Weighted total least-squares joint adjustment with weight correction factors

• Published in: Communications in statistics. Simulation and computation Vol. 48; no. 9; pp. 2689 - 2707
• Main Authors: Wang, Leyang, Yu, Hang
• Format: Journal Article
• Language: English
• Published: Philadelphia Taylor & Francis 21.10.2019; Taylor & Francis Ltd
• Subjects: Affine transformations; Algorithms; Data points; Datasets; Errors-in-variables model; Helmert variance component estimation; Iterative algorithms; Iterative methods; Joint adjustment; Least squares; Parameter estimation; Stochastic models; Weight; Weight correction factor; Weighted total least squares

A joint adjustment involves integrating different types of geodetic datasets, or multiple datasets of the same data type, into a single adjustment. This paper applies the weighted total least-squares (WTLS) principle to joint adjustment problems and proposes an iterative algorithm for WTLS joint (WT...