贝叶斯估计在水深格网节点信息估算中的应用

Application of Bayes Estimator in Node Information Estimating

离散数据格网化是目前表达高程和地形方法的前期工作和基础,而格网化的关键是如何利用节点周围的水深值序列推估格网节点水深值及其不确定度值。为解决这一问题,提出了基于贝叶斯估计理论的估计格网节点水深值及水深不确定度的方法,该方法具有独特的估计优势,可以很好的运用测量值和专家经验,得到可靠性较高的节点水深值和水深不确定度,对海底地形显示及数据质量估计具有一定的参考意义。

Gridding of discrete data is the foundation and prophase of altitude and terrain presentation, and the key work of network is how to make great use of the soundings around the node to deduce the depth and TVU of node. In order to resolve this problem, a estimation model is put forward based on Bayes Estimator in this paper, which can be good at using survey data and experience of experts to gain more reliable depth and TVU of node, and it is significant to the topography of sea and data quality estimation.