| MIAO Hongli,JING Yujie,JIA Yongjun,LIN Mingsen,ZHANG Guoshou,WANG Guizhong. 2017. Nonparametric estimations of the sea state bias for a radar altimeter. Acta Oceanologica Sinica, 36(9):108－113 |
| Nonparametric estimations of the sea state bias for a radar altimeter |
| 雷达高度计海况偏差估计非参数模型研究 |
| Received:May 23, 2016 |
| DOI：10.1007/s13131-017-1116-x |
| Key words:radar altimeter sea state bias significant wave height wind speed nonparametric model parametric model |
| 中文关键词: 高度计 海况偏差 有效波高 风速 非参数模型 参数模型 |
| 基金项目:The National Key R&D Program of China under contract No. 2016YFC1401004; the National Natural Science Foundation of China under contract Nos 41406207, 41176157 and 41406197. |
| Author Name | Affiliation | E-mail | | MIAO Hongli | College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China | oumhl@ouc.edu.cn | | JING Yujie | College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China | | | JIA Yongjun | National Satellite Ocean Application Service, State Oceanic Administration, Beijing 100081, China | | | LIN Mingsen | National Satellite Ocean Application Service, State Oceanic Administration, Beijing 100081, China | | | ZHANG Guoshou | College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China | | | WANG Guizhong | College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China | |
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| Abstract: |
| To estimate the sea state bias (SSB) for radar altimeter, two nonparametric models, including a Nadaraya-Watson (NW) kernel estimator and a local linear regression (LLR) estimator, are studied based on the Jason-2 altimeter data. Selecting from different combinations of the Gaussian kernel function, spherical Epanechnikov kernel function, a fixed bandwidth and a local adjustable bandwidth, it is observed that the LLR method with the spherical Epanechnikov kernel function and the local adjustable bandwidth is the optimal nonparametric model for the SSB estimation. The comparisons between the nonparametric and parametric models are conducted and the results show that the nonparametric model performs relatively better at high-latitudes of the Northern Hemisphere. This method has been applied to the HY-2A altimeter as well and the same conclusion can be obtained. |
| 中文摘要: |
| 本文基于Jason-2高度计，采用核函数估计（NW）和局部线性回归估计(LLR)两种非参数估计方法，选用高斯(Gaussian)核函数和球谐(Epanechnikov)核函数及固定带宽和局部可调带宽。对不同组合形式的模型进行优选，确定LLR估计方法的Epanechnikov核函数、局部可调带宽为最优非参数模型。通过对最优非参数模型和参数模型结果进行对比分析表明，非参数模型在北高纬度区域表现更优，而在中低纬度及南纬区域参数模型不失优势。将非参数模型应用于我国HY-2A高度计，得到与以上同样的结论。 |
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