一種改進的局部線性回歸估計器及其在雷達高度計海況偏差估計中的應用

蔣茂飛; 許可; 劉亞龍; 王磊

doi:10.11999/JEIT151280

一種改進的局部線性回歸估計器及其在雷達高度計海況偏差估計中的應用

doi: 10.11999/JEIT151280 cstr: 32379.14.JEIT151280

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出版歷程
- 收稿日期: 2015-11-17
- 修回日期: 2016-05-05
- 刊出日期: 2016-09-19

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

摘要

摘要: 在建立雷達高度計海況偏差(Sea State Bias, SSB)非參數(shù)模型時，通常會用到局部線性回歸(Local Linear Regression, LLR)估計器，而傳統(tǒng)的局部線性回歸估計器涉及高維矩陣運算，當建模的數(shù)據(jù)量較大時，估計海況偏差需要大量的時間，從而使得非參數(shù)估計方法很難用于高維海況偏差模型。該文提出一種改進的局部線性回歸(Improved Local Linear Regression, ILLR)估計器，可以避免傳統(tǒng)的LLR估計器所需的高維矩陣運算，在不影響海況偏差估計結(jié)果的條件下，將局部線性回歸估計器獲取加權(quán)函數(shù)的時間復雜度由O(N2)降低為O(N)，從而大幅地降低估計海況偏差所需的時間，為實現(xiàn)高維非參數(shù)海況偏差模型的實時運算奠定了基礎。
- 雷達高度計 /
- 海況偏差 /
- 非參數(shù)估計 /
- LLR估計器
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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