,and the equal-weight Stochastic model for underwater positioning is simple but not practical.Based on the underwater sonar localization model and the stochastic model,this paper discusses the impact of the imperfect stochastic model on parameter estimation.Considering the relationship between the main error that affect the positioning accuracy and the elevation angle,combined with statistical experience,a stochastic model of underwater positioning based on the elevation angle is established.Experimental results show that the optimized elevation-angle-related random model has a greater improvement in positioning accuracy than the equal-weight random model.Therefore, the weight of low elevation angle observations should be reduced in underwater positioning.Using the random model proposed in this paper can reduce the impact of elevation angle observation errors on positioning accuracy.
Keywords:
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