Increasing numerical efficiency of iterative solution for total least-squares in datum transformations

Total Msplit estimation

“…Currently, an errors-in-variables (EIV) model, in which design matrix elements are also affected by random errors, is applied in many geodetic problems. For example, this model was applied in geodetic datum transformation (Teunissen 1988;Davis 1999;Acar et al 2006;Akyilmaz 2007;Schaffrin and Felus 2008;Mahboub 2012;Fang 2015;Aydin et al 2018;Mercan et al 2018)) as well as in remote sensing (Felus and Schaffrin 2005), in a function approximation (Wang and Zhao 2019), in linear regression (Schaffrin and Wieser 2008;Amiri-Simkooei and Jazaeri 2012;Zeng et al 2018;Lv and Sui 2020) and in the least-squares collocation (Schaffrin 2020;Wiśniewski and Kamiński 2020). The effect of the random design matrix on the weighted LS estimate is presented in .…”