全球导航卫星系统-声呐组合观测模型分类体系
Global navigation satellite system-acoustic combined observation model classification system
薛树强 1杨元喜 2肖圳 3赵爽 1李保金3
作者信息
- 1. 中国测绘科学研究院大地测量与导航定位研究所,北京 100830;西安测绘研究所地理信息工程国家重点实验室,陕西西安 710054
- 2. 西安测绘研究所地理信息工程国家重点实验室,陕西西安 710054
- 3. 中国测绘科学研究院大地测量与导航定位研究所,北京 100830
- 折叠
摘要
本文回顾了海底大地测量全球导航卫星系统-声呐观测模型近二十年来的发展,以声速误差处理为主线给出了全球导航卫星系统-声呐观测模型的分类体系,按函数模型、随机模型和约束条件进行了归纳,探讨了未来发展方向.研究表明:测距定位模型无需现场声速剖面测量,但需解决声速垂向梯度影响的有效参数化估计或改正问题;海底大地测量更为关注声速时空变化对观测值影响,为此推荐采用声速场误差加性补偿模型及其导出的声速场参数间接估计模型;海底局域网阵列存在类似共模环境误差,具有提升海洋环境参数估计及海底定位精度的能力.
Abstract
This paper reviews the development of the global navigation satellite system(GNSS)-acoustic observa-tion model in the seafloor geodesy over the past two decades.With a focus on the processing of sound speed errors,the classification system of the GNSS-acoustic observation models is presented,and these models are summarized according to the functional and stochastic models and constraint conditions.In addition,future development direc-tions are discussed.It shows that the range-based positioning models do not need an in-field sound velocity profile measurement,but they must address effective parameterization estimation or correction of the vertical gradient effect of sound velocity.The seafloor geodesy is more concerned with the impact of spatiotemporal variations in the sound speed on observations.Thus,we recommend using an error compensation model for the sound speed field and an indirectly estimated model for sound speed field parameters.There are similar common-mode environmental error features in the seafloor local network arrays;thus,the seafloor arrays can enhance the estimation of ocean environ-mental parameters and further improve the seafloor positioning accuracy.
关键词
海底大地测量/全球导航卫星系统/声呐/水下定位/参考声速/声速误差/补偿模型/声速场反演/天顶延迟/参数估计Key words
seafloor geodesy/global navigation satellite system/sona/underwater positioning/reference sound speed/sound speed error/compensation model/inversion of sound speed field/zenith delay/parameter estimation引用本文复制引用
基金项目
国家自然科学基金(41931076)
崂山实验室科技创新项目(LSKJ202205100)
崂山实验室科技创新项目(LSKJ202205105)
出版年
2023
国家科技期刊平台
NSTL
维普
万方数据