Improved Local Linear Regression Estimator and Its Application to Estimation for Radar Altimeter Sea State Bias

JIANG Maofei; XU Ke; LIU Yalong; WANG Lei

doi:10.11999/JEIT151280

Volume 38 Issue 9

Sep. 2016

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Article Navigation > Journal of Electronics & Information Technology > 2016 > 38(9): 2314-2320

JIANG Maofei, XU Ke, LIU Yalong, WANG Lei. Improved Local Linear Regression Estimator and Its Application to Estimation for Radar Altimeter Sea State Bias[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2314-2320. doi: 10.11999/JEIT151280

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JIANG Maofei, XU Ke, LIU Yalong, WANG Lei. Improved Local Linear Regression Estimator and Its Application to Estimation for Radar Altimeter Sea State Bias[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2314-2320. doi: 10.11999/JEIT151280

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Improved Local Linear Regression Estimator and Its Application to Estimation for Radar Altimeter Sea State Bias

doi: 10.11999/JEIT151280 cstr: 32379.14.JEIT151280

Received Date: 2015-11-17
Rev Recd Date: 2016-05-05
Publish Date: 2016-09-19

Abstract

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 fromO(N2)toO(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.
- Radar altimeter,
- Sea state bias,
- Nonparametric estimation,
- Local Linear Regression (LLR) estimator

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References(20)

References

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