多波束测深趋势面系数的主成分估计  

Principal Components Estimation of Trend Surface Coefficients in Multibeam Bathymetry

作　　者：王海栋[1,2] 柴洪洲[1,3] 宋国大[2] 王君[2] 

机构地区：[1]解放军信息工程大学测绘学院,河南郑州450052 [2]海军出版社,天津300450 [3]海军海洋测绘研究所,天津300061

出　　处：《海洋测绘》2009年第5期5-7,共3页Hydrographic Surveying and Charting

基　　金：中国博士后科学基金(20080431342)

摘　　要：在多波束测深趋势面滤波构建趋势面模型的过程中,其模型变量线性相关时,系数阵存在复共线性,因此将主成分估计的方法应用于趋势面模型系数的求解,从而避免了复共线性的影响,最后通过实测数据进行实验,分别利用最小二乘算法和主成分估计求解二次趋势面模型。比较计算结果,验证了主成分估计算法的有效性。When the model of trend surface filter in multibeam bathymetry is constructed, the coeffcients matrix is multi-collinearity while variables of the model are linear correlation. For the above problem, the principal components estimation is used in calculating coefficients of the trend surface model in this paper, and it avoids the multi-collinearity. In the end, the experiment is made by the survey data. Least squares method and principal components estimation are used in calculating the model of the quadratic trend surface. The result is compared, and it is proved that principal components estimation is much better than least squares method.

关 键 词：多波束测深 趋势面滤波 复共线性 主成分估计 最小二乘法 

分 类 号：P204[天文地球—测绘科学与技术]