刘经南, 曾文宪, 徐培亮. 整体最小二乘估计的研究进展[J]. 武汉大学学报 ( 信息科学版), 2013, 38(5): 505-512.
引用本文: 刘经南, 曾文宪, 徐培亮. 整体最小二乘估计的研究进展[J]. 武汉大学学报 ( 信息科学版), 2013, 38(5): 505-512.
LIU Jingnan, ZENG Wenxian, XU Peiliang. Overview of Total Least Squares Methods[J]. Geomatics and Information Science of Wuhan University, 2013, 38(5): 505-512.
Citation: LIU Jingnan, ZENG Wenxian, XU Peiliang. Overview of Total Least Squares Methods[J]. Geomatics and Information Science of Wuhan University, 2013, 38(5): 505-512.

整体最小二乘估计的研究进展

Overview of Total Least Squares Methods

  • 摘要: 整体最小二乘估计方法作为经典最小二乘估计方法的扩展,近20年来被广泛地应用于信号处理、计算机视觉、图像处理、通信工程以及大地测量与摄影测量等测绘相关领域,成为各专业领域进行数据处理的基本方法。概述了整体最小二乘估计的发展历史,从整体最小二乘估计的算法、统计特性和可靠性研究三方面综述了整体最小二乘估计方法的研究进展情况,侧重强调各种算法的本质特征,并对整体最小二乘估计的研究方向进行了展望。

     

    Abstract: Total least squares (TLS) is a basic estimation method to account for random errors in functional models and has found a wide variety of applications in different areas of science and engineering, including signal and image processing, computer vision, communication engineering and our own subject area (geodesy, photogrammetry, geomatics and GIS). The purpose of this paper is to briefly review TLS methods and algorithms, including a discussion of the accuracy of TLS estimates. Since reliability is of interest in our subject area, we will also briefly touch the reliability issue of TLS. Finally, we will outline some topics for further investigations in the future.

     

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