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| Improved Local Linear Regression Estimator and Its Application to Estimation for Radar Altimeter Sea State Bias |
| JIANG Maofei①②③ XU Ke①② LIU Yalong④ WANG Lei①② |
①(Key Laboratory of Microwave Remote Sensing, Chinese Academy of Sciences, Beijing 100190, China)
②(National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China)
③(University of Chinese Academy of Sciences, Beijing 100049, China)
④(Yantai Marine Environmental Monitoring Center Station, State Oceanic Administration, Yantai 264000, China) |
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Abstract The Local Linear Regression (LLR) estimator is usually used when developing a nonparametric model for radar altimeter Sea State Bias (SSB). However, the conventional LLR estimator contains matrices with high dimension. When a large number of data are used to develop the SSB model, the SSB estimation costs too much time. Therefore, the nonparametric estimation method can hardly be used to develop high-dimensional SSB models. This paper presents an Improved LLR (ILLR) estimator, complexity from O(N2) to O(N) which can avoid high-dimensional matrix operations. The improved LLR estimator can greatly reduce the time for SSB estimation without affecting the estimated accuracy. So the improved LLR estimator can laid the foundation for high-dimensional SSB models.
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Received: 17 November 2015
Published: 12 June 2016
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Corresponding Authors:
XU Ke
E-mail: xuke@mirslab.cn
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